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Posted to commits@tvm.apache.org by tq...@apache.org on 2026/10/10 16:13:21 UTC
(tvm-site) branch asf-site updated: deploying docs (apache/tvm@9059d9d25149c9ca7a015717b5023d1e2e1185fd)
This is an automated email from the ASF dual-hosted git repository.
tqchen pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/tvm-site.git
The following commit(s) were added to refs/heads/asf-site by this push:
new 0662f3fd571 deploying docs (apache/tvm@9059d9d25149c9ca7a015717b5023d1e2e1185fd)
0662f3fd571 is described below
commit 0662f3fd5717aebfd182febe4909deb7a90ac2b3
Author: tvm-bot <95...@users.noreply.github.com>
AuthorDate: Sat Oct 10 16:13:14 2026 +0000
deploying docs (apache/tvm@9059d9d25149c9ca7a015717b5023d1e2e1185fd)
---
.../import_model.zip | Bin 35138 -> 35138 bytes
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.../tir_transformation.zip | Bin 15988 -> 15988 bytes
.../meta_schedule.zip | Bin 24227 -> 24227 bytes
.../mix_python_and_tvm_with_pymodule.zip | Bin 38284 -> 38284 bytes
.../relax_creation.zip | Bin 22449 -> 22449 bytes
.../relax_transformation.zip | Bin 11474 -> 11474 bytes
.../optimize_llm.zip | Bin 53997 -> 53997 bytes
.../bring_your_own_codegen.zip | Bin 36295 -> 36295 bytes
.../e2e_opt_model.zip | Bin 14473 -> 14473 bytes
.../quick_start.zip | Bin 16252 -> 16252 bytes
.../export_and_load_executable.zip | Bin 31408 -> 31408 bytes
.../tir_creation.zip | Bin 24464 -> 24464 bytes
.../cross_compilation_and_rpc.zip | Bin 62282 -> 62282 bytes
.../customize_opt.zip | Bin 20510 -> 20510 bytes
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--- a/docs/_sources/deep_dive/relax/tutorials/relax_creation.rst
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@@ -89,11 +89,11 @@ high-level Relax operators using TVMScript.
@R.function
def forward(data: R.Tensor((n, 784), dtype="float32"), w0: R.Tensor((128, 784), dtype="float32"), b0: R.Tensor((128,), dtype="float32"), w1: R.Tensor((10, 128), dtype="float32"), b1: R.Tensor((10,), dtype="float32")) -> R.Tensor((n, 10), dtype="float32"):
with R.dataflow():
- lv: R.Tensor((784, 128), dtype="float32") = I.Call("relax.permute_dims", [w0], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 128), dtype="float32"))
+ lv: R.Tensor((784, 128), dtype="float32") = R.permute_dims(w0)
lv1: R.Tensor((n, 128), dtype="float32") = I.Call("relax.matmul", [data, lv], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 128), dtype="float32"))
lv0: R.Tensor((n, 128), dtype="float32") = R.add(lv1, b0, ty=R.Tensor((n, 128), dtype="float32"))
lv1_1: R.Tensor((n, 128), dtype="float32") = R.nn.relu(lv0)
- lv4: R.Tensor((128, 10), dtype="float32") = I.Call("relax.permute_dims", [w1], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((128, 10), dtype="float32"))
+ lv4: R.Tensor((128, 10), dtype="float32") = R.permute_dims(w1)
lv5: R.Tensor((n, 10), dtype="float32") = I.Call("relax.matmul", [lv1_1, lv4], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 10), dtype="float32"))
lv2: R.Tensor((n, 10), dtype="float32") = R.add(lv5, b1, ty=R.Tensor((n, 10), dtype="float32"))
R.output(lv2)
@@ -175,18 +175,18 @@ TensorIR functions in Relax function.
with Ts.sblock("relu"):
v = Ts.axis.spatial(n, i, dtype="int64")
v_1 = Ts.axis.spatial(m, j, dtype="int64")
- Ts.reads(X[v, v_1])
- Ts.writes(Y[v, v_1])
+ Ts.reads(X[v, v_1:v_1 + T.int64(1)])
+ Ts.writes(Y[v, v_1:v_1 + T.int64(1)])
Y[v, v_1] = T.max(X[v, v_1], T.float32(0.0))
@R.function
def forward(data: R.Tensor((n, 784), dtype="float32"), w0: R.Tensor((128, 784), dtype="float32"), b0: R.Tensor((128,), dtype="float32"), w1: R.Tensor((10, 128), dtype="float32"), b1: R.Tensor((10,), dtype="float32")) -> R.Tensor((n, 10), dtype="float32"):
with R.dataflow():
- lv: R.Tensor((784, 128), dtype="float32") = I.Call("relax.permute_dims", [w0], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 128), dtype="float32"))
+ lv: R.Tensor((784, 128), dtype="float32") = R.permute_dims(w0)
lv1: R.Tensor((n, 128), dtype="float32") = I.Call("relax.matmul", [data, lv], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 128), dtype="float32"))
lv0: R.Tensor((n, 128), dtype="float32") = R.add(lv1, b0, ty=R.Tensor((n, 128), dtype="float32"))
- lv1_1 = R.call_tir(Module.relu, I.Tuple([lv0]), ty_args=[R.Tensor((n, 128), dtype="float32")])
- lv4: R.Tensor((128, 10), dtype="float32") = I.Call("relax.permute_dims", [w1], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((128, 10), dtype="float32"))
+ lv1_1 = R.call_tir(Module.relu, (lv0,), ty_args=[R.Tensor((n, 128), dtype="float32")])
+ lv4: R.Tensor((128, 10), dtype="float32") = R.permute_dims(w1)
lv5: R.Tensor((n, 10), dtype="float32") = I.Call("relax.matmul", [lv1_1, lv4], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 10), dtype="float32"))
lv2: R.Tensor((n, 10), dtype="float32") = R.add(lv5, b1, ty=R.Tensor((n, 10), dtype="float32"))
R.output(lv2)
@@ -293,11 +293,11 @@ After we define the NNModule, we can export it to TVM IRModule via
def forward(x: R.Tensor((n, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 128), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 128), dtype="float32"))
+ permute_dims: R.Tensor((784, 128), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((n, 128), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 128), dtype="float32"))
add: R.Tensor((n, 128), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((n, 128), dtype="float32"))
relu: R.Tensor((n, 128), dtype="float32") = R.nn.relu(add)
- permute_dims1: R.Tensor((128, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((128, 10), dtype="float32"))
+ permute_dims1: R.Tensor((128, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((n, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 10), dtype="float32"))
add1: R.Tensor((n, 10), dtype="float32") = R.add(matmul1, fc2_bias, ty=R.Tensor((n, 10), dtype="float32"))
gv: R.Tensor((n, 10), dtype="float32") = add1
@@ -406,8 +406,8 @@ Tensor Expression(TE), TensorIR functions or other TVM packed functions.
with Ts.sblock("compute"):
v_i0 = Ts.axis.spatial(n, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(128), i1, dtype="int64")
- Ts.reads(env_linear[v_i0, v_i1])
- Ts.writes(compute[v_i0, v_i1])
+ Ts.reads(env_linear[v_i0, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(compute[v_i0, v_i1:v_i1 + T.int64(1)])
compute[v_i0, v_i1] = T.max(env_linear[v_i0, v_i1], T.float32(0.0))
@Ts.function
@@ -422,8 +422,8 @@ Tensor Expression(TE), TensorIR functions or other TVM packed functions.
v = Ts.axis.spatial(M, i, dtype="int64")
v_1 = Ts.axis.spatial(N, j, dtype="int64")
v_2 = Ts.axis.reduce(K, k, dtype="int64")
- Ts.reads(X[v, v_2], W[v_1, v_2])
- Ts.writes(Z[v, v_1])
+ Ts.reads(X[v, v_2:v_2 + T.int64(1)], W[v_1, v_2:v_2 + T.int64(1)])
+ Ts.writes(Z[v, v_1:v_1 + T.int64(1)])
with Ts.init():
Z[v, v_1] = T.float32(0.0)
Z[v, v_1] = Z[v, v_1] + X[v, v_2] * W[v_1, v_2]
@@ -432,17 +432,17 @@ Tensor Expression(TE), TensorIR functions or other TVM packed functions.
with Ts.sblock("add"):
v_3 = Ts.axis.spatial(M, i_1, dtype="int64")
v_4 = Ts.axis.spatial(N, j_1, dtype="int64")
- Ts.reads(Z[v_3, v_4], B[v_4])
- Ts.writes(Z[v_3, v_4])
+ Ts.reads(Z[v_3, v_4:v_4 + T.int64(1)], B[v_4:v_4 + T.int64(1)])
+ Ts.writes(Z[v_3, v_4:v_4 + T.int64(1)])
Z[v_3, v_4] = Z[v_3, v_4] + B[v_4]
@R.function
def forward(x: R.Tensor((n_1, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n_1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- env_linear = R.call_dps_packed("env.linear", I.Tuple([x, fc1_weight, fc1_bias]), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
- lv = R.call_tir(Module.relu, I.Tuple([env_linear]), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
- lv1 = R.call_tir(Module.tir_linear, I.Tuple([lv, fc2_weight, fc2_bias]), ty_args=[R.Tensor((n_1, 10), dtype="float32")])
+ env_linear = R.call_dps_packed("env.linear", (x, fc1_weight, fc1_bias), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
+ lv = R.call_tir(Module.relu, (env_linear,), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
+ lv1 = R.call_tir(Module.tir_linear, (lv, fc2_weight, fc2_bias), ty_args=[R.Tensor((n_1, 10), dtype="float32")])
gv: R.Tensor((n_1, 10), dtype="float32") = lv1
R.output(gv)
return gv
@@ -502,11 +502,11 @@ customized pass.
@R.function
def forward(x: R.Tensor((n, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n, 10), dtype="float32"):
with R.dataflow():
- lv: R.Tensor((784, 128), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 128), dtype="float32"))
+ lv: R.Tensor((784, 128), dtype="float32") = R.permute_dims(fc1_weight)
lv1: R.Tensor((n, 128), dtype="float32") = I.Call("relax.matmul", [x, lv], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 128), dtype="float32"))
lv2: R.Tensor((n, 128), dtype="float32") = R.add(lv1, fc1_bias, ty=R.Tensor((n, 128), dtype="float32"))
lv3: R.Tensor((n, 128), dtype="float32") = R.nn.relu(lv2)
- lv4: R.Tensor((128, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((128, 10), dtype="float32"))
+ lv4: R.Tensor((128, 10), dtype="float32") = R.permute_dims(fc2_weight)
lv5: R.Tensor((n, 10), dtype="float32") = I.Call("relax.matmul", [lv3, lv4], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 10), dtype="float32"))
lv6: R.Tensor((n, 10), dtype="float32") = R.add(lv5, fc2_bias, ty=R.Tensor((n, 10), dtype="float32"))
gv: R.Tensor((n, 10), dtype="float32") = lv6
@@ -584,8 +584,8 @@ Relax functions, TensorIR functions and other TVM packed functions.
with Ts.sblock("compute"):
v_i0 = Ts.axis.spatial(n, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(128), i1, dtype="int64")
- Ts.reads(lv[v_i0, v_i1])
- Ts.writes(compute[v_i0, v_i1])
+ Ts.reads(lv[v_i0, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(compute[v_i0, v_i1:v_i1 + T.int64(1)])
compute[v_i0, v_i1] = T.max(lv[v_i0, v_i1], T.float32(0.0))
@Ts.function
@@ -600,8 +600,8 @@ Relax functions, TensorIR functions and other TVM packed functions.
v = Ts.axis.spatial(M, i, dtype="int64")
v_1 = Ts.axis.spatial(N, j, dtype="int64")
v_2 = Ts.axis.reduce(K, k, dtype="int64")
- Ts.reads(X[v, v_2], W[v_1, v_2])
- Ts.writes(Z[v, v_1])
+ Ts.reads(X[v, v_2:v_2 + T.int64(1)], W[v_1, v_2:v_2 + T.int64(1)])
+ Ts.writes(Z[v, v_1:v_1 + T.int64(1)])
with Ts.init():
Z[v, v_1] = T.float32(0.0)
Z[v, v_1] = Z[v, v_1] + X[v, v_2] * W[v_1, v_2]
@@ -610,16 +610,16 @@ Relax functions, TensorIR functions and other TVM packed functions.
with Ts.sblock("add"):
v_3 = Ts.axis.spatial(M, i_1, dtype="int64")
v_4 = Ts.axis.spatial(N, j_1, dtype="int64")
- Ts.reads(Z[v_3, v_4], B[v_4])
- Ts.writes(Z[v_3, v_4])
+ Ts.reads(Z[v_3, v_4:v_4 + T.int64(1)], B[v_4:v_4 + T.int64(1)])
+ Ts.writes(Z[v_3, v_4:v_4 + T.int64(1)])
Z[v_3, v_4] = Z[v_3, v_4] + B[v_4]
@R.function
def forward(x: R.Tensor((n_1, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n_1, 10), dtype="float32"):
with R.dataflow():
- lv = R.call_dps_packed("env.linear", I.Tuple([x, fc1_weight, fc1_bias]), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
- lv1 = R.call_tir(Module.relu, I.Tuple([lv]), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
- lv2 = R.call_tir(Module.tir_linear, I.Tuple([lv1, fc2_weight, fc2_bias]), ty_args=[R.Tensor((n_1, 10), dtype="float32")])
+ lv = R.call_dps_packed("env.linear", (x, fc1_weight, fc1_bias), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
+ lv1 = R.call_tir(Module.relu, (lv,), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
+ lv2 = R.call_tir(Module.tir_linear, (lv1, fc2_weight, fc2_bias), ty_args=[R.Tensor((n_1, 10), dtype="float32")])
gv: R.Tensor((n_1, 10), dtype="float32") = lv2
R.output(gv)
return lv2
diff --git a/docs/_sources/deep_dive/relax/tutorials/relax_transformation.rst b/docs/_sources/deep_dive/relax/tutorials/relax_transformation.rst
index e4adbdc5bdb..65fef19c9f2 100644
--- a/docs/_sources/deep_dive/relax/tutorials/relax_transformation.rst
+++ b/docs/_sources/deep_dive/relax/tutorials/relax_transformation.rst
@@ -78,11 +78,11 @@ the :ref:`previous section <relax-creation>`.
def forward(x: R.Tensor((n, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 128), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 128), dtype="float32"))
+ permute_dims: R.Tensor((784, 128), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((n, 128), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 128), dtype="float32"))
add: R.Tensor((n, 128), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((n, 128), dtype="float32"))
relu: R.Tensor((n, 128), dtype="float32") = R.nn.relu(add)
- permute_dims1: R.Tensor((128, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((128, 10), dtype="float32"))
+ permute_dims1: R.Tensor((128, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((n, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 10), dtype="float32"))
add1: R.Tensor((n, 10), dtype="float32") = R.add(matmul1, fc2_bias, ty=R.Tensor((n, 10), dtype="float32"))
gv: R.Tensor((n, 10), dtype="float32") = add1
@@ -144,8 +144,8 @@ into low-level operators.
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(n, ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(128), ax1, dtype="int64")
- Ts.reads(matmul[v_ax0, v_ax1], fc1_bias[v_ax1])
- Ts.writes(T_add[v_ax0, v_ax1])
+ Ts.reads(matmul[v_ax0, v_ax1:v_ax1 + T.int64(1)], fc1_bias[v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add[v_ax0, v_ax1] = matmul[v_ax0, v_ax1] + fc1_bias[v_ax1]
@Ts.function(private=True)
@@ -159,8 +159,8 @@ into low-level operators.
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(n_1, ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(matmul1[v_ax0, v_ax1], fc2_bias[v_ax1])
- Ts.writes(T_add[v_ax0, v_ax1])
+ Ts.reads(matmul1[v_ax0, v_ax1:v_ax1 + T.int64(1)], fc2_bias[v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add[v_ax0, v_ax1] = matmul1[v_ax0, v_ax1] + fc2_bias[v_ax1]
@Ts.function(private=True)
@@ -176,8 +176,8 @@ into low-level operators.
v_i0 = Ts.axis.spatial(n_2, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(128), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(784), k, dtype="int64")
- Ts.reads(x[v_i0, v_k], permute_dims[v_k, v_i1])
- Ts.writes(matmul[v_i0, v_i1])
+ Ts.reads(x[v_i0, v_k:v_k + T.int64(1)], permute_dims[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul[v_i0, v_i1] = T.float32(0.0)
matmul[v_i0, v_i1] = matmul[v_i0, v_i1] + x[v_i0, v_k] * permute_dims[v_k, v_i1]
@@ -195,8 +195,8 @@ into low-level operators.
v_i0 = Ts.axis.spatial(n_3, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(10), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(128), k, dtype="int64")
- Ts.reads(relu[v_i0, v_k], permute_dims1[v_k, v_i1])
- Ts.writes(matmul[v_i0, v_i1])
+ Ts.reads(relu[v_i0, v_k:v_k + T.int64(1)], permute_dims1[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul[v_i0, v_i1] = T.float32(0.0)
matmul[v_i0, v_i1] = matmul[v_i0, v_i1] + relu[v_i0, v_k] * permute_dims1[v_k, v_i1]
@@ -212,8 +212,8 @@ into low-level operators.
with Ts.sblock("compute"):
v_i0 = Ts.axis.spatial(n_4, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(128), i1, dtype="int64")
- Ts.reads(add[v_i0, v_i1])
- Ts.writes(compute[v_i0, v_i1])
+ Ts.reads(add[v_i0, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(compute[v_i0, v_i1:v_i1 + T.int64(1)])
compute[v_i0, v_i1] = T.max(add[v_i0, v_i1], T.float32(0.0))
@Ts.function(private=True)
@@ -227,8 +227,8 @@ into low-level operators.
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(784), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(128), ax1, dtype="int64")
- Ts.reads(fc1_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(fc1_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = fc1_weight[v_ax1, v_ax0]
@Ts.function(private=True)
@@ -242,21 +242,21 @@ into low-level operators.
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(128), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(fc2_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(fc2_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = fc2_weight[v_ax1, v_ax0]
@R.function
def forward(x: R.Tensor((n_5, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n_5, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims = R.call_tir(Module.transpose, I.Tuple([fc1_weight]), ty_args=[R.Tensor((784, 128), dtype="float32")])
- matmul = R.call_tir(Module.matmul, I.Tuple([x, permute_dims]), ty_args=[R.Tensor((n_5, 128), dtype="float32")])
- add = R.call_tir(Module.add, I.Tuple([matmul, fc1_bias]), ty_args=[R.Tensor((n_5, 128), dtype="float32")])
- relu = R.call_tir(Module.relu, I.Tuple([add]), ty_args=[R.Tensor((n_5, 128), dtype="float32")])
- permute_dims1 = R.call_tir(Module.transpose1, I.Tuple([fc2_weight]), ty_args=[R.Tensor((128, 10), dtype="float32")])
- matmul1 = R.call_tir(Module.matmul1, I.Tuple([relu, permute_dims1]), ty_args=[R.Tensor((n_5, 10), dtype="float32")])
- add1 = R.call_tir(Module.add1, I.Tuple([matmul1, fc2_bias]), ty_args=[R.Tensor((n_5, 10), dtype="float32")])
+ permute_dims = R.call_tir(Module.transpose, (fc1_weight,), ty_args=[R.Tensor((784, 128), dtype="float32")])
+ matmul = R.call_tir(Module.matmul, (x, permute_dims), ty_args=[R.Tensor((n_5, 128), dtype="float32")])
+ add = R.call_tir(Module.add, (matmul, fc1_bias), ty_args=[R.Tensor((n_5, 128), dtype="float32")])
+ relu = R.call_tir(Module.relu, (add,), ty_args=[R.Tensor((n_5, 128), dtype="float32")])
+ permute_dims1 = R.call_tir(Module.transpose1, (fc2_weight,), ty_args=[R.Tensor((128, 10), dtype="float32")])
+ matmul1 = R.call_tir(Module.matmul1, (relu, permute_dims1), ty_args=[R.Tensor((n_5, 10), dtype="float32")])
+ add1 = R.call_tir(Module.add1, (matmul1, fc2_bias), ty_args=[R.Tensor((n_5, 10), dtype="float32")])
gv: R.Tensor((n_5, 10), dtype="float32") = add1
R.output(gv)
return gv
@@ -322,8 +322,8 @@ a set of passes. We can apply them in a sequence.
v_i0 = Ts.axis.spatial(n, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(10), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(128), k, dtype="int64")
- Ts.reads(relu[v_i0, v_k], permute_dims1[v_k, v_i1])
- Ts.writes(matmul_intermediate[v_i0, v_i1])
+ Ts.reads(relu[v_i0, v_k:v_k + T.int64(1)], permute_dims1[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul_intermediate[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul_intermediate[v_i0, v_i1] = T.float32(0.0)
matmul_intermediate[v_i0, v_i1] = matmul_intermediate[v_i0, v_i1] + relu[v_i0, v_k] * permute_dims1[v_k, v_i1]
@@ -332,8 +332,8 @@ a set of passes. We can apply them in a sequence.
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(n, ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(matmul_intermediate[v_ax0, v_ax1], fc2_bias[v_ax1])
- Ts.writes(T_add_intermediate[v_ax0, v_ax1])
+ Ts.reads(matmul_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)], fc2_bias[v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add_intermediate[v_ax0, v_ax1] = matmul_intermediate[v_ax0, v_ax1] + fc2_bias[v_ax1]
@Ts.function(private=True)
@@ -351,8 +351,8 @@ a set of passes. We can apply them in a sequence.
v_i0 = Ts.axis.spatial(n_1, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(128), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(784), k, dtype="int64")
- Ts.reads(x[v_i0, v_k], permute_dims[v_k, v_i1])
- Ts.writes(matmul_intermediate[v_i0, v_i1])
+ Ts.reads(x[v_i0, v_k:v_k + T.int64(1)], permute_dims[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul_intermediate[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul_intermediate[v_i0, v_i1] = T.float32(0.0)
matmul_intermediate[v_i0, v_i1] = matmul_intermediate[v_i0, v_i1] + x[v_i0, v_k] * permute_dims[v_k, v_i1]
@@ -361,16 +361,16 @@ a set of passes. We can apply them in a sequence.
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(n_1, ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(128), ax1, dtype="int64")
- Ts.reads(matmul_intermediate[v_ax0, v_ax1], fc1_bias[v_ax1])
- Ts.writes(T_add_intermediate[v_ax0, v_ax1])
+ Ts.reads(matmul_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)], fc1_bias[v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add_intermediate[v_ax0, v_ax1] = matmul_intermediate[v_ax0, v_ax1] + fc1_bias[v_ax1]
for i0_1 in range(T.int64(0), n_1):
for i1_1 in range(T.int64(0), T.int64(128)):
with Ts.sblock("compute"):
v_i0_1 = Ts.axis.spatial(n_1, i0_1, dtype="int64")
v_i1_1 = Ts.axis.spatial(T.int64(128), i1_1, dtype="int64")
- Ts.reads(T_add_intermediate[v_i0_1, v_i1_1])
- Ts.writes(compute_intermediate[v_i0_1, v_i1_1])
+ Ts.reads(T_add_intermediate[v_i0_1, v_i1_1:v_i1_1 + T.int64(1)])
+ Ts.writes(compute_intermediate[v_i0_1, v_i1_1:v_i1_1 + T.int64(1)])
compute_intermediate[v_i0_1, v_i1_1] = T.max(T_add_intermediate[v_i0_1, v_i1_1], T.float32(0.0))
@Ts.function(private=True)
@@ -384,8 +384,8 @@ a set of passes. We can apply them in a sequence.
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(784), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(128), ax1, dtype="int64")
- Ts.reads(fc1_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(fc1_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = fc1_weight[v_ax1, v_ax0]
@Ts.function(private=True)
@@ -399,18 +399,18 @@ a set of passes. We can apply them in a sequence.
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(128), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(fc2_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(fc2_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = fc2_weight[v_ax1, v_ax0]
@R.function
def forward(x: R.Tensor((n_2, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n_2, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims = R.call_tir(Module.transpose, I.Tuple([fc1_weight]), ty_args=[R.Tensor((784, 128), dtype="float32")])
- lv = R.call_tir(Module.fused_matmul_add_relu, I.Tuple([x, permute_dims, fc1_bias]), ty_args=[R.Tensor((n_2, 128), dtype="float32")])
- permute_dims1 = R.call_tir(Module.transpose1, I.Tuple([fc2_weight]), ty_args=[R.Tensor((128, 10), dtype="float32")])
- gv = R.call_tir(Module.fused_matmul1_add1, I.Tuple([lv, permute_dims1, fc2_bias]), ty_args=[R.Tensor((n_2, 10), dtype="float32")])
+ permute_dims = R.call_tir(Module.transpose, (fc1_weight,), ty_args=[R.Tensor((784, 128), dtype="float32")])
+ lv = R.call_tir(Module.fused_matmul_add_relu, (x, permute_dims, fc1_bias), ty_args=[R.Tensor((n_2, 128), dtype="float32")])
+ permute_dims1 = R.call_tir(Module.transpose1, (fc2_weight,), ty_args=[R.Tensor((128, 10), dtype="float32")])
+ gv = R.call_tir(Module.fused_matmul1_add1, (lv, permute_dims1, fc2_bias), ty_args=[R.Tensor((n_2, 10), dtype="float32")])
R.output(gv)
return gv
@@ -505,11 +505,11 @@ Then we can write a pass to apply the mutator to the whole module.
def forward(x: R.Tensor((n, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 128), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 128), dtype="float32"))
+ permute_dims: R.Tensor((784, 128), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((n, 128), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 128), dtype="float32"))
add: R.Tensor((n, 128), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((n, 128), dtype="float32"))
relu: R.Tensor((n, 128), dtype="float32") = R.nn.gelu(add)
- permute_dims1: R.Tensor((128, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((128, 10), dtype="float32"))
+ permute_dims1: R.Tensor((128, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((n, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 10), dtype="float32"))
add1: R.Tensor((n, 10), dtype="float32") = R.add(matmul1, fc2_bias, ty=R.Tensor((n, 10), dtype="float32"))
gv: R.Tensor((n, 10), dtype="float32") = add1
diff --git a/docs/_sources/deep_dive/relax/tutorials/sg_execution_times.rst b/docs/_sources/deep_dive/relax/tutorials/sg_execution_times.rst
index 2d723d06a38..9a1e76fab0d 100644
--- a/docs/_sources/deep_dive/relax/tutorials/sg_execution_times.rst
+++ b/docs/_sources/deep_dive/relax/tutorials/sg_execution_times.rst
@@ -6,7 +6,7 @@
Computation times
=================
-**00:00.222** total execution time for 2 files **from deep_dive/relax/tutorials**:
+**00:00.177** total execution time for 2 files **from deep_dive/relax/tutorials**:
.. container::
@@ -33,8 +33,8 @@ Computation times
- Time
- Mem (MB)
* - :ref:`sphx_glr_deep_dive_relax_tutorials_relax_creation.py` (``relax_creation.py``)
- - 00:00.119
+ - 00:00.095
- 0.0
* - :ref:`sphx_glr_deep_dive_relax_tutorials_relax_transformation.py` (``relax_transformation.py``)
- - 00:00.103
+ - 00:00.083
- 0.0
diff --git a/docs/_sources/deep_dive/tensor_ir/tutorials/dlight_gpu_scheduling.rst b/docs/_sources/deep_dive/tensor_ir/tutorials/dlight_gpu_scheduling.rst
index 7b8c4e74bef..6a55f71770b 100644
--- a/docs/_sources/deep_dive/tensor_ir/tutorials/dlight_gpu_scheduling.rst
+++ b/docs/_sources/deep_dive/tensor_ir/tutorials/dlight_gpu_scheduling.rst
@@ -192,7 +192,7 @@ Here we use a common subset of rules. The full catalog (including ``LowBatchGEMV
vax1_fused_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
Ts.reads()
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0:v0 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0] = T.float32(0.0)
for ax1_fused_0 in range(T.int64(0), T.int64(48)):
for u in range(1):
@@ -200,16 +200,16 @@ Here we use a common subset of rules. The full catalog (including ``LowBatchGEMV
vax1_fused_1_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0_1 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
vax1_fused_0 = Ts.axis.reduce(T.int64(48), ax1_fused_0, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1], layer_norm[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1], permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1])
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)], layer_norm[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1:vax1_fused_0 * T.int64(16) + vax1_fused_1_1 + T.int64(1)], permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1:v0_1 + T.int64(1)])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] = matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] + layer_norm[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1] * permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1]
for ax1_fused in T.thread_binding(T.int64(16), thread="threadIdx.x"):
for ax0 in T.thread_binding(T.int64(16), thread="threadIdx.y"):
with Ts.sblock("matmul"):
vax1_fused_1_2 = Ts.axis.reduce(T.int64(16), ax0, dtype="int64")
v0_2 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax1_fused, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2])
- Ts.writes(matmul_intermediate_local[T.int64(0), v0_2])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2:v0_2 + T.int64(1)])
+ Ts.writes(matmul_intermediate_local[T.int64(0), v0_2:v0_2 + T.int64(1)])
with Ts.init():
matmul_intermediate_local[T.int64(0), v0_2] = T.float32(0.0)
matmul_intermediate_local[T.int64(0), v0_2] = matmul_intermediate_local[T.int64(0), v0_2] + matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2]
@@ -217,8 +217,8 @@ Here we use a common subset of rules. The full catalog (including ``LowBatchGEMV
for ax0_fused_1_1 in range(T.int64(0), T.int64(1)):
with Ts.sblock("T_add"):
v0_3 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax0_fused_0_1 + ax0_fused_1_1, dtype="int64")
- Ts.reads(matmul_intermediate_local[T.int64(0), v0_3], fc2_bias[v0_3])
- Ts.writes(T_add_intermediate[T.int64(0), v0_3])
+ Ts.reads(matmul_intermediate_local[T.int64(0), v0_3:v0_3 + T.int64(1)], fc2_bias[v0_3:v0_3 + T.int64(1)])
+ Ts.writes(T_add_intermediate[T.int64(0), v0_3:v0_3 + T.int64(1)])
T_add_intermediate[T.int64(0), v0_3] = matmul_intermediate_local[T.int64(0), v0_3] + fc2_bias[v0_3]
@Ts.function(private=True)
@@ -236,7 +236,7 @@ Here we use a common subset of rules. The full catalog (including ``LowBatchGEMV
vax1_fused_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
Ts.reads()
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0:v0 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0] = T.float32(0.0)
for ax1_fused_0 in range(T.int64(0), T.int64(48)):
for u in range(1):
@@ -244,16 +244,16 @@ Here we use a common subset of rules. The full catalog (including ``LowBatchGEMV
vax1_fused_1_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0_1 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
vax1_fused_0 = Ts.axis.reduce(T.int64(48), ax1_fused_0, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1], x[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1], permute_dims[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1])
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)], x[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1:vax1_fused_0 * T.int64(16) + vax1_fused_1_1 + T.int64(1)], permute_dims[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1:v0_1 + T.int64(1)])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] = matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] + x[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1] * permute_dims[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1]
for ax1_fused in T.thread_binding(T.int64(16), thread="threadIdx.x"):
for ax0 in T.thread_binding(T.int64(16), thread="threadIdx.y"):
with Ts.sblock("matmul"):
vax1_fused_1_2 = Ts.axis.reduce(T.int64(16), ax0, dtype="int64")
v0_2 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax1_fused, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2])
- Ts.writes(matmul_intermediate_local[T.int64(0), v0_2])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2:v0_2 + T.int64(1)])
+ Ts.writes(matmul_intermediate_local[T.int64(0), v0_2:v0_2 + T.int64(1)])
with Ts.init():
matmul_intermediate_local[T.int64(0), v0_2] = T.float32(0.0)
matmul_intermediate_local[T.int64(0), v0_2] = matmul_intermediate_local[T.int64(0), v0_2] + matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2]
@@ -261,8 +261,8 @@ Here we use a common subset of rules. The full catalog (including ``LowBatchGEMV
for ax0_fused_1_1 in range(T.int64(0), T.int64(1)):
with Ts.sblock("compute"):
v0_3 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax0_fused_0_1 + ax0_fused_1_1, dtype="int64")
- Ts.reads(matmul_intermediate_local[T.int64(0), v0_3], fc1_bias[v0_3])
- Ts.writes(compute_intermediate[T.int64(0), v0_3])
+ Ts.reads(matmul_intermediate_local[T.int64(0), v0_3:v0_3 + T.int64(1)], fc1_bias[v0_3:v0_3 + T.int64(1)])
+ Ts.writes(compute_intermediate[T.int64(0), v0_3:v0_3 + T.int64(1)])
compute_intermediate[T.int64(0), v0_3] = T.max(matmul_intermediate_local[T.int64(0), v0_3] + fc1_bias[v0_3], T.float32(0.0))
@Ts.function(private=True)
@@ -280,8 +280,8 @@ Here we use a common subset of rules. The full catalog (including ``LowBatchGEMV
with Ts.sblock("relu_sum"):
v0 = Ts.axis.spatial(T.int64(1), ax0, dtype="int64")
v1 = Ts.axis.reduce(T.int64(768), ax1_fused_0 * T.int64(256) + ax1_fused_1, dtype="int64")
- Ts.reads(relu[T.int64(0), v1])
- Ts.writes(relu_sum_shared[T.int64(0)])
+ Ts.reads(relu[T.int64(0), v1:v1 + T.int64(1)])
+ Ts.writes(relu_sum_shared[T.int64(0):T.int64(1)])
with Ts.init():
relu_sum_shared[T.int64(0)] = T.float32(0.0)
relu_sum_shared[T.int64(0)] = relu_sum_shared[T.int64(0)] + relu[T.int64(0), v1]
@@ -291,8 +291,8 @@ Here we use a common subset of rules. The full catalog (including ``LowBatchGEMV
with Ts.sblock("relu_var_sum"):
v0_1 = Ts.axis.spatial(T.int64(1), ax0_1, dtype="int64")
v1_1 = Ts.axis.reduce(T.int64(768), ax1_fused_0_1 * T.int64(256) + ax1_fused_1_1, dtype="int64")
- Ts.reads(relu[T.int64(0), v1_1], relu_sum_shared[T.int64(0)])
- Ts.writes(relu_var_sum_shared[T.int64(0)])
+ Ts.reads(relu[T.int64(0), v1_1:v1_1 + T.int64(1)], relu_sum_shared[T.int64(0):T.int64(1)])
+ Ts.writes(relu_var_sum_shared[T.int64(0):T.int64(1)])
with Ts.init():
relu_var_sum_shared[T.int64(0)] = T.float32(0.0)
relu_var_sum_shared[T.int64(0)] = relu_var_sum_shared[T.int64(0)] + (relu[T.int64(0), v1_1] - relu_sum_shared[T.int64(0)] / T.float32(768.0)) * (relu[T.int64(0), v1_1] - relu_sum_shared[T.int64(0)] / T.float32(768.0))
@@ -301,8 +301,8 @@ Here we use a common subset of rules. The full catalog (including ``LowBatchGEMV
with Ts.sblock("T_layer_norm"):
v0_2 = Ts.axis.spatial(T.int64(1), T.int64(0), dtype="int64")
v1_2 = Ts.axis.spatial(T.int64(768), ax1_0 * T.int64(256) + ax1_1, dtype="int64")
- Ts.reads(relu[T.int64(0), v1_2], relu_sum_shared[T.int64(0)], relu_var_sum_shared[T.int64(0)], norm_weight[v1_2], norm_bias[v1_2])
- Ts.writes(T_layer_norm[T.int64(0), v1_2])
+ Ts.reads(relu[T.int64(0), v1_2:v1_2 + T.int64(1)], relu_sum_shared[T.int64(0):T.int64(1)], relu_var_sum_shared[T.int64(0):T.int64(1)], norm_weight[v1_2:v1_2 + T.int64(1)], norm_bias[v1_2:v1_2 + T.int64(1)])
+ Ts.writes(T_layer_norm[T.int64(0), v1_2:v1_2 + T.int64(1)])
T_layer_norm[T.int64(0), v1_2] = (relu[T.int64(0), v1_2] - relu_sum_shared[T.int64(0)] / T.float32(768.0)) * T.rsqrt(relu_var_sum_shared[T.int64(0)] / T.float32(768.0) + T.float32(1.0000000000000001e-05)) * norm_weight[v1_2] + norm_bias[v1_2]
@Ts.function(private=True)
@@ -316,8 +316,8 @@ Here we use a common subset of rules. The full catalog (including ``LowBatchGEMV
with Ts.sblock("T_transpose"):
v0 = Ts.axis.spatial(T.int64(768), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) // T.int64(768), dtype="int64")
v1 = Ts.axis.spatial(T.int64(768), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) % T.int64(768), dtype="int64")
- Ts.reads(fc1_weight[v1, v0])
- Ts.writes(T_transpose[v0, v1])
+ Ts.reads(fc1_weight[v1, v0:v0 + T.int64(1)])
+ Ts.writes(T_transpose[v0, v1:v1 + T.int64(1)])
T_transpose[v0, v1] = fc1_weight[v1, v0]
@Ts.function(private=True)
@@ -331,19 +331,19 @@ Here we use a common subset of rules. The full catalog (including ``LowBatchGEMV
with Ts.sblock("T_transpose"):
v0 = Ts.axis.spatial(T.int64(768), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) // T.int64(256), dtype="int64")
v1 = Ts.axis.spatial(T.int64(256), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) % T.int64(256), dtype="int64")
- Ts.reads(fc2_weight[v1, v0])
- Ts.writes(T_transpose[v0, v1])
+ Ts.reads(fc2_weight[v1, v0:v0 + T.int64(1)])
+ Ts.writes(T_transpose[v0, v1:v1 + T.int64(1)])
T_transpose[v0, v1] = fc2_weight[v1, v0]
@R.function
def forward(x: R.Tensor((1, 768), dtype="float32"), fc1_weight: R.Tensor((768, 768), dtype="float32"), fc1_bias: R.Tensor((768,), dtype="float32"), norm_weight: R.Tensor((768,), dtype="float32"), norm_bias: R.Tensor((768,), dtype="float32"), fc2_weight: R.Tensor((256, 768), dtype="float32"), fc2_bias: R.Tensor((256,), dtype="float32")) -> R.Tensor((1, 256), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims = R.call_tir(Module.transpose, I.Tuple([fc1_weight]), ty_args=[R.Tensor((768, 768), dtype="float32")])
- lv = R.call_tir(Module.fused_matmul_add_relu, I.Tuple([x, permute_dims, fc1_bias]), ty_args=[R.Tensor((1, 768), dtype="float32")])
- layer_norm = R.call_tir(Module.layer_norm, I.Tuple([lv, norm_weight, norm_bias]), ty_args=[R.Tensor((1, 768), dtype="float32")])
- permute_dims1 = R.call_tir(Module.transpose1, I.Tuple([fc2_weight]), ty_args=[R.Tensor((768, 256), dtype="float32")])
- gv = R.call_tir(Module.fused_matmul1_add1, I.Tuple([layer_norm, permute_dims1, fc2_bias]), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ permute_dims = R.call_tir(Module.transpose, (fc1_weight,), ty_args=[R.Tensor((768, 768), dtype="float32")])
+ lv = R.call_tir(Module.fused_matmul_add_relu, (x, permute_dims, fc1_bias), ty_args=[R.Tensor((1, 768), dtype="float32")])
+ layer_norm = R.call_tir(Module.layer_norm, (lv, norm_weight, norm_bias), ty_args=[R.Tensor((1, 768), dtype="float32")])
+ permute_dims1 = R.call_tir(Module.transpose1, (fc2_weight,), ty_args=[R.Tensor((768, 256), dtype="float32")])
+ gv = R.call_tir(Module.fused_matmul1_add1, (layer_norm, permute_dims1, fc2_bias), ty_args=[R.Tensor((1, 256), dtype="float32")])
R.output(gv)
return gv
@@ -637,7 +637,7 @@ Insert the custom rule into the rule chain. Note that ``from_callable`` returns
vax1_fused_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
Ts.reads()
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0:v0 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0] = T.float32(0.0)
for ax1_fused_0 in range(T.int64(0), T.int64(48)):
for u in range(1):
@@ -645,16 +645,16 @@ Insert the custom rule into the rule chain. Note that ``from_callable`` returns
vax1_fused_1_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0_1 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
vax1_fused_0 = Ts.axis.reduce(T.int64(48), ax1_fused_0, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1], layer_norm[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1], permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1])
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)], layer_norm[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1:vax1_fused_0 * T.int64(16) + vax1_fused_1_1 + T.int64(1)], permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1:v0_1 + T.int64(1)])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] = matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] + layer_norm[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1] * permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1]
for ax1_fused in T.thread_binding(T.int64(16), thread="threadIdx.x"):
for ax0 in T.thread_binding(T.int64(16), thread="threadIdx.y"):
with Ts.sblock("matmul"):
vax1_fused_1_2 = Ts.axis.reduce(T.int64(16), ax0, dtype="int64")
v0_2 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax1_fused, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2])
- Ts.writes(matmul_intermediate_local[T.int64(0), v0_2])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2:v0_2 + T.int64(1)])
+ Ts.writes(matmul_intermediate_local[T.int64(0), v0_2:v0_2 + T.int64(1)])
with Ts.init():
matmul_intermediate_local[T.int64(0), v0_2] = T.float32(0.0)
matmul_intermediate_local[T.int64(0), v0_2] = matmul_intermediate_local[T.int64(0), v0_2] + matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2]
@@ -662,8 +662,8 @@ Insert the custom rule into the rule chain. Note that ``from_callable`` returns
for ax0_fused_1_1 in range(T.int64(0), T.int64(1)):
with Ts.sblock("T_add"):
v0_3 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax0_fused_0_1 + ax0_fused_1_1, dtype="int64")
- Ts.reads(matmul_intermediate_local[T.int64(0), v0_3], fc2_bias[v0_3])
- Ts.writes(T_add_intermediate[T.int64(0), v0_3])
+ Ts.reads(matmul_intermediate_local[T.int64(0), v0_3:v0_3 + T.int64(1)], fc2_bias[v0_3:v0_3 + T.int64(1)])
+ Ts.writes(T_add_intermediate[T.int64(0), v0_3:v0_3 + T.int64(1)])
T_add_intermediate[T.int64(0), v0_3] = matmul_intermediate_local[T.int64(0), v0_3] + fc2_bias[v0_3]
@Ts.function(private=True)
@@ -681,7 +681,7 @@ Insert the custom rule into the rule chain. Note that ``from_callable`` returns
vax1_fused_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
Ts.reads()
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0:v0 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0] = T.float32(0.0)
for ax1_fused_0 in range(T.int64(0), T.int64(48)):
for u in range(1):
@@ -689,16 +689,16 @@ Insert the custom rule into the rule chain. Note that ``from_callable`` returns
vax1_fused_1_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0_1 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
vax1_fused_0 = Ts.axis.reduce(T.int64(48), ax1_fused_0, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1], x[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1], permute_dims[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1])
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)], x[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1:vax1_fused_0 * T.int64(16) + vax1_fused_1_1 + T.int64(1)], permute_dims[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1:v0_1 + T.int64(1)])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] = matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] + x[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1] * permute_dims[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1]
for ax1_fused in T.thread_binding(T.int64(16), thread="threadIdx.x"):
for ax0 in T.thread_binding(T.int64(16), thread="threadIdx.y"):
with Ts.sblock("matmul"):
vax1_fused_1_2 = Ts.axis.reduce(T.int64(16), ax0, dtype="int64")
v0_2 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax1_fused, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2])
- Ts.writes(matmul_intermediate_local[T.int64(0), v0_2])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2:v0_2 + T.int64(1)])
+ Ts.writes(matmul_intermediate_local[T.int64(0), v0_2:v0_2 + T.int64(1)])
with Ts.init():
matmul_intermediate_local[T.int64(0), v0_2] = T.float32(0.0)
matmul_intermediate_local[T.int64(0), v0_2] = matmul_intermediate_local[T.int64(0), v0_2] + matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2]
@@ -706,8 +706,8 @@ Insert the custom rule into the rule chain. Note that ``from_callable`` returns
for ax0_fused_1_1 in range(T.int64(0), T.int64(1)):
with Ts.sblock("compute"):
v0_3 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax0_fused_0_1 + ax0_fused_1_1, dtype="int64")
- Ts.reads(matmul_intermediate_local[T.int64(0), v0_3], fc1_bias[v0_3])
- Ts.writes(compute_intermediate[T.int64(0), v0_3])
+ Ts.reads(matmul_intermediate_local[T.int64(0), v0_3:v0_3 + T.int64(1)], fc1_bias[v0_3:v0_3 + T.int64(1)])
+ Ts.writes(compute_intermediate[T.int64(0), v0_3:v0_3 + T.int64(1)])
compute_intermediate[T.int64(0), v0_3] = T.max(matmul_intermediate_local[T.int64(0), v0_3] + fc1_bias[v0_3], T.float32(0.0))
@Ts.function(private=True)
@@ -725,8 +725,8 @@ Insert the custom rule into the rule chain. Note that ``from_callable`` returns
with Ts.sblock("relu_sum"):
v0 = Ts.axis.spatial(T.int64(1), ax0, dtype="int64")
v1 = Ts.axis.reduce(T.int64(768), ax1_fused_0 * T.int64(256) + ax1_fused_1, dtype="int64")
- Ts.reads(relu[T.int64(0), v1])
- Ts.writes(relu_sum_shared[T.int64(0)])
+ Ts.reads(relu[T.int64(0), v1:v1 + T.int64(1)])
+ Ts.writes(relu_sum_shared[T.int64(0):T.int64(1)])
with Ts.init():
relu_sum_shared[T.int64(0)] = T.float32(0.0)
relu_sum_shared[T.int64(0)] = relu_sum_shared[T.int64(0)] + relu[T.int64(0), v1]
@@ -736,8 +736,8 @@ Insert the custom rule into the rule chain. Note that ``from_callable`` returns
with Ts.sblock("relu_var_sum"):
v0_1 = Ts.axis.spatial(T.int64(1), ax0_1, dtype="int64")
v1_1 = Ts.axis.reduce(T.int64(768), ax1_fused_0_1 * T.int64(256) + ax1_fused_1_1, dtype="int64")
- Ts.reads(relu[T.int64(0), v1_1], relu_sum_shared[T.int64(0)])
- Ts.writes(relu_var_sum_shared[T.int64(0)])
+ Ts.reads(relu[T.int64(0), v1_1:v1_1 + T.int64(1)], relu_sum_shared[T.int64(0):T.int64(1)])
+ Ts.writes(relu_var_sum_shared[T.int64(0):T.int64(1)])
with Ts.init():
relu_var_sum_shared[T.int64(0)] = T.float32(0.0)
relu_var_sum_shared[T.int64(0)] = relu_var_sum_shared[T.int64(0)] + (relu[T.int64(0), v1_1] - relu_sum_shared[T.int64(0)] / T.float32(768.0)) * (relu[T.int64(0), v1_1] - relu_sum_shared[T.int64(0)] / T.float32(768.0))
@@ -746,8 +746,8 @@ Insert the custom rule into the rule chain. Note that ``from_callable`` returns
with Ts.sblock("T_layer_norm"):
v0_2 = Ts.axis.spatial(T.int64(1), T.int64(0), dtype="int64")
v1_2 = Ts.axis.spatial(T.int64(768), ax1_0 * T.int64(256) + ax1_1, dtype="int64")
- Ts.reads(relu[T.int64(0), v1_2], relu_sum_shared[T.int64(0)], relu_var_sum_shared[T.int64(0)], norm_weight[v1_2], norm_bias[v1_2])
- Ts.writes(T_layer_norm[T.int64(0), v1_2])
+ Ts.reads(relu[T.int64(0), v1_2:v1_2 + T.int64(1)], relu_sum_shared[T.int64(0):T.int64(1)], relu_var_sum_shared[T.int64(0):T.int64(1)], norm_weight[v1_2:v1_2 + T.int64(1)], norm_bias[v1_2:v1_2 + T.int64(1)])
+ Ts.writes(T_layer_norm[T.int64(0), v1_2:v1_2 + T.int64(1)])
T_layer_norm[T.int64(0), v1_2] = (relu[T.int64(0), v1_2] - relu_sum_shared[T.int64(0)] / T.float32(768.0)) * T.rsqrt(relu_var_sum_shared[T.int64(0)] / T.float32(768.0) + T.float32(1.0000000000000001e-05)) * norm_weight[v1_2] + norm_bias[v1_2]
@Ts.function(private=True)
@@ -761,8 +761,8 @@ Insert the custom rule into the rule chain. Note that ``from_callable`` returns
with Ts.sblock("T_transpose"):
v0 = Ts.axis.spatial(T.int64(768), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) // T.int64(768), dtype="int64")
v1 = Ts.axis.spatial(T.int64(768), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) % T.int64(768), dtype="int64")
- Ts.reads(fc1_weight[v1, v0])
- Ts.writes(T_transpose[v0, v1])
+ Ts.reads(fc1_weight[v1, v0:v0 + T.int64(1)])
+ Ts.writes(T_transpose[v0, v1:v1 + T.int64(1)])
T_transpose[v0, v1] = fc1_weight[v1, v0]
@Ts.function(private=True)
@@ -776,19 +776,19 @@ Insert the custom rule into the rule chain. Note that ``from_callable`` returns
with Ts.sblock("T_transpose"):
v0 = Ts.axis.spatial(T.int64(768), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) // T.int64(256), dtype="int64")
v1 = Ts.axis.spatial(T.int64(256), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) % T.int64(256), dtype="int64")
- Ts.reads(fc2_weight[v1, v0])
- Ts.writes(T_transpose[v0, v1])
+ Ts.reads(fc2_weight[v1, v0:v0 + T.int64(1)])
+ Ts.writes(T_transpose[v0, v1:v1 + T.int64(1)])
T_transpose[v0, v1] = fc2_weight[v1, v0]
@R.function
def forward(x: R.Tensor((1, 768), dtype="float32"), fc1_weight: R.Tensor((768, 768), dtype="float32"), fc1_bias: R.Tensor((768,), dtype="float32"), norm_weight: R.Tensor((768,), dtype="float32"), norm_bias: R.Tensor((768,), dtype="float32"), fc2_weight: R.Tensor((256, 768), dtype="float32"), fc2_bias: R.Tensor((256,), dtype="float32")) -> R.Tensor((1, 256), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims = R.call_tir(Module.transpose, I.Tuple([fc1_weight]), ty_args=[R.Tensor((768, 768), dtype="float32")])
- lv = R.call_tir(Module.fused_matmul_add_relu, I.Tuple([x, permute_dims, fc1_bias]), ty_args=[R.Tensor((1, 768), dtype="float32")])
- layer_norm = R.call_tir(Module.layer_norm, I.Tuple([lv, norm_weight, norm_bias]), ty_args=[R.Tensor((1, 768), dtype="float32")])
- permute_dims1 = R.call_tir(Module.transpose1, I.Tuple([fc2_weight]), ty_args=[R.Tensor((768, 256), dtype="float32")])
- gv = R.call_tir(Module.fused_matmul1_add1, I.Tuple([layer_norm, permute_dims1, fc2_bias]), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ permute_dims = R.call_tir(Module.transpose, (fc1_weight,), ty_args=[R.Tensor((768, 768), dtype="float32")])
+ lv = R.call_tir(Module.fused_matmul_add_relu, (x, permute_dims, fc1_bias), ty_args=[R.Tensor((1, 768), dtype="float32")])
+ layer_norm = R.call_tir(Module.layer_norm, (lv, norm_weight, norm_bias), ty_args=[R.Tensor((1, 768), dtype="float32")])
+ permute_dims1 = R.call_tir(Module.transpose1, (fc2_weight,), ty_args=[R.Tensor((768, 256), dtype="float32")])
+ gv = R.call_tir(Module.fused_matmul1_add1, (layer_norm, permute_dims1, fc2_bias), ty_args=[R.Tensor((1, 256), dtype="float32")])
R.output(gv)
return gv
diff --git a/docs/_sources/deep_dive/tensor_ir/tutorials/sg_execution_times.rst b/docs/_sources/deep_dive/tensor_ir/tutorials/sg_execution_times.rst
index 9f17b10db50..a3ae598023d 100644
--- a/docs/_sources/deep_dive/tensor_ir/tutorials/sg_execution_times.rst
+++ b/docs/_sources/deep_dive/tensor_ir/tutorials/sg_execution_times.rst
@@ -6,7 +6,7 @@
Computation times
=================
-**00:00.713** total execution time for 4 files **from deep_dive/tensor_ir/tutorials**:
+**00:00.602** total execution time for 4 files **from deep_dive/tensor_ir/tutorials**:
.. container::
@@ -33,14 +33,14 @@ Computation times
- Time
- Mem (MB)
* - :ref:`sphx_glr_deep_dive_tensor_ir_tutorials_tir_transformation.py` (``tir_transformation.py``)
- - 00:00.317
+ - 00:00.267
- 0.0
* - :ref:`sphx_glr_deep_dive_tensor_ir_tutorials_dlight_gpu_scheduling.py` (``dlight_gpu_scheduling.py``)
- - 00:00.220
+ - 00:00.184
- 0.0
* - :ref:`sphx_glr_deep_dive_tensor_ir_tutorials_tir_creation.py` (``tir_creation.py``)
- - 00:00.161
+ - 00:00.138
- 0.0
* - :ref:`sphx_glr_deep_dive_tensor_ir_tutorials_meta_schedule.py` (``meta_schedule.py``)
- - 00:00.014
+ - 00:00.012
- 0.0
diff --git a/docs/_sources/deep_dive/tensor_ir/tutorials/tir_creation.rst b/docs/_sources/deep_dive/tensor_ir/tutorials/tir_creation.rst
index 28573d3989f..6cca5fbe3f8 100644
--- a/docs/_sources/deep_dive/tensor_ir/tutorials/tir_creation.rst
+++ b/docs/_sources/deep_dive/tensor_ir/tutorials/tir_creation.rst
@@ -433,8 +433,8 @@ and one output parameter **C**.
v_i = Ts.axis.spatial(128, i)
v_j = Ts.axis.spatial(128, j)
v_k = Ts.axis.reduce(128, k)
- Ts.reads(A[v_i, v_k], B[v_k, v_j])
- Ts.writes(Y[v_i, v_j])
+ Ts.reads(A[v_i, v_k:v_k + 1], B[v_k, v_j:v_j + 1])
+ Ts.writes(Y[v_i, v_j:v_j + 1])
with Ts.init():
Y[v_i, v_j] = T.float32(0.0)
Y[v_i, v_j] = Y[v_i, v_j] + A[v_i, v_k] * B[v_k, v_j]
@@ -443,8 +443,8 @@ and one output parameter **C**.
with Ts.sblock("C"):
v_i_1 = Ts.axis.spatial(128, i_1)
v_j_1 = Ts.axis.spatial(128, j_1)
- Ts.reads(Y[v_i_1, v_j_1])
- Ts.writes(C[v_i_1, v_j_1])
+ Ts.reads(Y[v_i_1, v_j_1:v_j_1 + 1])
+ Ts.writes(C[v_i_1, v_j_1:v_j_1 + 1])
C[v_i_1, v_j_1] = T.max(Y[v_i_1, v_j_1], T.float32(0.0))
@@ -507,8 +507,8 @@ is that we need to specify the shape of the input tensors as symbolic variables.
v_i = Ts.axis.spatial(m, i)
v_j = Ts.axis.spatial(n, j)
v_k = Ts.axis.reduce(k, k_1)
- Ts.reads(A[v_i, v_k], B[v_k, v_j])
- Ts.writes(Y[v_i, v_j])
+ Ts.reads(A[v_i, v_k:v_k + 1], B[v_k, v_j:v_j + 1])
+ Ts.writes(Y[v_i, v_j:v_j + 1])
with Ts.init():
Y[v_i, v_j] = T.float32(0.0)
Y[v_i, v_j] = Y[v_i, v_j] + A[v_i, v_k] * B[v_k, v_j]
@@ -517,8 +517,8 @@ is that we need to specify the shape of the input tensors as symbolic variables.
with Ts.sblock("C"):
v_i_1 = Ts.axis.spatial(m, i_1)
v_j_1 = Ts.axis.spatial(n, j_1)
- Ts.reads(Y[v_i_1, v_j_1])
- Ts.writes(C[v_i_1, v_j_1])
+ Ts.reads(Y[v_i_1, v_j_1:v_j_1 + 1])
+ Ts.writes(C[v_i_1, v_j_1:v_j_1 + 1])
C[v_i_1, v_j_1] = T.max(Y[v_i_1, v_j_1], T.float32(0.0))
diff --git a/docs/_sources/deep_dive/tensor_ir/tutorials/tir_transformation.rst b/docs/_sources/deep_dive/tensor_ir/tutorials/tir_transformation.rst
index 95f05bdaaa4..a226ba390c5 100644
--- a/docs/_sources/deep_dive/tensor_ir/tutorials/tir_transformation.rst
+++ b/docs/_sources/deep_dive/tensor_ir/tutorials/tir_transformation.rst
@@ -121,7 +121,7 @@ original implementation.
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 2.7543 2.7543 2.7543 2.7543 0.0000
+ 2.4568 2.4568 2.4568 2.4568 0.0000
@@ -233,8 +233,8 @@ The outcome of the transformation can be examined, as it is retained within ``sc
v_1 = Ts.axis.spatial(128, i)
v_2 = Ts.axis.spatial(128, j_0 * 8 + j_1)
v_3 = Ts.axis.reduce(128, k)
- Ts.reads(A[v_1, v_3], B[v_3, v_2])
- Ts.writes(v[v_1, v_2])
+ Ts.reads(A[v_1, v_3:v_3 + 1], B[v_3, v_2:v_2 + 1])
+ Ts.writes(v[v_1, v_2:v_2 + 1])
with Ts.init():
v[v_1, v_2] = T.float32(0.0)
v[v_1, v_2] = v[v_1, v_2] + A[v_1, v_3] * B[v_3, v_2]
@@ -243,8 +243,8 @@ The outcome of the transformation can be examined, as it is retained within ``sc
with Ts.sblock("C"):
v_4 = Ts.axis.spatial(128, i_1)
v_5 = Ts.axis.spatial(128, j)
- Ts.reads(v[v_4, v_5])
- Ts.writes(C[v_4, v_5])
+ Ts.reads(v[v_4, v_5:v_5 + 1])
+ Ts.writes(C[v_4, v_5:v_5 + 1])
C[v_4, v_5] = T.max(v[v_4, v_5], T.float32(0.0))
@@ -297,8 +297,8 @@ action involves reordering these two loops.
v_1 = Ts.axis.spatial(128, i)
v_2 = Ts.axis.spatial(128, j_0 * 8 + j_1)
v_3 = Ts.axis.reduce(128, k)
- Ts.reads(A[v_1, v_3], B[v_3, v_2])
- Ts.writes(v[v_1, v_2])
+ Ts.reads(A[v_1, v_3:v_3 + 1], B[v_3, v_2:v_2 + 1])
+ Ts.writes(v[v_1, v_2:v_2 + 1])
with Ts.init():
v[v_1, v_2] = T.float32(0.0)
v[v_1, v_2] = v[v_1, v_2] + A[v_1, v_3] * B[v_3, v_2]
@@ -307,13 +307,13 @@ action involves reordering these two loops.
with Ts.sblock("C"):
v_4 = Ts.axis.spatial(128, i_1)
v_5 = Ts.axis.spatial(128, j)
- Ts.reads(v[v_4, v_5])
- Ts.writes(C[v_4, v_5])
+ Ts.reads(v[v_4, v_5:v_5 + 1])
+ Ts.writes(C[v_4, v_5:v_5 + 1])
C[v_4, v_5] = T.max(v[v_4, v_5], T.float32(0.0))
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 0.8625 0.8625 0.8625 0.8625 0.0000
+ 0.8632 0.8632 0.8632 0.8632 0.0000
@@ -366,8 +366,8 @@ variant. First, we employ a primitive known as **reverse_compute_at** to relocat
v_1 = Ts.axis.spatial(128, i)
v_2 = Ts.axis.spatial(128, j_0 * 8 + j_1)
v_3 = Ts.axis.reduce(128, k)
- Ts.reads(A[v_1, v_3], B[v_3, v_2])
- Ts.writes(v[v_1, v_2])
+ Ts.reads(A[v_1, v_3:v_3 + 1], B[v_3, v_2:v_2 + 1])
+ Ts.writes(v[v_1, v_2:v_2 + 1])
with Ts.init():
v[v_1, v_2] = T.float32(0.0)
v[v_1, v_2] = v[v_1, v_2] + A[v_1, v_3] * B[v_3, v_2]
@@ -375,8 +375,8 @@ variant. First, we employ a primitive known as **reverse_compute_at** to relocat
with Ts.sblock("C"):
v_4 = Ts.axis.spatial(128, i)
v_5 = Ts.axis.spatial(128, j_0 * 8 + ax0)
- Ts.reads(v[v_4, v_5])
- Ts.writes(C[v_4, v_5])
+ Ts.reads(v[v_4, v_5:v_5 + 1])
+ Ts.writes(C[v_4, v_5:v_5 + 1])
C[v_4, v_5] = T.max(v[v_4, v_5], T.float32(0.0))
@@ -434,7 +434,7 @@ from the reduction update via the **decompose_reduction** primitive.
v_1 = Ts.axis.spatial(128, i)
v_2 = Ts.axis.spatial(128, j_0 * 8 + j_1_init)
Ts.reads()
- Ts.writes(v[v_1, v_2])
+ Ts.writes(v[v_1, v_2:v_2 + 1])
v[v_1, v_2] = T.float32(0.0)
for k in range(128):
for j_1 in range(8):
@@ -442,20 +442,20 @@ from the reduction update via the **decompose_reduction** primitive.
v_3 = Ts.axis.spatial(128, i)
v_4 = Ts.axis.spatial(128, j_0 * 8 + j_1)
v_5 = Ts.axis.reduce(128, k)
- Ts.reads(v[v_3, v_4], A[v_3, v_5], B[v_5, v_4])
- Ts.writes(v[v_3, v_4])
+ Ts.reads(v[v_3, v_4:v_4 + 1], A[v_3, v_5:v_5 + 1], B[v_5, v_4:v_4 + 1])
+ Ts.writes(v[v_3, v_4:v_4 + 1])
v[v_3, v_4] = v[v_3, v_4] + A[v_3, v_5] * B[v_5, v_4]
for ax0 in range(8):
with Ts.sblock("C"):
v_6 = Ts.axis.spatial(128, i)
v_7 = Ts.axis.spatial(128, j_0 * 8 + ax0)
- Ts.reads(v[v_6, v_7])
- Ts.writes(C[v_6, v_7])
+ Ts.reads(v[v_6, v_7:v_7 + 1])
+ Ts.writes(C[v_6, v_7:v_7 + 1])
C[v_6, v_7] = T.max(v[v_6, v_7], T.float32(0.0))
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 0.3379 0.3379 0.3379 0.3379 0.0000
+ 0.3482 0.3482 0.3482 0.3482 0.0000
@@ -540,7 +540,7 @@ Alternatively, we can output the IRModule in conjunction with the historical tra
v_1 = Ts.axis.spatial(128, i)
v_2 = Ts.axis.spatial(128, j_0 * 8 + j_1_init)
Ts.reads()
- Ts.writes(v[v_1, v_2])
+ Ts.writes(v[v_1, v_2:v_2 + 1])
v[v_1, v_2] = T.float32(0.0)
for k in range(128):
for j_1 in range(8):
@@ -548,15 +548,15 @@ Alternatively, we can output the IRModule in conjunction with the historical tra
v_3 = Ts.axis.spatial(128, i)
v_4 = Ts.axis.spatial(128, j_0 * 8 + j_1)
v_5 = Ts.axis.reduce(128, k)
- Ts.reads(v[v_3, v_4], A[v_3, v_5], B[v_5, v_4])
- Ts.writes(v[v_3, v_4])
+ Ts.reads(v[v_3, v_4:v_4 + 1], A[v_3, v_5:v_5 + 1], B[v_5, v_4:v_4 + 1])
+ Ts.writes(v[v_3, v_4:v_4 + 1])
v[v_3, v_4] = v[v_3, v_4] + A[v_3, v_5] * B[v_5, v_4]
for ax0 in range(8):
with Ts.sblock("C"):
v_6 = Ts.axis.spatial(128, i)
v_7 = Ts.axis.spatial(128, j_0 * 8 + ax0)
- Ts.reads(v[v_6, v_7])
- Ts.writes(C[v_6, v_7])
+ Ts.reads(v[v_6, v_7:v_7 + 1])
+ Ts.writes(C[v_6, v_7:v_7 + 1])
C[v_6, v_7] = T.max(v[v_6, v_7], T.float32(0.0))
# from tvm import s_tir
diff --git a/docs/_sources/get_started/tutorials/ir_module.rst b/docs/_sources/get_started/tutorials/ir_module.rst
index b67bb7afe77..73ecf684b17 100644
--- a/docs/_sources/get_started/tutorials/ir_module.rst
+++ b/docs/_sources/get_started/tutorials/ir_module.rst
@@ -201,11 +201,11 @@ write the IRModule directly.
def forward(x: R.Tensor((1, 784), dtype="float32"), fc1_weight: R.Tensor((256, 784), dtype="float32"), fc1_bias: R.Tensor((256,), dtype="float32"), fc2_weight: R.Tensor((10, 256), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 256), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 256), dtype="float32"))
+ permute_dims: R.Tensor((784, 256), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((1, 256), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 256), dtype="float32"))
add: R.Tensor((1, 256), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((1, 256), dtype="float32"))
relu: R.Tensor((1, 256), dtype="float32") = R.nn.relu(add)
- permute_dims1: R.Tensor((256, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((256, 10), dtype="float32"))
+ permute_dims1: R.Tensor((256, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((1, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 10), dtype="float32"))
add1: R.Tensor((1, 10), dtype="float32") = R.add(matmul1, fc2_bias, ty=R.Tensor((1, 10), dtype="float32"))
gv: R.Tensor((1, 10), dtype="float32") = add1
@@ -279,11 +279,11 @@ parse the TVMScript to obtain an IRModule.
def main(x: R.Tensor((1, 784), dtype="float32"), fc1_weight: R.Tensor((256, 784), dtype="float32"), fc1_bias: R.Tensor((256,), dtype="float32"), fc2_weight: R.Tensor((10, 256), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 256), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 256), dtype="float32"))
+ permute_dims: R.Tensor((784, 256), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((1, 256), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 256), dtype="float32"))
add: R.Tensor((1, 256), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((1, 256), dtype="float32"))
relu: R.Tensor((1, 256), dtype="float32") = R.nn.relu(add)
- permute_dims1: R.Tensor((256, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((256, 10), dtype="float32"))
+ permute_dims1: R.Tensor((256, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((1, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 10), dtype="float32"))
add1: R.Tensor((1, 10), dtype="float32") = R.add(matmul1, fc2_bias, ty=R.Tensor((1, 10), dtype="float32"))
gv: R.Tensor((1, 10), dtype="float32") = add1
@@ -423,8 +423,8 @@ within the same module. Meanwhile, the Relax operators will be converted into ``
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(T.int64(1), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(256), ax1, dtype="int64")
- Ts.reads(p_fc1_bias[v_ax1], lv1[v_ax0, v_ax1])
- Ts.writes(T_add[v_ax0, v_ax1])
+ Ts.reads(p_fc1_bias[v_ax1:v_ax1 + T.int64(1)], lv1[v_ax0, v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add[v_ax0, v_ax1] = p_fc1_bias[v_ax1] + lv1[v_ax0, v_ax1]
@Ts.function(private=True)
@@ -438,8 +438,8 @@ within the same module. Meanwhile, the Relax operators will be converted into ``
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(T.int64(1), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(p_fc2_bias[v_ax1], lv5[v_ax0, v_ax1])
- Ts.writes(T_add[v_ax0, v_ax1])
+ Ts.reads(p_fc2_bias[v_ax1:v_ax1 + T.int64(1)], lv5[v_ax0, v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add[v_ax0, v_ax1] = p_fc2_bias[v_ax1] + lv5[v_ax0, v_ax1]
@Ts.function(private=True)
@@ -455,8 +455,8 @@ within the same module. Meanwhile, the Relax operators will be converted into ``
v_i0 = Ts.axis.spatial(T.int64(1), i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(256), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(784), k, dtype="int64")
- Ts.reads(x[v_i0, v_k], lv[v_k, v_i1])
- Ts.writes(matmul[v_i0, v_i1])
+ Ts.reads(x[v_i0, v_k:v_k + T.int64(1)], lv[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul[v_i0, v_i1] = T.float32(0.0)
matmul[v_i0, v_i1] = matmul[v_i0, v_i1] + x[v_i0, v_k] * lv[v_k, v_i1]
@@ -474,8 +474,8 @@ within the same module. Meanwhile, the Relax operators will be converted into ``
v_i0 = Ts.axis.spatial(T.int64(1), i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(10), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(256), k, dtype="int64")
- Ts.reads(lv3[v_i0, v_k], lv4[v_k, v_i1])
- Ts.writes(matmul[v_i0, v_i1])
+ Ts.reads(lv3[v_i0, v_k:v_k + T.int64(1)], lv4[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul[v_i0, v_i1] = T.float32(0.0)
matmul[v_i0, v_i1] = matmul[v_i0, v_i1] + lv3[v_i0, v_k] * lv4[v_k, v_i1]
@@ -491,8 +491,8 @@ within the same module. Meanwhile, the Relax operators will be converted into ``
with Ts.sblock("compute"):
v_i0 = Ts.axis.spatial(T.int64(1), i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(256), i1, dtype="int64")
- Ts.reads(lv2[v_i0, v_i1])
- Ts.writes(compute[v_i0, v_i1])
+ Ts.reads(lv2[v_i0, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(compute[v_i0, v_i1:v_i1 + T.int64(1)])
compute[v_i0, v_i1] = T.max(lv2[v_i0, v_i1], T.float32(0.0))
@Ts.function(private=True)
@@ -506,8 +506,8 @@ within the same module. Meanwhile, the Relax operators will be converted into ``
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(784), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(256), ax1, dtype="int64")
- Ts.reads(p_fc1_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(p_fc1_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = p_fc1_weight[v_ax1, v_ax0]
@Ts.function(private=True)
@@ -521,21 +521,21 @@ within the same module. Meanwhile, the Relax operators will be converted into ``
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(256), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(p_fc2_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(p_fc2_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = p_fc2_weight[v_ax1, v_ax0]
@R.function
def main(x: R.Tensor((1, 784), dtype="float32"), p_fc1_weight: R.Tensor((256, 784), dtype="float32"), p_fc1_bias: R.Tensor((256,), dtype="float32"), p_fc2_weight: R.Tensor((10, 256), dtype="float32"), p_fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- lv = R.call_tir(Module.transpose, I.Tuple([p_fc1_weight]), ty_args=[R.Tensor((784, 256), dtype="float32")])
- lv1 = R.call_tir(Module.matmul, I.Tuple([x, lv]), ty_args=[R.Tensor((1, 256), dtype="float32")])
- lv2 = R.call_tir(Module.add, I.Tuple([p_fc1_bias, lv1]), ty_args=[R.Tensor((1, 256), dtype="float32")])
- lv3 = R.call_tir(Module.relu, I.Tuple([lv2]), ty_args=[R.Tensor((1, 256), dtype="float32")])
- lv4 = R.call_tir(Module.transpose1, I.Tuple([p_fc2_weight]), ty_args=[R.Tensor((256, 10), dtype="float32")])
- lv5 = R.call_tir(Module.matmul1, I.Tuple([lv3, lv4]), ty_args=[R.Tensor((1, 10), dtype="float32")])
- lv6 = R.call_tir(Module.add1, I.Tuple([p_fc2_bias, lv5]), ty_args=[R.Tensor((1, 10), dtype="float32")])
+ lv = R.call_tir(Module.transpose, (p_fc1_weight,), ty_args=[R.Tensor((784, 256), dtype="float32")])
+ lv1 = R.call_tir(Module.matmul, (x, lv), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ lv2 = R.call_tir(Module.add, (p_fc1_bias, lv1), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ lv3 = R.call_tir(Module.relu, (lv2,), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ lv4 = R.call_tir(Module.transpose1, (p_fc2_weight,), ty_args=[R.Tensor((256, 10), dtype="float32")])
+ lv5 = R.call_tir(Module.matmul1, (lv3, lv4), ty_args=[R.Tensor((1, 10), dtype="float32")])
+ lv6 = R.call_tir(Module.add1, (p_fc2_bias, lv5), ty_args=[R.Tensor((1, 10), dtype="float32")])
gv: R.Tensor((1, 10), dtype="float32") = lv6
R.output(gv)
return gv
@@ -633,8 +633,8 @@ The default **zero** pipeline contains very fundamental transformations, includi
v_i0 = Ts.axis.spatial(T.int64(1), i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(10), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(256), k, dtype="int64")
- Ts.reads(lv3[v_i0, v_k], lv4[v_k, v_i1])
- Ts.writes(matmul_intermediate[v_i0, v_i1])
+ Ts.reads(lv3[v_i0, v_k:v_k + T.int64(1)], lv4[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul_intermediate[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul_intermediate[v_i0, v_i1] = T.float32(0.0)
matmul_intermediate[v_i0, v_i1] = matmul_intermediate[v_i0, v_i1] + lv3[v_i0, v_k] * lv4[v_k, v_i1]
@@ -643,8 +643,8 @@ The default **zero** pipeline contains very fundamental transformations, includi
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(T.int64(1), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(p_fc2_bias[v_ax1], matmul_intermediate[v_ax0, v_ax1])
- Ts.writes(T_add_intermediate[v_ax0, v_ax1])
+ Ts.reads(p_fc2_bias[v_ax1:v_ax1 + T.int64(1)], matmul_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add_intermediate[v_ax0, v_ax1] = p_fc2_bias[v_ax1] + matmul_intermediate[v_ax0, v_ax1]
@Ts.function(private=True)
@@ -662,8 +662,8 @@ The default **zero** pipeline contains very fundamental transformations, includi
v_i0 = Ts.axis.spatial(T.int64(1), i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(256), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(784), k, dtype="int64")
- Ts.reads(x[v_i0, v_k], lv[v_k, v_i1])
- Ts.writes(matmul_intermediate[v_i0, v_i1])
+ Ts.reads(x[v_i0, v_k:v_k + T.int64(1)], lv[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul_intermediate[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul_intermediate[v_i0, v_i1] = T.float32(0.0)
matmul_intermediate[v_i0, v_i1] = matmul_intermediate[v_i0, v_i1] + x[v_i0, v_k] * lv[v_k, v_i1]
@@ -672,16 +672,16 @@ The default **zero** pipeline contains very fundamental transformations, includi
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(T.int64(1), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(256), ax1, dtype="int64")
- Ts.reads(p_fc1_bias[v_ax1], matmul_intermediate[v_ax0, v_ax1])
- Ts.writes(T_add_intermediate[v_ax0, v_ax1])
+ Ts.reads(p_fc1_bias[v_ax1:v_ax1 + T.int64(1)], matmul_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add_intermediate[v_ax0, v_ax1] = p_fc1_bias[v_ax1] + matmul_intermediate[v_ax0, v_ax1]
for i0_1 in range(T.int64(0), T.int64(1)):
for i1_1 in range(T.int64(0), T.int64(256)):
with Ts.sblock("compute"):
v_i0_1 = Ts.axis.spatial(T.int64(1), i0_1, dtype="int64")
v_i1_1 = Ts.axis.spatial(T.int64(256), i1_1, dtype="int64")
- Ts.reads(T_add_intermediate[v_i0_1, v_i1_1])
- Ts.writes(compute_intermediate[v_i0_1, v_i1_1])
+ Ts.reads(T_add_intermediate[v_i0_1, v_i1_1:v_i1_1 + T.int64(1)])
+ Ts.writes(compute_intermediate[v_i0_1, v_i1_1:v_i1_1 + T.int64(1)])
compute_intermediate[v_i0_1, v_i1_1] = T.max(T_add_intermediate[v_i0_1, v_i1_1], T.float32(0.0))
@Ts.function(private=True)
@@ -695,8 +695,8 @@ The default **zero** pipeline contains very fundamental transformations, includi
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(784), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(256), ax1, dtype="int64")
- Ts.reads(p_fc1_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(p_fc1_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = p_fc1_weight[v_ax1, v_ax0]
@Ts.function(private=True)
@@ -710,18 +710,18 @@ The default **zero** pipeline contains very fundamental transformations, includi
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(256), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(p_fc2_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(p_fc2_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = p_fc2_weight[v_ax1, v_ax0]
@R.function
def main(x: R.Tensor((1, 784), dtype="float32"), p_fc1_weight: R.Tensor((256, 784), dtype="float32"), p_fc1_bias: R.Tensor((256,), dtype="float32"), p_fc2_weight: R.Tensor((10, 256), dtype="float32"), p_fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- lv = R.call_tir(Module.transpose, I.Tuple([p_fc1_weight]), ty_args=[R.Tensor((784, 256), dtype="float32")])
- lv_1 = R.call_tir(Module.fused_matmul_add_relu, I.Tuple([x, lv, p_fc1_bias]), ty_args=[R.Tensor((1, 256), dtype="float32")])
- lv4 = R.call_tir(Module.transpose1, I.Tuple([p_fc2_weight]), ty_args=[R.Tensor((256, 10), dtype="float32")])
- gv = R.call_tir(Module.fused_matmul1_add1, I.Tuple([lv_1, lv4, p_fc2_bias]), ty_args=[R.Tensor((1, 10), dtype="float32")])
+ lv = R.call_tir(Module.transpose, (p_fc1_weight,), ty_args=[R.Tensor((784, 256), dtype="float32")])
+ lv_1 = R.call_tir(Module.fused_matmul_add_relu, (x, lv, p_fc1_bias), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ lv4 = R.call_tir(Module.transpose1, (p_fc2_weight,), ty_args=[R.Tensor((256, 10), dtype="float32")])
+ gv = R.call_tir(Module.fused_matmul1_add1, (lv_1, lv4, p_fc2_bias), ty_args=[R.Tensor((1, 10), dtype="float32")])
R.output(gv)
return gv
@@ -764,8 +764,8 @@ We can deploy the IRModule on CPU by specifying the target as ``llvm``.
.. code-block:: none
- [[ 0.19126415 -0.11120734 -0.18844074 -0.09666331 -0.10459481 0.27168792
- 0.00239159 0.09554429 -0.07331742 0.14715831]]
+ [[-0.05448412 -0.29549795 -0.15731497 -0.03810223 -0.07888201 -0.02606021
+ 0.07264606 -0.02397087 -0.0854951 0.12246296]]
@@ -831,8 +831,8 @@ Now we can compile the IRModule on GPU, the similar way as we did on CPU.
.. code-block:: none
- [[ 0.19126418 -0.11120729 -0.18844078 -0.09666328 -0.10459483 0.27168787
- 0.00239164 0.09554419 -0.07331741 0.14715831]]
+ [[-0.05448417 -0.29549783 -0.15731494 -0.03810223 -0.07888198 -0.02606017
+ 0.07264615 -0.02397087 -0.08549506 0.12246294]]
diff --git a/docs/_sources/get_started/tutorials/quick_start.rst b/docs/_sources/get_started/tutorials/quick_start.rst
index 12cc393f351..52542a6eb6d 100644
--- a/docs/_sources/get_started/tutorials/quick_start.rst
+++ b/docs/_sources/get_started/tutorials/quick_start.rst
@@ -144,11 +144,11 @@ in TVM.
def forward(x: R.Tensor((1, 784), dtype="float32"), fc1_weight: R.Tensor((256, 784), dtype="float32"), fc1_bias: R.Tensor((256,), dtype="float32"), fc2_weight: R.Tensor((10, 256), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 256), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 256), dtype="float32"))
+ permute_dims: R.Tensor((784, 256), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((1, 256), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 256), dtype="float32"))
add: R.Tensor((1, 256), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((1, 256), dtype="float32"))
relu: R.Tensor((1, 256), dtype="float32") = R.nn.relu(add)
- permute_dims1: R.Tensor((256, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((256, 10), dtype="float32"))
+ permute_dims1: R.Tensor((256, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((1, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 10), dtype="float32"))
add1: R.Tensor((1, 10), dtype="float32") = R.add(matmul1, fc2_bias, ty=R.Tensor((1, 10), dtype="float32"))
gv: R.Tensor((1, 10), dtype="float32") = add1
@@ -226,8 +226,8 @@ different devices.
.. code-block:: none
- [[25108.578 25844.07 25979.24 26348.05 25168.773 25847.172 24586.246
- 25995.445 26530.38 25515.549]]
+ [[25122.676 25524.105 26727.49 24541.062 24177.166 24328.219 25000.912
+ 24791.475 24570.314 23909.021]]
diff --git a/docs/_sources/get_started/tutorials/sg_execution_times.rst b/docs/_sources/get_started/tutorials/sg_execution_times.rst
index 31d2146bda8..37ecefbd97e 100644
--- a/docs/_sources/get_started/tutorials/sg_execution_times.rst
+++ b/docs/_sources/get_started/tutorials/sg_execution_times.rst
@@ -6,7 +6,7 @@
Computation times
=================
-**00:06.556** total execution time for 2 files **from get_started/tutorials**:
+**00:05.643** total execution time for 2 files **from get_started/tutorials**:
.. container::
@@ -33,8 +33,8 @@ Computation times
- Time
- Mem (MB)
* - :ref:`sphx_glr_get_started_tutorials_ir_module.py` (``ir_module.py``)
- - 00:06.350
+ - 00:05.473
- 0.0
* - :ref:`sphx_glr_get_started_tutorials_quick_start.py` (``quick_start.py``)
- - 00:00.207
+ - 00:00.170
- 0.0
diff --git a/docs/_sources/how_to/tutorials/cross_compilation_and_rpc.rst b/docs/_sources/how_to/tutorials/cross_compilation_and_rpc.rst
index 49beb105ad8..49f27d547a9 100644
--- a/docs/_sources/how_to/tutorials/cross_compilation_and_rpc.rst
+++ b/docs/_sources/how_to/tutorials/cross_compilation_and_rpc.rst
@@ -275,7 +275,7 @@ device and returns the measured cost. Network overhead is excluded.
.. code-block:: none
- 1.07e-07 secs/op
+ 9.2e-08 secs/op
@@ -864,8 +864,8 @@ This workflow is applicable to various deployment scenarios:
Converted PyTorch model to Relax:
- Number of parameters: 4
Using local target for demonstration
- Exported library to: /tmp/tmpijy_x2fd/model_deployed.so
- Saved parameters to: /tmp/tmpijy_x2fd/model_params.npz
+ Exported library to: /tmp/tmphs8_oft0/model_deployed.so
+ Saved parameters to: /tmp/tmphs8_oft0/model_params.npz
RPC workflow (works for any remote device):
==================================================
diff --git a/docs/_sources/how_to/tutorials/customize_opt.rst b/docs/_sources/how_to/tutorials/customize_opt.rst
index 6d7a4b69993..061c4d7c4d9 100644
--- a/docs/_sources/how_to/tutorials/customize_opt.rst
+++ b/docs/_sources/how_to/tutorials/customize_opt.rst
@@ -129,11 +129,11 @@ with NN module frontend or TVMScript. Here we use a simple neural network model
def forward(x: R.Tensor((1, 784), dtype="float32"), fc1_weight: R.Tensor((256, 784), dtype="float32"), fc1_bias: R.Tensor((256,), dtype="float32"), fc2_weight: R.Tensor((10, 256), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 256), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 256), dtype="float32"))
+ permute_dims: R.Tensor((784, 256), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((1, 256), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 256), dtype="float32"))
add: R.Tensor((1, 256), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((1, 256), dtype="float32"))
relu: R.Tensor((1, 256), dtype="float32") = R.nn.relu(add)
- permute_dims1: R.Tensor((256, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((256, 10), dtype="float32"))
+ permute_dims1: R.Tensor((256, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((1, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 10), dtype="float32"))
gv: R.Tensor((1, 10), dtype="float32") = matmul1
R.output(gv)
@@ -217,8 +217,8 @@ operator. Here we demonstrate how to dispatch the CUBLAS library for certain pat
def forward(x: R.Tensor((1, 784), dtype="float32"), fc1_weight: R.Tensor((256, 784), dtype="float32"), fc1_bias: R.Tensor((256,), dtype="float32"), fc2_weight: R.Tensor((10, 256), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- lv = R.call_dps_packed("fused_relax_permute_dims_relax_matmul_relax_add_relax_nn_relu_cublas", I.Tuple([fc1_weight, x, fc1_bias]), ty_args=[R.Tensor((1, 256), dtype="float32")])
- permute_dims1: R.Tensor((256, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((256, 10), dtype="float32"))
+ lv = R.call_dps_packed("fused_relax_permute_dims_relax_matmul_relax_add_relax_nn_relu_cublas", (fc1_weight, x, fc1_bias), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ permute_dims1: R.Tensor((256, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((1, 10), dtype="float32") = I.Call("relax.matmul", [lv, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 10), dtype="float32"))
gv: R.Tensor((1, 10), dtype="float32") = matmul1
R.output(gv)
@@ -347,7 +347,7 @@ it achieves a balance between performance and compilation time.
vax1_fused_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0 = Ts.axis.spatial(T.int64(10), ax0_fused_0 * T.int64(10) + ax0_fused_1, dtype="int64")
Ts.reads()
- Ts.writes(matmul_rf_local[vax1_fused_1, T.int64(0), v0])
+ Ts.writes(matmul_rf_local[vax1_fused_1, T.int64(0), v0:v0 + T.int64(1)])
matmul_rf_local[vax1_fused_1, T.int64(0), v0] = T.float32(0.0)
for ax1_fused_0 in range(T.int64(0), T.int64(16)):
for u in range(1):
@@ -355,16 +355,16 @@ it achieves a balance between performance and compilation time.
vax1_fused_1_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0_1 = Ts.axis.spatial(T.int64(10), ax0_fused_0 * T.int64(10) + ax0_fused_1, dtype="int64")
vax1_fused_0 = Ts.axis.reduce(T.int64(16), ax1_fused_0, dtype="int64")
- Ts.reads(matmul_rf_local[vax1_fused_1_1, T.int64(0), v0_1], lv[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1], permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1])
- Ts.writes(matmul_rf_local[vax1_fused_1_1, T.int64(0), v0_1])
+ Ts.reads(matmul_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)], lv[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1:vax1_fused_0 * T.int64(16) + vax1_fused_1_1 + T.int64(1)], permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1:v0_1 + T.int64(1)])
+ Ts.writes(matmul_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)])
matmul_rf_local[vax1_fused_1_1, T.int64(0), v0_1] = matmul_rf_local[vax1_fused_1_1, T.int64(0), v0_1] + lv[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1] * permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1]
for ax1_fused in T.thread_binding(T.int64(10), thread="threadIdx.x"):
for ax0 in T.thread_binding(T.int64(16), thread="threadIdx.y"):
with Ts.sblock("matmul"):
vax1_fused_1_2 = Ts.axis.reduce(T.int64(16), ax0, dtype="int64")
v0_2 = Ts.axis.spatial(T.int64(10), ax1_fused, dtype="int64")
- Ts.reads(matmul_rf_local[vax1_fused_1_2, T.int64(0), v0_2])
- Ts.writes(matmul[T.int64(0), v0_2])
+ Ts.reads(matmul_rf_local[vax1_fused_1_2, T.int64(0), v0_2:v0_2 + T.int64(1)])
+ Ts.writes(matmul[T.int64(0), v0_2:v0_2 + T.int64(1)])
with Ts.init():
matmul[T.int64(0), v0_2] = T.float32(0.0)
matmul[T.int64(0), v0_2] = matmul[T.int64(0), v0_2] + matmul_rf_local[vax1_fused_1_2, T.int64(0), v0_2]
@@ -381,17 +381,17 @@ it achieves a balance between performance and compilation time.
v0 = Ts.axis.spatial(T.int64(256), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) // T.int64(10), dtype="int64")
v1 = Ts.axis.spatial(T.int64(10), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) % T.int64(10), dtype="int64")
Ts.where(ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1 < T.int64(2560))
- Ts.reads(fc2_weight[v1, v0])
- Ts.writes(T_transpose[v0, v1])
+ Ts.reads(fc2_weight[v1, v0:v0 + T.int64(1)])
+ Ts.writes(T_transpose[v0, v1:v1 + T.int64(1)])
T_transpose[v0, v1] = fc2_weight[v1, v0]
@R.function
def forward(x: R.Tensor((1, 784), dtype="float32"), fc1_weight: R.Tensor((256, 784), dtype="float32"), fc1_bias: R.Tensor((256,), dtype="float32"), fc2_weight: R.Tensor((10, 256), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- lv = R.call_dps_packed("fused_relax_permute_dims_relax_matmul_relax_add_relax_nn_relu_cublas", I.Tuple([fc1_weight, x, fc1_bias]), ty_args=[R.Tensor((1, 256), dtype="float32")])
- permute_dims1 = R.call_tir(Module.transpose, I.Tuple([fc2_weight]), ty_args=[R.Tensor((256, 10), dtype="float32")])
- gv = R.call_tir(Module.matmul, I.Tuple([lv, permute_dims1]), ty_args=[R.Tensor((1, 10), dtype="float32")])
+ lv = R.call_dps_packed("fused_relax_permute_dims_relax_matmul_relax_add_relax_nn_relu_cublas", (fc1_weight, x, fc1_bias), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ permute_dims1 = R.call_tir(Module.transpose, (fc2_weight,), ty_args=[R.Tensor((256, 10), dtype="float32")])
+ gv = R.call_tir(Module.matmul, (lv, permute_dims1), ty_args=[R.Tensor((1, 10), dtype="float32")])
R.output(gv)
return gv
diff --git a/docs/_sources/how_to/tutorials/e2e_opt_model.rst b/docs/_sources/how_to/tutorials/e2e_opt_model.rst
index 072661a94c0..d88bd5951cd 100644
--- a/docs/_sources/how_to/tutorials/e2e_opt_model.rst
+++ b/docs/_sources/how_to/tutorials/e2e_opt_model.rst
@@ -54,7 +54,7 @@ PyTorch.
.. code-block:: none
Downloading: "https://download.pytorch.org/models/resnet18-f37072fd.pth" to /workspace/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
- 0%| | 0.00/44.7M [00:00<?, ?B/s] 61%|██████▏ | 27.4M/44.7M [00:00<00:00, 286MB/s] 100%|██████████| 44.7M/44.7M [00:00<00:00, 322MB/s]
+ 0%| | 0.00/44.7M [00:00<?, ?B/s] 55%|█████▌ | 24.8M/44.7M [00:00<00:00, 259MB/s] 100%|██████████| 44.7M/44.7M [00:00<00:00, 289MB/s]
diff --git a/docs/_sources/how_to/tutorials/sg_execution_times.rst b/docs/_sources/how_to/tutorials/sg_execution_times.rst
index 06b6fee52ba..3340b5dfbee 100644
--- a/docs/_sources/how_to/tutorials/sg_execution_times.rst
+++ b/docs/_sources/how_to/tutorials/sg_execution_times.rst
@@ -6,7 +6,7 @@
Computation times
=================
-**00:18.679** total execution time for 8 files **from how_to/tutorials**:
+**00:15.114** total execution time for 8 files **from how_to/tutorials**:
.. container::
@@ -33,25 +33,25 @@ Computation times
- Time
- Mem (MB)
* - :ref:`sphx_glr_how_to_tutorials_optimize_llm.py` (``optimize_llm.py``)
- - 00:13.225
+ - 00:10.233
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_import_model.py` (``import_model.py``)
- - 00:03.664
+ - 00:03.335
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_e2e_opt_model.py` (``e2e_opt_model.py``)
- - 00:00.696
+ - 00:00.621
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_cross_compilation_and_rpc.py` (``cross_compilation_and_rpc.py``)
- - 00:00.590
+ - 00:00.489
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_customize_opt.py` (``customize_opt.py``)
- - 00:00.360
+ - 00:00.308
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_bring_your_own_codegen.py` (``bring_your_own_codegen.py``)
- - 00:00.137
+ - 00:00.122
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_mix_python_and_tvm_with_pymodule.py` (``mix_python_and_tvm_with_pymodule.py``)
- - 00:00.005
+ - 00:00.004
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_export_and_load_executable.py` (``export_and_load_executable.py``)
- 00:00.002
diff --git a/docs/_sources/sg_execution_times.rst b/docs/_sources/sg_execution_times.rst
index 4582b50b6e9..391f5f10c23 100644
--- a/docs/_sources/sg_execution_times.rst
+++ b/docs/_sources/sg_execution_times.rst
@@ -6,7 +6,7 @@
Computation times
=================
-**00:26.170** total execution time for 16 files **from all galleries**:
+**00:21.537** total execution time for 16 files **from all galleries**:
.. container::
@@ -33,49 +33,49 @@ Computation times
- Time
- Mem (MB)
* - :ref:`sphx_glr_how_to_tutorials_optimize_llm.py` (``../how_to/tutorials/optimize_llm.py``)
- - 00:13.225
+ - 00:10.233
- 0.0
* - :ref:`sphx_glr_get_started_tutorials_ir_module.py` (``../get_started/tutorials/ir_module.py``)
- - 00:06.350
+ - 00:05.473
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_import_model.py` (``../how_to/tutorials/import_model.py``)
- - 00:03.664
+ - 00:03.335
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_e2e_opt_model.py` (``../how_to/tutorials/e2e_opt_model.py``)
- - 00:00.696
+ - 00:00.621
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_cross_compilation_and_rpc.py` (``../how_to/tutorials/cross_compilation_and_rpc.py``)
- - 00:00.590
+ - 00:00.489
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_customize_opt.py` (``../how_to/tutorials/customize_opt.py``)
- - 00:00.360
+ - 00:00.308
- 0.0
* - :ref:`sphx_glr_deep_dive_tensor_ir_tutorials_tir_transformation.py` (``../deep_dive/tensor_ir/tutorials/tir_transformation.py``)
- - 00:00.317
+ - 00:00.267
- 0.0
* - :ref:`sphx_glr_deep_dive_tensor_ir_tutorials_dlight_gpu_scheduling.py` (``../deep_dive/tensor_ir/tutorials/dlight_gpu_scheduling.py``)
- - 00:00.220
+ - 00:00.184
- 0.0
* - :ref:`sphx_glr_get_started_tutorials_quick_start.py` (``../get_started/tutorials/quick_start.py``)
- - 00:00.207
+ - 00:00.170
- 0.0
* - :ref:`sphx_glr_deep_dive_tensor_ir_tutorials_tir_creation.py` (``../deep_dive/tensor_ir/tutorials/tir_creation.py``)
- - 00:00.161
+ - 00:00.138
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_bring_your_own_codegen.py` (``../how_to/tutorials/bring_your_own_codegen.py``)
- - 00:00.137
+ - 00:00.122
- 0.0
* - :ref:`sphx_glr_deep_dive_relax_tutorials_relax_creation.py` (``../deep_dive/relax/tutorials/relax_creation.py``)
- - 00:00.119
+ - 00:00.095
- 0.0
* - :ref:`sphx_glr_deep_dive_relax_tutorials_relax_transformation.py` (``../deep_dive/relax/tutorials/relax_transformation.py``)
- - 00:00.103
+ - 00:00.083
- 0.0
* - :ref:`sphx_glr_deep_dive_tensor_ir_tutorials_meta_schedule.py` (``../deep_dive/tensor_ir/tutorials/meta_schedule.py``)
- - 00:00.014
+ - 00:00.012
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_mix_python_and_tvm_with_pymodule.py` (``../how_to/tutorials/mix_python_and_tvm_with_pymodule.py``)
- - 00:00.005
+ - 00:00.004
- 0.0
* - :ref:`sphx_glr_how_to_tutorials_export_and_load_executable.py` (``../how_to/tutorials/export_and_load_executable.py``)
- 00:00.002
diff --git a/docs/commit_hash b/docs/commit_hash
index 113c3fa13bd..59e1e669f6e 100644
--- a/docs/commit_hash
+++ b/docs/commit_hash
@@ -1 +1 @@
-ebeebf1116fb2360fa74a82e5f07ffaa7916e87b
+9059d9d25149c9ca7a015717b5023d1e2e1185fd
diff --git a/docs/deep_dive/relax/tutorials/relax_creation.html b/docs/deep_dive/relax/tutorials/relax_creation.html
index 3843aceeaa1..e0c0dab58ba 100644
--- a/docs/deep_dive/relax/tutorials/relax_creation.html
+++ b/docs/deep_dive/relax/tutorials/relax_creation.html
@@ -696,11 +696,11 @@ class Module:
@R.function
def forward(data: R.Tensor((n, 784), dtype="float32"), w0: R.Tensor((128, 784), dtype="float32"), b0: R.Tensor((128,), dtype="float32"), w1: R.Tensor((10, 128), dtype="float32"), b1: R.Tensor((10,), dtype="float32")) -> R.Tensor((n, 10), dtype="float32"):
with R.dataflow():
- lv: R.Tensor((784, 128), dtype="float32") = I.Call("relax.permute_dims", [w0], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 128), dtype="float32"))
+ lv: R.Tensor((784, 128), dtype="float32") = R.permute_dims(w0)
lv1: R.Tensor((n, 128), dtype="float32") = I.Call("relax.matmul", [data, lv], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 128), dtype="float32"))
lv0: R.Tensor((n, 128), dtype="float32") = R.add(lv1, b0, ty=R.Tensor((n, 128), dtype="float32"))
lv1_1: R.Tensor((n, 128), dtype="float32") = R.nn.relu(lv0)
- lv4: R.Tensor((128, 10), dtype="float32") = I.Call("relax.permute_dims", [w1], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((128, 10), dtype="float32"))
+ lv4: R.Tensor((128, 10), dtype="float32") = R.permute_dims(w1)
lv5: R.Tensor((n, 10), dtype="float32") = I.Call("relax.matmul", [lv1_1, lv4], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 10), dtype="float32"))
lv2: R.Tensor((n, 10), dtype="float32") = R.add(lv5, b1, ty=R.Tensor((n, 10), dtype="float32"))
R.output(lv2)
@@ -764,18 +764,18 @@ class Module:
with Ts.sblock("relu"):
v = Ts.axis.spatial(n, i, dtype="int64")
v_1 = Ts.axis.spatial(m, j, dtype="int64")
- Ts.reads(X[v, v_1])
- Ts.writes(Y[v, v_1])
+ Ts.reads(X[v, v_1:v_1 + T.int64(1)])
+ Ts.writes(Y[v, v_1:v_1 + T.int64(1)])
Y[v, v_1] = T.max(X[v, v_1], T.float32(0.0))
@R.function
def forward(data: R.Tensor((n, 784), dtype="float32"), w0: R.Tensor((128, 784), dtype="float32"), b0: R.Tensor((128,), dtype="float32"), w1: R.Tensor((10, 128), dtype="float32"), b1: R.Tensor((10,), dtype="float32")) -> R.Tensor((n, 10), dtype="float32"):
with R.dataflow():
- lv: R.Tensor((784, 128), dtype="float32") = I.Call("relax.permute_dims", [w0], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 128), dtype="float32"))
+ lv: R.Tensor((784, 128), dtype="float32") = R.permute_dims(w0)
lv1: R.Tensor((n, 128), dtype="float32") = I.Call("relax.matmul", [data, lv], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 128), dtype="float32"))
lv0: R.Tensor((n, 128), dtype="float32") = R.add(lv1, b0, ty=R.Tensor((n, 128), dtype="float32"))
- lv1_1 = R.call_tir(Module.relu, I.Tuple([lv0]), ty_args=[R.Tensor((n, 128), dtype="float32")])
- lv4: R.Tensor((128, 10), dtype="float32") = I.Call("relax.permute_dims", [w1], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((128, 10), dtype="float32"))
+ lv1_1 = R.call_tir(Module.relu, (lv0,), ty_args=[R.Tensor((n, 128), dtype="float32")])
+ lv4: R.Tensor((128, 10), dtype="float32") = R.permute_dims(w1)
lv5: R.Tensor((n, 10), dtype="float32") = I.Call("relax.matmul", [lv1_1, lv4], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 10), dtype="float32"))
lv2: R.Tensor((n, 10), dtype="float32") = R.add(lv5, b1, ty=R.Tensor((n, 10), dtype="float32"))
R.output(lv2)
@@ -842,11 +842,11 @@ class Module:
def forward(x: R.Tensor((n, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 128), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 128), dtype="float32"))
+ permute_dims: R.Tensor((784, 128), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((n, 128), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 128), dtype="float32"))
add: R.Tensor((n, 128), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((n, 128), dtype="float32"))
relu: R.Tensor((n, 128), dtype="float32") = R.nn.relu(add)
- permute_dims1: R.Tensor((128, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((128, 10), dtype="float32"))
+ permute_dims1: R.Tensor((128, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((n, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 10), dtype="float32"))
add1: R.Tensor((n, 10), dtype="float32") = R.add(matmul1, fc2_bias, ty=R.Tensor((n, 10), dtype="float32"))
gv: R.Tensor((n, 10), dtype="float32") = add1
@@ -937,8 +937,8 @@ class Module:
with Ts.sblock("compute"):
v_i0 = Ts.axis.spatial(n, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(128), i1, dtype="int64")
- Ts.reads(env_linear[v_i0, v_i1])
- Ts.writes(compute[v_i0, v_i1])
+ Ts.reads(env_linear[v_i0, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(compute[v_i0, v_i1:v_i1 + T.int64(1)])
compute[v_i0, v_i1] = T.max(env_linear[v_i0, v_i1], T.float32(0.0))
@Ts.function
@@ -953,8 +953,8 @@ class Module:
v = Ts.axis.spatial(M, i, dtype="int64")
v_1 = Ts.axis.spatial(N, j, dtype="int64")
v_2 = Ts.axis.reduce(K, k, dtype="int64")
- Ts.reads(X[v, v_2], W[v_1, v_2])
- Ts.writes(Z[v, v_1])
+ Ts.reads(X[v, v_2:v_2 + T.int64(1)], W[v_1, v_2:v_2 + T.int64(1)])
+ Ts.writes(Z[v, v_1:v_1 + T.int64(1)])
with Ts.init():
Z[v, v_1] = T.float32(0.0)
Z[v, v_1] = Z[v, v_1] + X[v, v_2] * W[v_1, v_2]
@@ -963,17 +963,17 @@ class Module:
with Ts.sblock("add"):
v_3 = Ts.axis.spatial(M, i_1, dtype="int64")
v_4 = Ts.axis.spatial(N, j_1, dtype="int64")
- Ts.reads(Z[v_3, v_4], B[v_4])
- Ts.writes(Z[v_3, v_4])
+ Ts.reads(Z[v_3, v_4:v_4 + T.int64(1)], B[v_4:v_4 + T.int64(1)])
+ Ts.writes(Z[v_3, v_4:v_4 + T.int64(1)])
Z[v_3, v_4] = Z[v_3, v_4] + B[v_4]
@R.function
def forward(x: R.Tensor((n_1, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n_1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- env_linear = R.call_dps_packed("env.linear", I.Tuple([x, fc1_weight, fc1_bias]), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
- lv = R.call_tir(Module.relu, I.Tuple([env_linear]), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
- lv1 = R.call_tir(Module.tir_linear, I.Tuple([lv, fc2_weight, fc2_bias]), ty_args=[R.Tensor((n_1, 10), dtype="float32")])
+ env_linear = R.call_dps_packed("env.linear", (x, fc1_weight, fc1_bias), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
+ lv = R.call_tir(Module.relu, (env_linear,), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
+ lv1 = R.call_tir(Module.tir_linear, (lv, fc2_weight, fc2_bias), ty_args=[R.Tensor((n_1, 10), dtype="float32")])
gv: R.Tensor((n_1, 10), dtype="float32") = lv1
R.output(gv)
return gv
@@ -1016,11 +1016,11 @@ class Module:
@R.function
def forward(x: R.Tensor((n, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n, 10), dtype="float32"):
with R.dataflow():
- lv: R.Tensor((784, 128), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 128), dtype="float32"))
+ lv: R.Tensor((784, 128), dtype="float32") = R.permute_dims(fc1_weight)
lv1: R.Tensor((n, 128), dtype="float32") = I.Call("relax.matmul", [x, lv], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 128), dtype="float32"))
lv2: R.Tensor((n, 128), dtype="float32") = R.add(lv1, fc1_bias, ty=R.Tensor((n, 128), dtype="float32"))
lv3: R.Tensor((n, 128), dtype="float32") = R.nn.relu(lv2)
- lv4: R.Tensor((128, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((128, 10), dtype="float32"))
+ lv4: R.Tensor((128, 10), dtype="float32") = R.permute_dims(fc2_weight)
lv5: R.Tensor((n, 10), dtype="float32") = I.Call("relax.matmul", [lv3, lv4], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 10), dtype="float32"))
lv6: R.Tensor((n, 10), dtype="float32") = R.add(lv5, fc2_bias, ty=R.Tensor((n, 10), dtype="float32"))
gv: R.Tensor((n, 10), dtype="float32") = lv6
@@ -1080,8 +1080,8 @@ class Module:
with Ts.sblock("compute"):
v_i0 = Ts.axis.spatial(n, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(128), i1, dtype="int64")
- Ts.reads(lv[v_i0, v_i1])
- Ts.writes(compute[v_i0, v_i1])
+ Ts.reads(lv[v_i0, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(compute[v_i0, v_i1:v_i1 + T.int64(1)])
compute[v_i0, v_i1] = T.max(lv[v_i0, v_i1], T.float32(0.0))
@Ts.function
@@ -1096,8 +1096,8 @@ class Module:
v = Ts.axis.spatial(M, i, dtype="int64")
v_1 = Ts.axis.spatial(N, j, dtype="int64")
v_2 = Ts.axis.reduce(K, k, dtype="int64")
- Ts.reads(X[v, v_2], W[v_1, v_2])
- Ts.writes(Z[v, v_1])
+ Ts.reads(X[v, v_2:v_2 + T.int64(1)], W[v_1, v_2:v_2 + T.int64(1)])
+ Ts.writes(Z[v, v_1:v_1 + T.int64(1)])
with Ts.init():
Z[v, v_1] = T.float32(0.0)
Z[v, v_1] = Z[v, v_1] + X[v, v_2] * W[v_1, v_2]
@@ -1106,16 +1106,16 @@ class Module:
with Ts.sblock("add"):
v_3 = Ts.axis.spatial(M, i_1, dtype="int64")
v_4 = Ts.axis.spatial(N, j_1, dtype="int64")
- Ts.reads(Z[v_3, v_4], B[v_4])
- Ts.writes(Z[v_3, v_4])
+ Ts.reads(Z[v_3, v_4:v_4 + T.int64(1)], B[v_4:v_4 + T.int64(1)])
+ Ts.writes(Z[v_3, v_4:v_4 + T.int64(1)])
Z[v_3, v_4] = Z[v_3, v_4] + B[v_4]
@R.function
def forward(x: R.Tensor((n_1, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n_1, 10), dtype="float32"):
with R.dataflow():
- lv = R.call_dps_packed("env.linear", I.Tuple([x, fc1_weight, fc1_bias]), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
- lv1 = R.call_tir(Module.relu, I.Tuple([lv]), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
- lv2 = R.call_tir(Module.tir_linear, I.Tuple([lv1, fc2_weight, fc2_bias]), ty_args=[R.Tensor((n_1, 10), dtype="float32")])
+ lv = R.call_dps_packed("env.linear", (x, fc1_weight, fc1_bias), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
+ lv1 = R.call_tir(Module.relu, (lv,), ty_args=[R.Tensor((n_1, 128), dtype="float32")])
+ lv2 = R.call_tir(Module.tir_linear, (lv1, fc2_weight, fc2_bias), ty_args=[R.Tensor((n_1, 10), dtype="float32")])
gv: R.Tensor((n_1, 10), dtype="float32") = lv2
R.output(gv)
return lv2
diff --git a/docs/deep_dive/relax/tutorials/relax_transformation.html b/docs/deep_dive/relax/tutorials/relax_transformation.html
index d1a37eb1f36..a3f58699088 100644
--- a/docs/deep_dive/relax/tutorials/relax_transformation.html
+++ b/docs/deep_dive/relax/tutorials/relax_transformation.html
@@ -685,11 +685,11 @@ class Module:
def forward(x: R.Tensor((n, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 128), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 128), dtype="float32"))
+ permute_dims: R.Tensor((784, 128), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((n, 128), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 128), dtype="float32"))
add: R.Tensor((n, 128), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((n, 128), dtype="float32"))
relu: R.Tensor((n, 128), dtype="float32") = R.nn.relu(add)
- permute_dims1: R.Tensor((128, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((128, 10), dtype="float32"))
+ permute_dims1: R.Tensor((128, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((n, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 10), dtype="float32"))
add1: R.Tensor((n, 10), dtype="float32") = R.add(matmul1, fc2_bias, ty=R.Tensor((n, 10), dtype="float32"))
gv: R.Tensor((n, 10), dtype="float32") = add1
@@ -733,8 +733,8 @@ class Module:
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(n, ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(128), ax1, dtype="int64")
- Ts.reads(matmul[v_ax0, v_ax1], fc1_bias[v_ax1])
- Ts.writes(T_add[v_ax0, v_ax1])
+ Ts.reads(matmul[v_ax0, v_ax1:v_ax1 + T.int64(1)], fc1_bias[v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add[v_ax0, v_ax1] = matmul[v_ax0, v_ax1] + fc1_bias[v_ax1]
@Ts.function(private=True)
@@ -748,8 +748,8 @@ class Module:
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(n_1, ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(matmul1[v_ax0, v_ax1], fc2_bias[v_ax1])
- Ts.writes(T_add[v_ax0, v_ax1])
+ Ts.reads(matmul1[v_ax0, v_ax1:v_ax1 + T.int64(1)], fc2_bias[v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add[v_ax0, v_ax1] = matmul1[v_ax0, v_ax1] + fc2_bias[v_ax1]
@Ts.function(private=True)
@@ -765,8 +765,8 @@ class Module:
v_i0 = Ts.axis.spatial(n_2, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(128), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(784), k, dtype="int64")
- Ts.reads(x[v_i0, v_k], permute_dims[v_k, v_i1])
- Ts.writes(matmul[v_i0, v_i1])
+ Ts.reads(x[v_i0, v_k:v_k + T.int64(1)], permute_dims[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul[v_i0, v_i1] = T.float32(0.0)
matmul[v_i0, v_i1] = matmul[v_i0, v_i1] + x[v_i0, v_k] * permute_dims[v_k, v_i1]
@@ -784,8 +784,8 @@ class Module:
v_i0 = Ts.axis.spatial(n_3, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(10), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(128), k, dtype="int64")
- Ts.reads(relu[v_i0, v_k], permute_dims1[v_k, v_i1])
- Ts.writes(matmul[v_i0, v_i1])
+ Ts.reads(relu[v_i0, v_k:v_k + T.int64(1)], permute_dims1[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul[v_i0, v_i1] = T.float32(0.0)
matmul[v_i0, v_i1] = matmul[v_i0, v_i1] + relu[v_i0, v_k] * permute_dims1[v_k, v_i1]
@@ -801,8 +801,8 @@ class Module:
with Ts.sblock("compute"):
v_i0 = Ts.axis.spatial(n_4, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(128), i1, dtype="int64")
- Ts.reads(add[v_i0, v_i1])
- Ts.writes(compute[v_i0, v_i1])
+ Ts.reads(add[v_i0, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(compute[v_i0, v_i1:v_i1 + T.int64(1)])
compute[v_i0, v_i1] = T.max(add[v_i0, v_i1], T.float32(0.0))
@Ts.function(private=True)
@@ -816,8 +816,8 @@ class Module:
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(784), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(128), ax1, dtype="int64")
- Ts.reads(fc1_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(fc1_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = fc1_weight[v_ax1, v_ax0]
@Ts.function(private=True)
@@ -831,21 +831,21 @@ class Module:
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(128), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(fc2_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(fc2_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = fc2_weight[v_ax1, v_ax0]
@R.function
def forward(x: R.Tensor((n_5, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n_5, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims = R.call_tir(Module.transpose, I.Tuple([fc1_weight]), ty_args=[R.Tensor((784, 128), dtype="float32")])
- matmul = R.call_tir(Module.matmul, I.Tuple([x, permute_dims]), ty_args=[R.Tensor((n_5, 128), dtype="float32")])
- add = R.call_tir(Module.add, I.Tuple([matmul, fc1_bias]), ty_args=[R.Tensor((n_5, 128), dtype="float32")])
- relu = R.call_tir(Module.relu, I.Tuple([add]), ty_args=[R.Tensor((n_5, 128), dtype="float32")])
- permute_dims1 = R.call_tir(Module.transpose1, I.Tuple([fc2_weight]), ty_args=[R.Tensor((128, 10), dtype="float32")])
- matmul1 = R.call_tir(Module.matmul1, I.Tuple([relu, permute_dims1]), ty_args=[R.Tensor((n_5, 10), dtype="float32")])
- add1 = R.call_tir(Module.add1, I.Tuple([matmul1, fc2_bias]), ty_args=[R.Tensor((n_5, 10), dtype="float32")])
+ permute_dims = R.call_tir(Module.transpose, (fc1_weight,), ty_args=[R.Tensor((784, 128), dtype="float32")])
+ matmul = R.call_tir(Module.matmul, (x, permute_dims), ty_args=[R.Tensor((n_5, 128), dtype="float32")])
+ add = R.call_tir(Module.add, (matmul, fc1_bias), ty_args=[R.Tensor((n_5, 128), dtype="float32")])
+ relu = R.call_tir(Module.relu, (add,), ty_args=[R.Tensor((n_5, 128), dtype="float32")])
+ permute_dims1 = R.call_tir(Module.transpose1, (fc2_weight,), ty_args=[R.Tensor((128, 10), dtype="float32")])
+ matmul1 = R.call_tir(Module.matmul1, (relu, permute_dims1), ty_args=[R.Tensor((n_5, 10), dtype="float32")])
+ add1 = R.call_tir(Module.add1, (matmul1, fc2_bias), ty_args=[R.Tensor((n_5, 10), dtype="float32")])
gv: R.Tensor((n_5, 10), dtype="float32") = add1
R.output(gv)
return gv
@@ -892,8 +892,8 @@ class Module:
v_i0 = Ts.axis.spatial(n, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(10), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(128), k, dtype="int64")
- Ts.reads(relu[v_i0, v_k], permute_dims1[v_k, v_i1])
- Ts.writes(matmul_intermediate[v_i0, v_i1])
+ Ts.reads(relu[v_i0, v_k:v_k + T.int64(1)], permute_dims1[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul_intermediate[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul_intermediate[v_i0, v_i1] = T.float32(0.0)
matmul_intermediate[v_i0, v_i1] = matmul_intermediate[v_i0, v_i1] + relu[v_i0, v_k] * permute_dims1[v_k, v_i1]
@@ -902,8 +902,8 @@ class Module:
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(n, ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(matmul_intermediate[v_ax0, v_ax1], fc2_bias[v_ax1])
- Ts.writes(T_add_intermediate[v_ax0, v_ax1])
+ Ts.reads(matmul_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)], fc2_bias[v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add_intermediate[v_ax0, v_ax1] = matmul_intermediate[v_ax0, v_ax1] + fc2_bias[v_ax1]
@Ts.function(private=True)
@@ -921,8 +921,8 @@ class Module:
v_i0 = Ts.axis.spatial(n_1, i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(128), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(784), k, dtype="int64")
- Ts.reads(x[v_i0, v_k], permute_dims[v_k, v_i1])
- Ts.writes(matmul_intermediate[v_i0, v_i1])
+ Ts.reads(x[v_i0, v_k:v_k + T.int64(1)], permute_dims[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul_intermediate[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul_intermediate[v_i0, v_i1] = T.float32(0.0)
matmul_intermediate[v_i0, v_i1] = matmul_intermediate[v_i0, v_i1] + x[v_i0, v_k] * permute_dims[v_k, v_i1]
@@ -931,16 +931,16 @@ class Module:
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(n_1, ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(128), ax1, dtype="int64")
- Ts.reads(matmul_intermediate[v_ax0, v_ax1], fc1_bias[v_ax1])
- Ts.writes(T_add_intermediate[v_ax0, v_ax1])
+ Ts.reads(matmul_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)], fc1_bias[v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add_intermediate[v_ax0, v_ax1] = matmul_intermediate[v_ax0, v_ax1] + fc1_bias[v_ax1]
for i0_1 in range(T.int64(0), n_1):
for i1_1 in range(T.int64(0), T.int64(128)):
with Ts.sblock("compute"):
v_i0_1 = Ts.axis.spatial(n_1, i0_1, dtype="int64")
v_i1_1 = Ts.axis.spatial(T.int64(128), i1_1, dtype="int64")
- Ts.reads(T_add_intermediate[v_i0_1, v_i1_1])
- Ts.writes(compute_intermediate[v_i0_1, v_i1_1])
+ Ts.reads(T_add_intermediate[v_i0_1, v_i1_1:v_i1_1 + T.int64(1)])
+ Ts.writes(compute_intermediate[v_i0_1, v_i1_1:v_i1_1 + T.int64(1)])
compute_intermediate[v_i0_1, v_i1_1] = T.max(T_add_intermediate[v_i0_1, v_i1_1], T.float32(0.0))
@Ts.function(private=True)
@@ -954,8 +954,8 @@ class Module:
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(784), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(128), ax1, dtype="int64")
- Ts.reads(fc1_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(fc1_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = fc1_weight[v_ax1, v_ax0]
@Ts.function(private=True)
@@ -969,18 +969,18 @@ class Module:
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(128), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(fc2_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(fc2_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = fc2_weight[v_ax1, v_ax0]
@R.function
def forward(x: R.Tensor((n_2, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n_2, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims = R.call_tir(Module.transpose, I.Tuple([fc1_weight]), ty_args=[R.Tensor((784, 128), dtype="float32")])
- lv = R.call_tir(Module.fused_matmul_add_relu, I.Tuple([x, permute_dims, fc1_bias]), ty_args=[R.Tensor((n_2, 128), dtype="float32")])
- permute_dims1 = R.call_tir(Module.transpose1, I.Tuple([fc2_weight]), ty_args=[R.Tensor((128, 10), dtype="float32")])
- gv = R.call_tir(Module.fused_matmul1_add1, I.Tuple([lv, permute_dims1, fc2_bias]), ty_args=[R.Tensor((n_2, 10), dtype="float32")])
+ permute_dims = R.call_tir(Module.transpose, (fc1_weight,), ty_args=[R.Tensor((784, 128), dtype="float32")])
+ lv = R.call_tir(Module.fused_matmul_add_relu, (x, permute_dims, fc1_bias), ty_args=[R.Tensor((n_2, 128), dtype="float32")])
+ permute_dims1 = R.call_tir(Module.transpose1, (fc2_weight,), ty_args=[R.Tensor((128, 10), dtype="float32")])
+ gv = R.call_tir(Module.fused_matmul1_add1, (lv, permute_dims1, fc2_bias), ty_args=[R.Tensor((n_2, 10), dtype="float32")])
R.output(gv)
return gv
</pre></div>
@@ -1039,11 +1039,11 @@ class Module:
def forward(x: R.Tensor((n, 784), dtype="float32"), fc1_weight: R.Tensor((128, 784), dtype="float32"), fc1_bias: R.Tensor((128,), dtype="float32"), fc2_weight: R.Tensor((10, 128), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((n, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 128), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 128), dtype="float32"))
+ permute_dims: R.Tensor((784, 128), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((n, 128), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 128), dtype="float32"))
add: R.Tensor((n, 128), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((n, 128), dtype="float32"))
relu: R.Tensor((n, 128), dtype="float32") = R.nn.gelu(add)
- permute_dims1: R.Tensor((128, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((128, 10), dtype="float32"))
+ permute_dims1: R.Tensor((128, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((n, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((n, 10), dtype="float32"))
add1: R.Tensor((n, 10), dtype="float32") = R.add(matmul1, fc2_bias, ty=R.Tensor((n, 10), dtype="float32"))
gv: R.Tensor((n, 10), dtype="float32") = add1
diff --git a/docs/deep_dive/relax/tutorials/sg_execution_times.html b/docs/deep_dive/relax/tutorials/sg_execution_times.html
index aea5c351b8d..380fb252531 100644
--- a/docs/deep_dive/relax/tutorials/sg_execution_times.html
+++ b/docs/deep_dive/relax/tutorials/sg_execution_times.html
@@ -627,7 +627,7 @@ document.write(`
<section id="computation-times">
<span id="sphx-glr-deep-dive-relax-tutorials-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading">#</a></h1>
-<p><strong>00:00.222</strong> total execution time for 2 files <strong>from deep_dive/relax/tutorials</strong>:</p>
+<p><strong>00:00.177</strong> total execution time for 2 files <strong>from deep_dive/relax/tutorials</strong>:</p>
<div class="docutils container">
<style scoped>
<link href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/5.3.0/css/bootstrap.min.css" rel="stylesheet" />
@@ -649,11 +649,11 @@ $(document).ready( function () {
</thead>
<tbody>
<tr class="row-even"><td><p><a class="reference internal" href="relax_creation.html#sphx-glr-deep-dive-relax-tutorials-relax-creation-py"><span class="std std-ref">Relax Creation</span></a> (<code class="docutils literal notranslate"><span class="pre">relax_creation.py</span></code>)</p></td>
-<td><p>00:00.119</p></td>
+<td><p>00:00.095</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="relax_transformation.html#sphx-glr-deep-dive-relax-tutorials-relax-transformation-py"><span class="std std-ref">Transformation</span></a> (<code class="docutils literal notranslate"><span class="pre">relax_transformation.py</span></code>)</p></td>
-<td><p>00:00.103</p></td>
+<td><p>00:00.083</p></td>
<td><p>0.0</p></td>
</tr>
</tbody>
diff --git a/docs/deep_dive/tensor_ir/tutorials/dlight_gpu_scheduling.html b/docs/deep_dive/tensor_ir/tutorials/dlight_gpu_scheduling.html
index 7989f04de51..2ebe2fc2b65 100644
--- a/docs/deep_dive/tensor_ir/tutorials/dlight_gpu_scheduling.html
+++ b/docs/deep_dive/tensor_ir/tutorials/dlight_gpu_scheduling.html
@@ -765,7 +765,7 @@ class Module:
vax1_fused_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
Ts.reads()
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0:v0 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0] = T.float32(0.0)
for ax1_fused_0 in range(T.int64(0), T.int64(48)):
for u in range(1):
@@ -773,16 +773,16 @@ class Module:
vax1_fused_1_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0_1 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
vax1_fused_0 = Ts.axis.reduce(T.int64(48), ax1_fused_0, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1], layer_norm[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1], permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1])
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)], layer_norm[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1:vax1_fused_0 * T.int64(16) + vax1_fused_1_1 + T.int64(1)], permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1:v0_1 + T.int64(1)])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] = matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] + layer_norm[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1] * permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1]
for ax1_fused in T.thread_binding(T.int64(16), thread="threadIdx.x"):
for ax0 in T.thread_binding(T.int64(16), thread="threadIdx.y"):
with Ts.sblock("matmul"):
vax1_fused_1_2 = Ts.axis.reduce(T.int64(16), ax0, dtype="int64")
v0_2 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax1_fused, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2])
- Ts.writes(matmul_intermediate_local[T.int64(0), v0_2])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2:v0_2 + T.int64(1)])
+ Ts.writes(matmul_intermediate_local[T.int64(0), v0_2:v0_2 + T.int64(1)])
with Ts.init():
matmul_intermediate_local[T.int64(0), v0_2] = T.float32(0.0)
matmul_intermediate_local[T.int64(0), v0_2] = matmul_intermediate_local[T.int64(0), v0_2] + matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2]
@@ -790,8 +790,8 @@ class Module:
for ax0_fused_1_1 in range(T.int64(0), T.int64(1)):
with Ts.sblock("T_add"):
v0_3 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax0_fused_0_1 + ax0_fused_1_1, dtype="int64")
- Ts.reads(matmul_intermediate_local[T.int64(0), v0_3], fc2_bias[v0_3])
- Ts.writes(T_add_intermediate[T.int64(0), v0_3])
+ Ts.reads(matmul_intermediate_local[T.int64(0), v0_3:v0_3 + T.int64(1)], fc2_bias[v0_3:v0_3 + T.int64(1)])
+ Ts.writes(T_add_intermediate[T.int64(0), v0_3:v0_3 + T.int64(1)])
T_add_intermediate[T.int64(0), v0_3] = matmul_intermediate_local[T.int64(0), v0_3] + fc2_bias[v0_3]
@Ts.function(private=True)
@@ -809,7 +809,7 @@ class Module:
vax1_fused_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
Ts.reads()
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0:v0 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0] = T.float32(0.0)
for ax1_fused_0 in range(T.int64(0), T.int64(48)):
for u in range(1):
@@ -817,16 +817,16 @@ class Module:
vax1_fused_1_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0_1 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
vax1_fused_0 = Ts.axis.reduce(T.int64(48), ax1_fused_0, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1], x[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1], permute_dims[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1])
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)], x[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1:vax1_fused_0 * T.int64(16) + vax1_fused_1_1 + T.int64(1)], permute_dims[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1:v0_1 + T.int64(1)])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] = matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] + x[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1] * permute_dims[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1]
for ax1_fused in T.thread_binding(T.int64(16), thread="threadIdx.x"):
for ax0 in T.thread_binding(T.int64(16), thread="threadIdx.y"):
with Ts.sblock("matmul"):
vax1_fused_1_2 = Ts.axis.reduce(T.int64(16), ax0, dtype="int64")
v0_2 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax1_fused, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2])
- Ts.writes(matmul_intermediate_local[T.int64(0), v0_2])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2:v0_2 + T.int64(1)])
+ Ts.writes(matmul_intermediate_local[T.int64(0), v0_2:v0_2 + T.int64(1)])
with Ts.init():
matmul_intermediate_local[T.int64(0), v0_2] = T.float32(0.0)
matmul_intermediate_local[T.int64(0), v0_2] = matmul_intermediate_local[T.int64(0), v0_2] + matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2]
@@ -834,8 +834,8 @@ class Module:
for ax0_fused_1_1 in range(T.int64(0), T.int64(1)):
with Ts.sblock("compute"):
v0_3 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax0_fused_0_1 + ax0_fused_1_1, dtype="int64")
- Ts.reads(matmul_intermediate_local[T.int64(0), v0_3], fc1_bias[v0_3])
- Ts.writes(compute_intermediate[T.int64(0), v0_3])
+ Ts.reads(matmul_intermediate_local[T.int64(0), v0_3:v0_3 + T.int64(1)], fc1_bias[v0_3:v0_3 + T.int64(1)])
+ Ts.writes(compute_intermediate[T.int64(0), v0_3:v0_3 + T.int64(1)])
compute_intermediate[T.int64(0), v0_3] = T.max(matmul_intermediate_local[T.int64(0), v0_3] + fc1_bias[v0_3], T.float32(0.0))
@Ts.function(private=True)
@@ -853,8 +853,8 @@ class Module:
with Ts.sblock("relu_sum"):
v0 = Ts.axis.spatial(T.int64(1), ax0, dtype="int64")
v1 = Ts.axis.reduce(T.int64(768), ax1_fused_0 * T.int64(256) + ax1_fused_1, dtype="int64")
- Ts.reads(relu[T.int64(0), v1])
- Ts.writes(relu_sum_shared[T.int64(0)])
+ Ts.reads(relu[T.int64(0), v1:v1 + T.int64(1)])
+ Ts.writes(relu_sum_shared[T.int64(0):T.int64(1)])
with Ts.init():
relu_sum_shared[T.int64(0)] = T.float32(0.0)
relu_sum_shared[T.int64(0)] = relu_sum_shared[T.int64(0)] + relu[T.int64(0), v1]
@@ -864,8 +864,8 @@ class Module:
with Ts.sblock("relu_var_sum"):
v0_1 = Ts.axis.spatial(T.int64(1), ax0_1, dtype="int64")
v1_1 = Ts.axis.reduce(T.int64(768), ax1_fused_0_1 * T.int64(256) + ax1_fused_1_1, dtype="int64")
- Ts.reads(relu[T.int64(0), v1_1], relu_sum_shared[T.int64(0)])
- Ts.writes(relu_var_sum_shared[T.int64(0)])
+ Ts.reads(relu[T.int64(0), v1_1:v1_1 + T.int64(1)], relu_sum_shared[T.int64(0):T.int64(1)])
+ Ts.writes(relu_var_sum_shared[T.int64(0):T.int64(1)])
with Ts.init():
relu_var_sum_shared[T.int64(0)] = T.float32(0.0)
relu_var_sum_shared[T.int64(0)] = relu_var_sum_shared[T.int64(0)] + (relu[T.int64(0), v1_1] - relu_sum_shared[T.int64(0)] / T.float32(768.0)) * (relu[T.int64(0), v1_1] - relu_sum_shared[T.int64(0)] / T.float32(768.0))
@@ -874,8 +874,8 @@ class Module:
with Ts.sblock("T_layer_norm"):
v0_2 = Ts.axis.spatial(T.int64(1), T.int64(0), dtype="int64")
v1_2 = Ts.axis.spatial(T.int64(768), ax1_0 * T.int64(256) + ax1_1, dtype="int64")
- Ts.reads(relu[T.int64(0), v1_2], relu_sum_shared[T.int64(0)], relu_var_sum_shared[T.int64(0)], norm_weight[v1_2], norm_bias[v1_2])
- Ts.writes(T_layer_norm[T.int64(0), v1_2])
+ Ts.reads(relu[T.int64(0), v1_2:v1_2 + T.int64(1)], relu_sum_shared[T.int64(0):T.int64(1)], relu_var_sum_shared[T.int64(0):T.int64(1)], norm_weight[v1_2:v1_2 + T.int64(1)], norm_bias[v1_2:v1_2 + T.int64(1)])
+ Ts.writes(T_layer_norm[T.int64(0), v1_2:v1_2 + T.int64(1)])
T_layer_norm[T.int64(0), v1_2] = (relu[T.int64(0), v1_2] - relu_sum_shared[T.int64(0)] / T.float32(768.0)) * T.rsqrt(relu_var_sum_shared[T.int64(0)] / T.float32(768.0) + T.float32(1.0000000000000001e-05)) * norm_weight[v1_2] + norm_bias[v1_2]
@Ts.function(private=True)
@@ -889,8 +889,8 @@ class Module:
with Ts.sblock("T_transpose"):
v0 = Ts.axis.spatial(T.int64(768), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) // T.int64(768), dtype="int64")
v1 = Ts.axis.spatial(T.int64(768), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) % T.int64(768), dtype="int64")
- Ts.reads(fc1_weight[v1, v0])
- Ts.writes(T_transpose[v0, v1])
+ Ts.reads(fc1_weight[v1, v0:v0 + T.int64(1)])
+ Ts.writes(T_transpose[v0, v1:v1 + T.int64(1)])
T_transpose[v0, v1] = fc1_weight[v1, v0]
@Ts.function(private=True)
@@ -904,19 +904,19 @@ class Module:
with Ts.sblock("T_transpose"):
v0 = Ts.axis.spatial(T.int64(768), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) // T.int64(256), dtype="int64")
v1 = Ts.axis.spatial(T.int64(256), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) % T.int64(256), dtype="int64")
- Ts.reads(fc2_weight[v1, v0])
- Ts.writes(T_transpose[v0, v1])
+ Ts.reads(fc2_weight[v1, v0:v0 + T.int64(1)])
+ Ts.writes(T_transpose[v0, v1:v1 + T.int64(1)])
T_transpose[v0, v1] = fc2_weight[v1, v0]
@R.function
def forward(x: R.Tensor((1, 768), dtype="float32"), fc1_weight: R.Tensor((768, 768), dtype="float32"), fc1_bias: R.Tensor((768,), dtype="float32"), norm_weight: R.Tensor((768,), dtype="float32"), norm_bias: R.Tensor((768,), dtype="float32"), fc2_weight: R.Tensor((256, 768), dtype="float32"), fc2_bias: R.Tensor((256,), dtype="float32")) -> R.Tensor((1, 256), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims = R.call_tir(Module.transpose, I.Tuple([fc1_weight]), ty_args=[R.Tensor((768, 768), dtype="float32")])
- lv = R.call_tir(Module.fused_matmul_add_relu, I.Tuple([x, permute_dims, fc1_bias]), ty_args=[R.Tensor((1, 768), dtype="float32")])
- layer_norm = R.call_tir(Module.layer_norm, I.Tuple([lv, norm_weight, norm_bias]), ty_args=[R.Tensor((1, 768), dtype="float32")])
- permute_dims1 = R.call_tir(Module.transpose1, I.Tuple([fc2_weight]), ty_args=[R.Tensor((768, 256), dtype="float32")])
- gv = R.call_tir(Module.fused_matmul1_add1, I.Tuple([layer_norm, permute_dims1, fc2_bias]), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ permute_dims = R.call_tir(Module.transpose, (fc1_weight,), ty_args=[R.Tensor((768, 768), dtype="float32")])
+ lv = R.call_tir(Module.fused_matmul_add_relu, (x, permute_dims, fc1_bias), ty_args=[R.Tensor((1, 768), dtype="float32")])
+ layer_norm = R.call_tir(Module.layer_norm, (lv, norm_weight, norm_bias), ty_args=[R.Tensor((1, 768), dtype="float32")])
+ permute_dims1 = R.call_tir(Module.transpose1, (fc2_weight,), ty_args=[R.Tensor((768, 256), dtype="float32")])
+ gv = R.call_tir(Module.fused_matmul1_add1, (layer_norm, permute_dims1, fc2_bias), ty_args=[R.Tensor((1, 256), dtype="float32")])
R.output(gv)
return gv
</pre></div>
@@ -1164,7 +1164,7 @@ class Module:
vax1_fused_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
Ts.reads()
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0:v0 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0] = T.float32(0.0)
for ax1_fused_0 in range(T.int64(0), T.int64(48)):
for u in range(1):
@@ -1172,16 +1172,16 @@ class Module:
vax1_fused_1_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0_1 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
vax1_fused_0 = Ts.axis.reduce(T.int64(48), ax1_fused_0, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1], layer_norm[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1], permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1])
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)], layer_norm[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1:vax1_fused_0 * T.int64(16) + vax1_fused_1_1 + T.int64(1)], permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1:v0_1 + T.int64(1)])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] = matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] + layer_norm[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1] * permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1]
for ax1_fused in T.thread_binding(T.int64(16), thread="threadIdx.x"):
for ax0 in T.thread_binding(T.int64(16), thread="threadIdx.y"):
with Ts.sblock("matmul"):
vax1_fused_1_2 = Ts.axis.reduce(T.int64(16), ax0, dtype="int64")
v0_2 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax1_fused, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2])
- Ts.writes(matmul_intermediate_local[T.int64(0), v0_2])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2:v0_2 + T.int64(1)])
+ Ts.writes(matmul_intermediate_local[T.int64(0), v0_2:v0_2 + T.int64(1)])
with Ts.init():
matmul_intermediate_local[T.int64(0), v0_2] = T.float32(0.0)
matmul_intermediate_local[T.int64(0), v0_2] = matmul_intermediate_local[T.int64(0), v0_2] + matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2]
@@ -1189,8 +1189,8 @@ class Module:
for ax0_fused_1_1 in range(T.int64(0), T.int64(1)):
with Ts.sblock("T_add"):
v0_3 = Ts.axis.spatial(T.int64(256), ax0_fused_0 * T.int64(16) + ax0_fused_0_1 + ax0_fused_1_1, dtype="int64")
- Ts.reads(matmul_intermediate_local[T.int64(0), v0_3], fc2_bias[v0_3])
- Ts.writes(T_add_intermediate[T.int64(0), v0_3])
+ Ts.reads(matmul_intermediate_local[T.int64(0), v0_3:v0_3 + T.int64(1)], fc2_bias[v0_3:v0_3 + T.int64(1)])
+ Ts.writes(T_add_intermediate[T.int64(0), v0_3:v0_3 + T.int64(1)])
T_add_intermediate[T.int64(0), v0_3] = matmul_intermediate_local[T.int64(0), v0_3] + fc2_bias[v0_3]
@Ts.function(private=True)
@@ -1208,7 +1208,7 @@ class Module:
vax1_fused_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
Ts.reads()
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0:v0 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1, T.int64(0), v0] = T.float32(0.0)
for ax1_fused_0 in range(T.int64(0), T.int64(48)):
for u in range(1):
@@ -1216,16 +1216,16 @@ class Module:
vax1_fused_1_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0_1 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax0_fused_1, dtype="int64")
vax1_fused_0 = Ts.axis.reduce(T.int64(48), ax1_fused_0, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1], x[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1], permute_dims[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1])
- Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)], x[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1:vax1_fused_0 * T.int64(16) + vax1_fused_1_1 + T.int64(1)], permute_dims[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1:v0_1 + T.int64(1)])
+ Ts.writes(matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)])
matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] = matmul_intermediate_rf_local[vax1_fused_1_1, T.int64(0), v0_1] + x[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1] * permute_dims[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1]
for ax1_fused in T.thread_binding(T.int64(16), thread="threadIdx.x"):
for ax0 in T.thread_binding(T.int64(16), thread="threadIdx.y"):
with Ts.sblock("matmul"):
vax1_fused_1_2 = Ts.axis.reduce(T.int64(16), ax0, dtype="int64")
v0_2 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax1_fused, dtype="int64")
- Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2])
- Ts.writes(matmul_intermediate_local[T.int64(0), v0_2])
+ Ts.reads(matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2:v0_2 + T.int64(1)])
+ Ts.writes(matmul_intermediate_local[T.int64(0), v0_2:v0_2 + T.int64(1)])
with Ts.init():
matmul_intermediate_local[T.int64(0), v0_2] = T.float32(0.0)
matmul_intermediate_local[T.int64(0), v0_2] = matmul_intermediate_local[T.int64(0), v0_2] + matmul_intermediate_rf_local[vax1_fused_1_2, T.int64(0), v0_2]
@@ -1233,8 +1233,8 @@ class Module:
for ax0_fused_1_1 in range(T.int64(0), T.int64(1)):
with Ts.sblock("compute"):
v0_3 = Ts.axis.spatial(T.int64(768), ax0_fused_0 * T.int64(16) + ax0_fused_0_1 + ax0_fused_1_1, dtype="int64")
- Ts.reads(matmul_intermediate_local[T.int64(0), v0_3], fc1_bias[v0_3])
- Ts.writes(compute_intermediate[T.int64(0), v0_3])
+ Ts.reads(matmul_intermediate_local[T.int64(0), v0_3:v0_3 + T.int64(1)], fc1_bias[v0_3:v0_3 + T.int64(1)])
+ Ts.writes(compute_intermediate[T.int64(0), v0_3:v0_3 + T.int64(1)])
compute_intermediate[T.int64(0), v0_3] = T.max(matmul_intermediate_local[T.int64(0), v0_3] + fc1_bias[v0_3], T.float32(0.0))
@Ts.function(private=True)
@@ -1252,8 +1252,8 @@ class Module:
with Ts.sblock("relu_sum"):
v0 = Ts.axis.spatial(T.int64(1), ax0, dtype="int64")
v1 = Ts.axis.reduce(T.int64(768), ax1_fused_0 * T.int64(256) + ax1_fused_1, dtype="int64")
- Ts.reads(relu[T.int64(0), v1])
- Ts.writes(relu_sum_shared[T.int64(0)])
+ Ts.reads(relu[T.int64(0), v1:v1 + T.int64(1)])
+ Ts.writes(relu_sum_shared[T.int64(0):T.int64(1)])
with Ts.init():
relu_sum_shared[T.int64(0)] = T.float32(0.0)
relu_sum_shared[T.int64(0)] = relu_sum_shared[T.int64(0)] + relu[T.int64(0), v1]
@@ -1263,8 +1263,8 @@ class Module:
with Ts.sblock("relu_var_sum"):
v0_1 = Ts.axis.spatial(T.int64(1), ax0_1, dtype="int64")
v1_1 = Ts.axis.reduce(T.int64(768), ax1_fused_0_1 * T.int64(256) + ax1_fused_1_1, dtype="int64")
- Ts.reads(relu[T.int64(0), v1_1], relu_sum_shared[T.int64(0)])
- Ts.writes(relu_var_sum_shared[T.int64(0)])
+ Ts.reads(relu[T.int64(0), v1_1:v1_1 + T.int64(1)], relu_sum_shared[T.int64(0):T.int64(1)])
+ Ts.writes(relu_var_sum_shared[T.int64(0):T.int64(1)])
with Ts.init():
relu_var_sum_shared[T.int64(0)] = T.float32(0.0)
relu_var_sum_shared[T.int64(0)] = relu_var_sum_shared[T.int64(0)] + (relu[T.int64(0), v1_1] - relu_sum_shared[T.int64(0)] / T.float32(768.0)) * (relu[T.int64(0), v1_1] - relu_sum_shared[T.int64(0)] / T.float32(768.0))
@@ -1273,8 +1273,8 @@ class Module:
with Ts.sblock("T_layer_norm"):
v0_2 = Ts.axis.spatial(T.int64(1), T.int64(0), dtype="int64")
v1_2 = Ts.axis.spatial(T.int64(768), ax1_0 * T.int64(256) + ax1_1, dtype="int64")
- Ts.reads(relu[T.int64(0), v1_2], relu_sum_shared[T.int64(0)], relu_var_sum_shared[T.int64(0)], norm_weight[v1_2], norm_bias[v1_2])
- Ts.writes(T_layer_norm[T.int64(0), v1_2])
+ Ts.reads(relu[T.int64(0), v1_2:v1_2 + T.int64(1)], relu_sum_shared[T.int64(0):T.int64(1)], relu_var_sum_shared[T.int64(0):T.int64(1)], norm_weight[v1_2:v1_2 + T.int64(1)], norm_bias[v1_2:v1_2 + T.int64(1)])
+ Ts.writes(T_layer_norm[T.int64(0), v1_2:v1_2 + T.int64(1)])
T_layer_norm[T.int64(0), v1_2] = (relu[T.int64(0), v1_2] - relu_sum_shared[T.int64(0)] / T.float32(768.0)) * T.rsqrt(relu_var_sum_shared[T.int64(0)] / T.float32(768.0) + T.float32(1.0000000000000001e-05)) * norm_weight[v1_2] + norm_bias[v1_2]
@Ts.function(private=True)
@@ -1288,8 +1288,8 @@ class Module:
with Ts.sblock("T_transpose"):
v0 = Ts.axis.spatial(T.int64(768), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) // T.int64(768), dtype="int64")
v1 = Ts.axis.spatial(T.int64(768), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) % T.int64(768), dtype="int64")
- Ts.reads(fc1_weight[v1, v0])
- Ts.writes(T_transpose[v0, v1])
+ Ts.reads(fc1_weight[v1, v0:v0 + T.int64(1)])
+ Ts.writes(T_transpose[v0, v1:v1 + T.int64(1)])
T_transpose[v0, v1] = fc1_weight[v1, v0]
@Ts.function(private=True)
@@ -1303,19 +1303,19 @@ class Module:
with Ts.sblock("T_transpose"):
v0 = Ts.axis.spatial(T.int64(768), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) // T.int64(256), dtype="int64")
v1 = Ts.axis.spatial(T.int64(256), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) % T.int64(256), dtype="int64")
- Ts.reads(fc2_weight[v1, v0])
- Ts.writes(T_transpose[v0, v1])
+ Ts.reads(fc2_weight[v1, v0:v0 + T.int64(1)])
+ Ts.writes(T_transpose[v0, v1:v1 + T.int64(1)])
T_transpose[v0, v1] = fc2_weight[v1, v0]
@R.function
def forward(x: R.Tensor((1, 768), dtype="float32"), fc1_weight: R.Tensor((768, 768), dtype="float32"), fc1_bias: R.Tensor((768,), dtype="float32"), norm_weight: R.Tensor((768,), dtype="float32"), norm_bias: R.Tensor((768,), dtype="float32"), fc2_weight: R.Tensor((256, 768), dtype="float32"), fc2_bias: R.Tensor((256,), dtype="float32")) -> R.Tensor((1, 256), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims = R.call_tir(Module.transpose, I.Tuple([fc1_weight]), ty_args=[R.Tensor((768, 768), dtype="float32")])
- lv = R.call_tir(Module.fused_matmul_add_relu, I.Tuple([x, permute_dims, fc1_bias]), ty_args=[R.Tensor((1, 768), dtype="float32")])
- layer_norm = R.call_tir(Module.layer_norm, I.Tuple([lv, norm_weight, norm_bias]), ty_args=[R.Tensor((1, 768), dtype="float32")])
- permute_dims1 = R.call_tir(Module.transpose1, I.Tuple([fc2_weight]), ty_args=[R.Tensor((768, 256), dtype="float32")])
- gv = R.call_tir(Module.fused_matmul1_add1, I.Tuple([layer_norm, permute_dims1, fc2_bias]), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ permute_dims = R.call_tir(Module.transpose, (fc1_weight,), ty_args=[R.Tensor((768, 768), dtype="float32")])
+ lv = R.call_tir(Module.fused_matmul_add_relu, (x, permute_dims, fc1_bias), ty_args=[R.Tensor((1, 768), dtype="float32")])
+ layer_norm = R.call_tir(Module.layer_norm, (lv, norm_weight, norm_bias), ty_args=[R.Tensor((1, 768), dtype="float32")])
+ permute_dims1 = R.call_tir(Module.transpose1, (fc2_weight,), ty_args=[R.Tensor((768, 256), dtype="float32")])
+ gv = R.call_tir(Module.fused_matmul1_add1, (layer_norm, permute_dims1, fc2_bias), ty_args=[R.Tensor((1, 256), dtype="float32")])
R.output(gv)
return gv
</pre></div>
diff --git a/docs/deep_dive/tensor_ir/tutorials/sg_execution_times.html b/docs/deep_dive/tensor_ir/tutorials/sg_execution_times.html
index 32751bdb88a..eee28464fa1 100644
--- a/docs/deep_dive/tensor_ir/tutorials/sg_execution_times.html
+++ b/docs/deep_dive/tensor_ir/tutorials/sg_execution_times.html
@@ -627,7 +627,7 @@ document.write(`
<section id="computation-times">
<span id="sphx-glr-deep-dive-tensor-ir-tutorials-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading">#</a></h1>
-<p><strong>00:00.713</strong> total execution time for 4 files <strong>from deep_dive/tensor_ir/tutorials</strong>:</p>
+<p><strong>00:00.602</strong> total execution time for 4 files <strong>from deep_dive/tensor_ir/tutorials</strong>:</p>
<div class="docutils container">
<style scoped>
<link href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/5.3.0/css/bootstrap.min.css" rel="stylesheet" />
@@ -649,19 +649,19 @@ $(document).ready( function () {
</thead>
<tbody>
<tr class="row-even"><td><p><a class="reference internal" href="tir_transformation.html#sphx-glr-deep-dive-tensor-ir-tutorials-tir-transformation-py"><span class="std std-ref">Transformation</span></a> (<code class="docutils literal notranslate"><span class="pre">tir_transformation.py</span></code>)</p></td>
-<td><p>00:00.317</p></td>
+<td><p>00:00.267</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="dlight_gpu_scheduling.html#sphx-glr-deep-dive-tensor-ir-tutorials-dlight-gpu-scheduling-py"><span class="std std-ref">DLight: Rule-Based GPU Scheduling</span></a> (<code class="docutils literal notranslate"><span class="pre">dlight_gpu_scheduling.py</span></code>)</p></td>
-<td><p>00:00.220</p></td>
+<td><p>00:00.184</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="tir_creation.html#sphx-glr-deep-dive-tensor-ir-tutorials-tir-creation-py"><span class="std std-ref">TensorIR Creation</span></a> (<code class="docutils literal notranslate"><span class="pre">tir_creation.py</span></code>)</p></td>
-<td><p>00:00.161</p></td>
+<td><p>00:00.138</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="meta_schedule.html#sphx-glr-deep-dive-tensor-ir-tutorials-meta-schedule-py"><span class="std std-ref">MetaSchedule: Search-Based Auto-Tuning</span></a> (<code class="docutils literal notranslate"><span class="pre">meta_schedule.py</span></code>)</p></td>
-<td><p>00:00.014</p></td>
+<td><p>00:00.012</p></td>
<td><p>0.0</p></td>
</tr>
</tbody>
diff --git a/docs/deep_dive/tensor_ir/tutorials/tir_creation.html b/docs/deep_dive/tensor_ir/tutorials/tir_creation.html
index 2655256edca..09ba9ef0aab 100644
--- a/docs/deep_dive/tensor_ir/tutorials/tir_creation.html
+++ b/docs/deep_dive/tensor_ir/tutorials/tir_creation.html
@@ -923,8 +923,8 @@ class Module:
v_i = Ts.axis.spatial(128, i)
v_j = Ts.axis.spatial(128, j)
v_k = Ts.axis.reduce(128, k)
- Ts.reads(A[v_i, v_k], B[v_k, v_j])
- Ts.writes(Y[v_i, v_j])
+ Ts.reads(A[v_i, v_k:v_k + 1], B[v_k, v_j:v_j + 1])
+ Ts.writes(Y[v_i, v_j:v_j + 1])
with Ts.init():
Y[v_i, v_j] = T.float32(0.0)
Y[v_i, v_j] = Y[v_i, v_j] + A[v_i, v_k] * B[v_k, v_j]
@@ -933,8 +933,8 @@ class Module:
with Ts.sblock("C"):
v_i_1 = Ts.axis.spatial(128, i_1)
v_j_1 = Ts.axis.spatial(128, j_1)
- Ts.reads(Y[v_i_1, v_j_1])
- Ts.writes(C[v_i_1, v_j_1])
+ Ts.reads(Y[v_i_1, v_j_1:v_j_1 + 1])
+ Ts.writes(C[v_i_1, v_j_1:v_j_1 + 1])
C[v_i_1, v_j_1] = T.max(Y[v_i_1, v_j_1], T.float32(0.0))
</pre></div>
</div>
@@ -981,8 +981,8 @@ class Module:
v_i = Ts.axis.spatial(m, i)
v_j = Ts.axis.spatial(n, j)
v_k = Ts.axis.reduce(k, k_1)
- Ts.reads(A[v_i, v_k], B[v_k, v_j])
- Ts.writes(Y[v_i, v_j])
+ Ts.reads(A[v_i, v_k:v_k + 1], B[v_k, v_j:v_j + 1])
+ Ts.writes(Y[v_i, v_j:v_j + 1])
with Ts.init():
Y[v_i, v_j] = T.float32(0.0)
Y[v_i, v_j] = Y[v_i, v_j] + A[v_i, v_k] * B[v_k, v_j]
@@ -991,8 +991,8 @@ class Module:
with Ts.sblock("C"):
v_i_1 = Ts.axis.spatial(m, i_1)
v_j_1 = Ts.axis.spatial(n, j_1)
- Ts.reads(Y[v_i_1, v_j_1])
- Ts.writes(C[v_i_1, v_j_1])
+ Ts.reads(Y[v_i_1, v_j_1:v_j_1 + 1])
+ Ts.writes(C[v_i_1, v_j_1:v_j_1 + 1])
C[v_i_1, v_j_1] = T.max(Y[v_i_1, v_j_1], T.float32(0.0))
</pre></div>
</div>
diff --git a/docs/deep_dive/tensor_ir/tutorials/tir_transformation.html b/docs/deep_dive/tensor_ir/tutorials/tir_transformation.html
index c257dfceafc..bf57e82f064 100644
--- a/docs/deep_dive/tensor_ir/tutorials/tir_transformation.html
+++ b/docs/deep_dive/tensor_ir/tutorials/tir_transformation.html
@@ -715,7 +715,7 @@ original implementation.</p>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 2.7543 2.7543 2.7543 2.7543 0.0000
+ 2.4568 2.4568 2.4568 2.4568 0.0000
</pre></div>
</div>
<section id="initialization-schedule">
@@ -769,8 +769,8 @@ class Module:
v_1 = Ts.axis.spatial(128, i)
v_2 = Ts.axis.spatial(128, j_0 * 8 + j_1)
v_3 = Ts.axis.reduce(128, k)
- Ts.reads(A[v_1, v_3], B[v_3, v_2])
- Ts.writes(v[v_1, v_2])
+ Ts.reads(A[v_1, v_3:v_3 + 1], B[v_3, v_2:v_2 + 1])
+ Ts.writes(v[v_1, v_2:v_2 + 1])
with Ts.init():
v[v_1, v_2] = T.float32(0.0)
v[v_1, v_2] = v[v_1, v_2] + A[v_1, v_3] * B[v_3, v_2]
@@ -779,8 +779,8 @@ class Module:
with Ts.sblock("C"):
v_4 = Ts.axis.spatial(128, i_1)
v_5 = Ts.axis.spatial(128, j)
- Ts.reads(v[v_4, v_5])
- Ts.writes(C[v_4, v_5])
+ Ts.reads(v[v_4, v_5:v_5 + 1])
+ Ts.writes(C[v_4, v_5:v_5 + 1])
C[v_4, v_5] = T.max(v[v_4, v_5], T.float32(0.0))
</pre></div>
</div>
@@ -815,8 +815,8 @@ class Module:
v_1 = Ts.axis.spatial(128, i)
v_2 = Ts.axis.spatial(128, j_0 * 8 + j_1)
v_3 = Ts.axis.reduce(128, k)
- Ts.reads(A[v_1, v_3], B[v_3, v_2])
- Ts.writes(v[v_1, v_2])
+ Ts.reads(A[v_1, v_3:v_3 + 1], B[v_3, v_2:v_2 + 1])
+ Ts.writes(v[v_1, v_2:v_2 + 1])
with Ts.init():
v[v_1, v_2] = T.float32(0.0)
v[v_1, v_2] = v[v_1, v_2] + A[v_1, v_3] * B[v_3, v_2]
@@ -825,13 +825,13 @@ class Module:
with Ts.sblock("C"):
v_4 = Ts.axis.spatial(128, i_1)
v_5 = Ts.axis.spatial(128, j)
- Ts.reads(v[v_4, v_5])
- Ts.writes(C[v_4, v_5])
+ Ts.reads(v[v_4, v_5:v_5 + 1])
+ Ts.writes(C[v_4, v_5:v_5 + 1])
C[v_4, v_5] = T.max(v[v_4, v_5], T.float32(0.0))
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 0.8625 0.8625 0.8625 0.8625 0.0000
+ 0.8632 0.8632 0.8632 0.8632 0.0000
</pre></div>
</div>
</section>
@@ -868,8 +868,8 @@ class Module:
v_1 = Ts.axis.spatial(128, i)
v_2 = Ts.axis.spatial(128, j_0 * 8 + j_1)
v_3 = Ts.axis.reduce(128, k)
- Ts.reads(A[v_1, v_3], B[v_3, v_2])
- Ts.writes(v[v_1, v_2])
+ Ts.reads(A[v_1, v_3:v_3 + 1], B[v_3, v_2:v_2 + 1])
+ Ts.writes(v[v_1, v_2:v_2 + 1])
with Ts.init():
v[v_1, v_2] = T.float32(0.0)
v[v_1, v_2] = v[v_1, v_2] + A[v_1, v_3] * B[v_3, v_2]
@@ -877,8 +877,8 @@ class Module:
with Ts.sblock("C"):
v_4 = Ts.axis.spatial(128, i)
v_5 = Ts.axis.spatial(128, j_0 * 8 + ax0)
- Ts.reads(v[v_4, v_5])
- Ts.writes(C[v_4, v_5])
+ Ts.reads(v[v_4, v_5:v_5 + 1])
+ Ts.writes(C[v_4, v_5:v_5 + 1])
C[v_4, v_5] = T.max(v[v_4, v_5], T.float32(0.0))
</pre></div>
</div>
@@ -918,7 +918,7 @@ class Module:
v_1 = Ts.axis.spatial(128, i)
v_2 = Ts.axis.spatial(128, j_0 * 8 + j_1_init)
Ts.reads()
- Ts.writes(v[v_1, v_2])
+ Ts.writes(v[v_1, v_2:v_2 + 1])
v[v_1, v_2] = T.float32(0.0)
for k in range(128):
for j_1 in range(8):
@@ -926,20 +926,20 @@ class Module:
v_3 = Ts.axis.spatial(128, i)
v_4 = Ts.axis.spatial(128, j_0 * 8 + j_1)
v_5 = Ts.axis.reduce(128, k)
- Ts.reads(v[v_3, v_4], A[v_3, v_5], B[v_5, v_4])
- Ts.writes(v[v_3, v_4])
+ Ts.reads(v[v_3, v_4:v_4 + 1], A[v_3, v_5:v_5 + 1], B[v_5, v_4:v_4 + 1])
+ Ts.writes(v[v_3, v_4:v_4 + 1])
v[v_3, v_4] = v[v_3, v_4] + A[v_3, v_5] * B[v_5, v_4]
for ax0 in range(8):
with Ts.sblock("C"):
v_6 = Ts.axis.spatial(128, i)
v_7 = Ts.axis.spatial(128, j_0 * 8 + ax0)
- Ts.reads(v[v_6, v_7])
- Ts.writes(C[v_6, v_7])
+ Ts.reads(v[v_6, v_7:v_7 + 1])
+ Ts.writes(C[v_6, v_7:v_7 + 1])
C[v_6, v_7] = T.max(v[v_6, v_7], T.float32(0.0))
Execution time summary:
mean (ms) median (ms) max (ms) min (ms) std (ms)
- 0.3379 0.3379 0.3379 0.3379 0.0000
+ 0.3482 0.3482 0.3482 0.3482 0.0000
</pre></div>
</div>
</section>
@@ -990,7 +990,7 @@ class Module:
v_1 = Ts.axis.spatial(128, i)
v_2 = Ts.axis.spatial(128, j_0 * 8 + j_1_init)
Ts.reads()
- Ts.writes(v[v_1, v_2])
+ Ts.writes(v[v_1, v_2:v_2 + 1])
v[v_1, v_2] = T.float32(0.0)
for k in range(128):
for j_1 in range(8):
@@ -998,15 +998,15 @@ class Module:
v_3 = Ts.axis.spatial(128, i)
v_4 = Ts.axis.spatial(128, j_0 * 8 + j_1)
v_5 = Ts.axis.reduce(128, k)
- Ts.reads(v[v_3, v_4], A[v_3, v_5], B[v_5, v_4])
- Ts.writes(v[v_3, v_4])
+ Ts.reads(v[v_3, v_4:v_4 + 1], A[v_3, v_5:v_5 + 1], B[v_5, v_4:v_4 + 1])
+ Ts.writes(v[v_3, v_4:v_4 + 1])
v[v_3, v_4] = v[v_3, v_4] + A[v_3, v_5] * B[v_5, v_4]
for ax0 in range(8):
with Ts.sblock("C"):
v_6 = Ts.axis.spatial(128, i)
v_7 = Ts.axis.spatial(128, j_0 * 8 + ax0)
- Ts.reads(v[v_6, v_7])
- Ts.writes(C[v_6, v_7])
+ Ts.reads(v[v_6, v_7:v_7 + 1])
+ Ts.writes(C[v_6, v_7:v_7 + 1])
C[v_6, v_7] = T.max(v[v_6, v_7], T.float32(0.0))
# from tvm import s_tir
diff --git a/docs/get_started/tutorials/ir_module.html b/docs/get_started/tutorials/ir_module.html
index 751ddd878c0..6eb255a56a7 100644
--- a/docs/get_started/tutorials/ir_module.html
+++ b/docs/get_started/tutorials/ir_module.html
@@ -782,11 +782,11 @@ class Module:
def forward(x: R.Tensor((1, 784), dtype="float32"), fc1_weight: R.Tensor((256, 784), dtype="float32"), fc1_bias: R.Tensor((256,), dtype="float32"), fc2_weight: R.Tensor((10, 256), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 256), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 256), dtype="float32"))
+ permute_dims: R.Tensor((784, 256), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((1, 256), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 256), dtype="float32"))
add: R.Tensor((1, 256), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((1, 256), dtype="float32"))
relu: R.Tensor((1, 256), dtype="float32") = R.nn.relu(add)
- permute_dims1: R.Tensor((256, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((256, 10), dtype="float32"))
+ permute_dims1: R.Tensor((256, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((1, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 10), dtype="float32"))
add1: R.Tensor((1, 10), dtype="float32") = R.add(matmul1, fc2_bias, ty=R.Tensor((1, 10), dtype="float32"))
gv: R.Tensor((1, 10), dtype="float32") = add1
@@ -843,11 +843,11 @@ class Module:
def main(x: R.Tensor((1, 784), dtype="float32"), fc1_weight: R.Tensor((256, 784), dtype="float32"), fc1_bias: R.Tensor((256,), dtype="float32"), fc2_weight: R.Tensor((10, 256), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 256), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 256), dtype="float32"))
+ permute_dims: R.Tensor((784, 256), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((1, 256), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 256), dtype="float32"))
add: R.Tensor((1, 256), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((1, 256), dtype="float32"))
relu: R.Tensor((1, 256), dtype="float32") = R.nn.relu(add)
- permute_dims1: R.Tensor((256, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((256, 10), dtype="float32"))
+ permute_dims1: R.Tensor((256, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((1, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 10), dtype="float32"))
add1: R.Tensor((1, 10), dtype="float32") = R.add(matmul1, fc2_bias, ty=R.Tensor((1, 10), dtype="float32"))
gv: R.Tensor((1, 10), dtype="float32") = add1
@@ -934,8 +934,8 @@ class Module:
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(T.int64(1), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(256), ax1, dtype="int64")
- Ts.reads(p_fc1_bias[v_ax1], lv1[v_ax0, v_ax1])
- Ts.writes(T_add[v_ax0, v_ax1])
+ Ts.reads(p_fc1_bias[v_ax1:v_ax1 + T.int64(1)], lv1[v_ax0, v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add[v_ax0, v_ax1] = p_fc1_bias[v_ax1] + lv1[v_ax0, v_ax1]
@Ts.function(private=True)
@@ -949,8 +949,8 @@ class Module:
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(T.int64(1), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(p_fc2_bias[v_ax1], lv5[v_ax0, v_ax1])
- Ts.writes(T_add[v_ax0, v_ax1])
+ Ts.reads(p_fc2_bias[v_ax1:v_ax1 + T.int64(1)], lv5[v_ax0, v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add[v_ax0, v_ax1] = p_fc2_bias[v_ax1] + lv5[v_ax0, v_ax1]
@Ts.function(private=True)
@@ -966,8 +966,8 @@ class Module:
v_i0 = Ts.axis.spatial(T.int64(1), i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(256), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(784), k, dtype="int64")
- Ts.reads(x[v_i0, v_k], lv[v_k, v_i1])
- Ts.writes(matmul[v_i0, v_i1])
+ Ts.reads(x[v_i0, v_k:v_k + T.int64(1)], lv[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul[v_i0, v_i1] = T.float32(0.0)
matmul[v_i0, v_i1] = matmul[v_i0, v_i1] + x[v_i0, v_k] * lv[v_k, v_i1]
@@ -985,8 +985,8 @@ class Module:
v_i0 = Ts.axis.spatial(T.int64(1), i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(10), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(256), k, dtype="int64")
- Ts.reads(lv3[v_i0, v_k], lv4[v_k, v_i1])
- Ts.writes(matmul[v_i0, v_i1])
+ Ts.reads(lv3[v_i0, v_k:v_k + T.int64(1)], lv4[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul[v_i0, v_i1] = T.float32(0.0)
matmul[v_i0, v_i1] = matmul[v_i0, v_i1] + lv3[v_i0, v_k] * lv4[v_k, v_i1]
@@ -1002,8 +1002,8 @@ class Module:
with Ts.sblock("compute"):
v_i0 = Ts.axis.spatial(T.int64(1), i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(256), i1, dtype="int64")
- Ts.reads(lv2[v_i0, v_i1])
- Ts.writes(compute[v_i0, v_i1])
+ Ts.reads(lv2[v_i0, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(compute[v_i0, v_i1:v_i1 + T.int64(1)])
compute[v_i0, v_i1] = T.max(lv2[v_i0, v_i1], T.float32(0.0))
@Ts.function(private=True)
@@ -1017,8 +1017,8 @@ class Module:
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(784), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(256), ax1, dtype="int64")
- Ts.reads(p_fc1_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(p_fc1_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = p_fc1_weight[v_ax1, v_ax0]
@Ts.function(private=True)
@@ -1032,21 +1032,21 @@ class Module:
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(256), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(p_fc2_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(p_fc2_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = p_fc2_weight[v_ax1, v_ax0]
@R.function
def main(x: R.Tensor((1, 784), dtype="float32"), p_fc1_weight: R.Tensor((256, 784), dtype="float32"), p_fc1_bias: R.Tensor((256,), dtype="float32"), p_fc2_weight: R.Tensor((10, 256), dtype="float32"), p_fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- lv = R.call_tir(Module.transpose, I.Tuple([p_fc1_weight]), ty_args=[R.Tensor((784, 256), dtype="float32")])
- lv1 = R.call_tir(Module.matmul, I.Tuple([x, lv]), ty_args=[R.Tensor((1, 256), dtype="float32")])
- lv2 = R.call_tir(Module.add, I.Tuple([p_fc1_bias, lv1]), ty_args=[R.Tensor((1, 256), dtype="float32")])
- lv3 = R.call_tir(Module.relu, I.Tuple([lv2]), ty_args=[R.Tensor((1, 256), dtype="float32")])
- lv4 = R.call_tir(Module.transpose1, I.Tuple([p_fc2_weight]), ty_args=[R.Tensor((256, 10), dtype="float32")])
- lv5 = R.call_tir(Module.matmul1, I.Tuple([lv3, lv4]), ty_args=[R.Tensor((1, 10), dtype="float32")])
- lv6 = R.call_tir(Module.add1, I.Tuple([p_fc2_bias, lv5]), ty_args=[R.Tensor((1, 10), dtype="float32")])
+ lv = R.call_tir(Module.transpose, (p_fc1_weight,), ty_args=[R.Tensor((784, 256), dtype="float32")])
+ lv1 = R.call_tir(Module.matmul, (x, lv), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ lv2 = R.call_tir(Module.add, (p_fc1_bias, lv1), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ lv3 = R.call_tir(Module.relu, (lv2,), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ lv4 = R.call_tir(Module.transpose1, (p_fc2_weight,), ty_args=[R.Tensor((256, 10), dtype="float32")])
+ lv5 = R.call_tir(Module.matmul1, (lv3, lv4), ty_args=[R.Tensor((1, 10), dtype="float32")])
+ lv6 = R.call_tir(Module.add1, (p_fc2_bias, lv5), ty_args=[R.Tensor((1, 10), dtype="float32")])
gv: R.Tensor((1, 10), dtype="float32") = lv6
R.output(gv)
return gv
@@ -1109,8 +1109,8 @@ class Module:
v_i0 = Ts.axis.spatial(T.int64(1), i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(10), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(256), k, dtype="int64")
- Ts.reads(lv3[v_i0, v_k], lv4[v_k, v_i1])
- Ts.writes(matmul_intermediate[v_i0, v_i1])
+ Ts.reads(lv3[v_i0, v_k:v_k + T.int64(1)], lv4[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul_intermediate[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul_intermediate[v_i0, v_i1] = T.float32(0.0)
matmul_intermediate[v_i0, v_i1] = matmul_intermediate[v_i0, v_i1] + lv3[v_i0, v_k] * lv4[v_k, v_i1]
@@ -1119,8 +1119,8 @@ class Module:
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(T.int64(1), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(p_fc2_bias[v_ax1], matmul_intermediate[v_ax0, v_ax1])
- Ts.writes(T_add_intermediate[v_ax0, v_ax1])
+ Ts.reads(p_fc2_bias[v_ax1:v_ax1 + T.int64(1)], matmul_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add_intermediate[v_ax0, v_ax1] = p_fc2_bias[v_ax1] + matmul_intermediate[v_ax0, v_ax1]
@Ts.function(private=True)
@@ -1138,8 +1138,8 @@ class Module:
v_i0 = Ts.axis.spatial(T.int64(1), i0, dtype="int64")
v_i1 = Ts.axis.spatial(T.int64(256), i1, dtype="int64")
v_k = Ts.axis.reduce(T.int64(784), k, dtype="int64")
- Ts.reads(x[v_i0, v_k], lv[v_k, v_i1])
- Ts.writes(matmul_intermediate[v_i0, v_i1])
+ Ts.reads(x[v_i0, v_k:v_k + T.int64(1)], lv[v_k, v_i1:v_i1 + T.int64(1)])
+ Ts.writes(matmul_intermediate[v_i0, v_i1:v_i1 + T.int64(1)])
with Ts.init():
matmul_intermediate[v_i0, v_i1] = T.float32(0.0)
matmul_intermediate[v_i0, v_i1] = matmul_intermediate[v_i0, v_i1] + x[v_i0, v_k] * lv[v_k, v_i1]
@@ -1148,16 +1148,16 @@ class Module:
with Ts.sblock("T_add"):
v_ax0 = Ts.axis.spatial(T.int64(1), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(256), ax1, dtype="int64")
- Ts.reads(p_fc1_bias[v_ax1], matmul_intermediate[v_ax0, v_ax1])
- Ts.writes(T_add_intermediate[v_ax0, v_ax1])
+ Ts.reads(p_fc1_bias[v_ax1:v_ax1 + T.int64(1)], matmul_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)])
+ Ts.writes(T_add_intermediate[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_add_intermediate[v_ax0, v_ax1] = p_fc1_bias[v_ax1] + matmul_intermediate[v_ax0, v_ax1]
for i0_1 in range(T.int64(0), T.int64(1)):
for i1_1 in range(T.int64(0), T.int64(256)):
with Ts.sblock("compute"):
v_i0_1 = Ts.axis.spatial(T.int64(1), i0_1, dtype="int64")
v_i1_1 = Ts.axis.spatial(T.int64(256), i1_1, dtype="int64")
- Ts.reads(T_add_intermediate[v_i0_1, v_i1_1])
- Ts.writes(compute_intermediate[v_i0_1, v_i1_1])
+ Ts.reads(T_add_intermediate[v_i0_1, v_i1_1:v_i1_1 + T.int64(1)])
+ Ts.writes(compute_intermediate[v_i0_1, v_i1_1:v_i1_1 + T.int64(1)])
compute_intermediate[v_i0_1, v_i1_1] = T.max(T_add_intermediate[v_i0_1, v_i1_1], T.float32(0.0))
@Ts.function(private=True)
@@ -1171,8 +1171,8 @@ class Module:
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(784), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(256), ax1, dtype="int64")
- Ts.reads(p_fc1_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(p_fc1_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = p_fc1_weight[v_ax1, v_ax0]
@Ts.function(private=True)
@@ -1186,18 +1186,18 @@ class Module:
with Ts.sblock("T_transpose"):
v_ax0 = Ts.axis.spatial(T.int64(256), ax0, dtype="int64")
v_ax1 = Ts.axis.spatial(T.int64(10), ax1, dtype="int64")
- Ts.reads(p_fc2_weight[v_ax1, v_ax0])
- Ts.writes(T_transpose[v_ax0, v_ax1])
+ Ts.reads(p_fc2_weight[v_ax1, v_ax0:v_ax0 + T.int64(1)])
+ Ts.writes(T_transpose[v_ax0, v_ax1:v_ax1 + T.int64(1)])
T_transpose[v_ax0, v_ax1] = p_fc2_weight[v_ax1, v_ax0]
@R.function
def main(x: R.Tensor((1, 784), dtype="float32"), p_fc1_weight: R.Tensor((256, 784), dtype="float32"), p_fc1_bias: R.Tensor((256,), dtype="float32"), p_fc2_weight: R.Tensor((10, 256), dtype="float32"), p_fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- lv = R.call_tir(Module.transpose, I.Tuple([p_fc1_weight]), ty_args=[R.Tensor((784, 256), dtype="float32")])
- lv_1 = R.call_tir(Module.fused_matmul_add_relu, I.Tuple([x, lv, p_fc1_bias]), ty_args=[R.Tensor((1, 256), dtype="float32")])
- lv4 = R.call_tir(Module.transpose1, I.Tuple([p_fc2_weight]), ty_args=[R.Tensor((256, 10), dtype="float32")])
- gv = R.call_tir(Module.fused_matmul1_add1, I.Tuple([lv_1, lv4, p_fc2_bias]), ty_args=[R.Tensor((1, 10), dtype="float32")])
+ lv = R.call_tir(Module.transpose, (p_fc1_weight,), ty_args=[R.Tensor((784, 256), dtype="float32")])
+ lv_1 = R.call_tir(Module.fused_matmul_add_relu, (x, lv, p_fc1_bias), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ lv4 = R.call_tir(Module.transpose1, (p_fc2_weight,), ty_args=[R.Tensor((256, 10), dtype="float32")])
+ gv = R.call_tir(Module.fused_matmul1_add1, (lv_1, lv4, p_fc2_bias), ty_args=[R.Tensor((1, 10), dtype="float32")])
R.output(gv)
return gv
</pre></div>
@@ -1222,8 +1222,8 @@ backends.</p>
<span class="nb">print</span><span class="p">(</span><span class="n">cpu_out</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[[ 0.19126415 -0.11120734 -0.18844074 -0.09666331 -0.10459481 0.27168792
- 0.00239159 0.09554429 -0.07331742 0.14715831]]
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[[-0.05448412 -0.29549795 -0.15731497 -0.03810223 -0.07888201 -0.02606021
+ 0.07264606 -0.02397087 -0.0854951 0.12246296]]
</pre></div>
</div>
</section>
@@ -1257,8 +1257,8 @@ the details of <code class="docutils literal notranslate"><span class="pre">DLig
<span class="k">assert</span> <span class="n">np</span><span class="o">.</span><span class="n">allclose</span><span class="p">(</span><span class="n">cpu_out</span><span class="p">,</span> <span class="n">gpu_out</span><span class="p">,</span> <span class="n">atol</span><span class="o">=</span><span class="mf">1e-3</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[[ 0.19126418 -0.11120729 -0.18844078 -0.09666328 -0.10459483 0.27168787
- 0.00239164 0.09554419 -0.07331741 0.14715831]]
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[[-0.05448417 -0.29549783 -0.15731494 -0.03810223 -0.07888198 -0.02606017
+ 0.07264615 -0.02397087 -0.08549506 0.12246294]]
</pre></div>
</div>
</section>
diff --git a/docs/get_started/tutorials/quick_start.html b/docs/get_started/tutorials/quick_start.html
index b6892d4648f..19fa12a0925 100644
--- a/docs/get_started/tutorials/quick_start.html
+++ b/docs/get_started/tutorials/quick_start.html
@@ -744,11 +744,11 @@ class Module:
def forward(x: R.Tensor((1, 784), dtype="float32"), fc1_weight: R.Tensor((256, 784), dtype="float32"), fc1_bias: R.Tensor((256,), dtype="float32"), fc2_weight: R.Tensor((10, 256), dtype="float32"), fc2_bias: R.Tensor((10,), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 256), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 256), dtype="float32"))
+ permute_dims: R.Tensor((784, 256), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((1, 256), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 256), dtype="float32"))
add: R.Tensor((1, 256), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((1, 256), dtype="float32"))
relu: R.Tensor((1, 256), dtype="float32") = R.nn.relu(add)
- permute_dims1: R.Tensor((256, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((256, 10), dtype="float32"))
+ permute_dims1: R.Tensor((256, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((1, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 10), dtype="float32"))
add1: R.Tensor((1, 10), dtype="float32") = R.add(matmul1, fc2_bias, ty=R.Tensor((1, 10), dtype="float32"))
gv: R.Tensor((1, 10), dtype="float32") = add1
@@ -797,8 +797,8 @@ different devices.</p>
<span class="nb">print</span><span class="p">(</span><span class="n">vm</span><span class="p">[</span><span class="s2">"forward"</span><span class="p">](</span><span class="n">tvm_data</span><span class="p">,</span> <span class="o">*</span><a href="https://docs.python.org/3/builtins/stdtypes.html#list" title="builtins.list" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">params</span></a><span class="p">)</span>< [...]
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[[25108.578 25844.07 25979.24 26348.05 25168.773 25847.172 24586.246
- 25995.445 26530.38 25515.549]]
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[[25122.676 25524.105 26727.49 24541.062 24177.166 24328.219 25000.912
+ 24791.475 24570.314 23909.021]]
</pre></div>
</div>
<p>Our goal is to bring machine learning to the application with any language of interest,
diff --git a/docs/get_started/tutorials/sg_execution_times.html b/docs/get_started/tutorials/sg_execution_times.html
index 4fc85ef099f..64d946801fc 100644
--- a/docs/get_started/tutorials/sg_execution_times.html
+++ b/docs/get_started/tutorials/sg_execution_times.html
@@ -627,7 +627,7 @@ document.write(`
<section id="computation-times">
<span id="sphx-glr-get-started-tutorials-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading">#</a></h1>
-<p><strong>00:06.556</strong> total execution time for 2 files <strong>from get_started/tutorials</strong>:</p>
+<p><strong>00:05.643</strong> total execution time for 2 files <strong>from get_started/tutorials</strong>:</p>
<div class="docutils container">
<style scoped>
<link href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/5.3.0/css/bootstrap.min.css" rel="stylesheet" />
@@ -649,11 +649,11 @@ $(document).ready( function () {
</thead>
<tbody>
<tr class="row-even"><td><p><a class="reference internal" href="ir_module.html#sphx-glr-get-started-tutorials-ir-module-py"><span class="std std-ref">IRModule</span></a> (<code class="docutils literal notranslate"><span class="pre">ir_module.py</span></code>)</p></td>
-<td><p>00:06.350</p></td>
+<td><p>00:05.473</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="quick_start.html#sphx-glr-get-started-tutorials-quick-start-py"><span class="std std-ref">Quick Start</span></a> (<code class="docutils literal notranslate"><span class="pre">quick_start.py</span></code>)</p></td>
-<td><p>00:00.207</p></td>
+<td><p>00:00.170</p></td>
<td><p>0.0</p></td>
</tr>
</tbody>
diff --git a/docs/how_to/tutorials/cross_compilation_and_rpc.html b/docs/how_to/tutorials/cross_compilation_and_rpc.html
index 13ebdc989ff..4401a260352 100644
--- a/docs/how_to/tutorials/cross_compilation_and_rpc.html
+++ b/docs/how_to/tutorials/cross_compilation_and_rpc.html
@@ -826,7 +826,7 @@ device and returns the measured cost. Network overhead is excluded.</p>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"</span><span class="si">{</span><span class="n">cost</span><span class="si">:</span><span class="s2">g</span><span class="si">}</span><span class="s2"> secs/op"</span><span class="p">)</span>
</pre></div>
</div>
-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>1.07e-07 secs/op
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>9.2e-08 secs/op
</pre></div>
</div>
</section>
@@ -1355,8 +1355,8 @@ for ONNX models. Simply replace <code class="docutils literal notranslate"><span
Converted PyTorch model to Relax:
- Number of parameters: 4
Using local target for demonstration
-Exported library to: /tmp/tmpijy_x2fd/model_deployed.so
-Saved parameters to: /tmp/tmpijy_x2fd/model_params.npz
+Exported library to: /tmp/tmphs8_oft0/model_deployed.so
+Saved parameters to: /tmp/tmphs8_oft0/model_params.npz
RPC workflow (works for any remote device):
==================================================
diff --git a/docs/how_to/tutorials/customize_opt.html b/docs/how_to/tutorials/customize_opt.html
index fa3caa85317..7401d340896 100644
--- a/docs/how_to/tutorials/customize_opt.html
+++ b/docs/how_to/tutorials/customize_opt.html
@@ -730,11 +730,11 @@ class Module:
def forward(x: R.Tensor((1, 784), dtype="float32"), fc1_weight: R.Tensor((256, 784), dtype="float32"), fc1_bias: R.Tensor((256,), dtype="float32"), fc2_weight: R.Tensor((10, 256), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- permute_dims: R.Tensor((784, 256), dtype="float32") = I.Call("relax.permute_dims", [fc1_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((784, 256), dtype="float32"))
+ permute_dims: R.Tensor((784, 256), dtype="float32") = R.permute_dims(fc1_weight)
matmul: R.Tensor((1, 256), dtype="float32") = I.Call("relax.matmul", [x, permute_dims], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 256), dtype="float32"))
add: R.Tensor((1, 256), dtype="float32") = R.add(matmul, fc1_bias, ty=R.Tensor((1, 256), dtype="float32"))
relu: R.Tensor((1, 256), dtype="float32") = R.nn.relu(add)
- permute_dims1: R.Tensor((256, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((256, 10), dtype="float32"))
+ permute_dims1: R.Tensor((256, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((1, 10), dtype="float32") = I.Call("relax.matmul", [relu, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 10), dtype="float32"))
gv: R.Tensor((1, 10), dtype="float32") = matmul1
R.output(gv)
@@ -801,8 +801,8 @@ class Module:
def forward(x: R.Tensor((1, 784), dtype="float32"), fc1_weight: R.Tensor((256, 784), dtype="float32"), fc1_bias: R.Tensor((256,), dtype="float32"), fc2_weight: R.Tensor((10, 256), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- lv = R.call_dps_packed("fused_relax_permute_dims_relax_matmul_relax_add_relax_nn_relu_cublas", I.Tuple([fc1_weight, x, fc1_bias]), ty_args=[R.Tensor((1, 256), dtype="float32")])
- permute_dims1: R.Tensor((256, 10), dtype="float32") = I.Call("relax.permute_dims", [fc2_weight], attrs=I.make_node("relax.attrs.PermuteDimsAttrs", axes=None), ty=R.Tensor((256, 10), dtype="float32"))
+ lv = R.call_dps_packed("fused_relax_permute_dims_relax_matmul_relax_add_relax_nn_relu_cublas", (fc1_weight, x, fc1_bias), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ permute_dims1: R.Tensor((256, 10), dtype="float32") = R.permute_dims(fc2_weight)
matmul1: R.Tensor((1, 10), dtype="float32") = I.Call("relax.matmul", [lv, permute_dims1], attrs=I.make_node("relax.attrs.MatmulAttrs", out_dtype=None), ty=R.Tensor((1, 10), dtype="float32"))
gv: R.Tensor((1, 10), dtype="float32") = matmul1
R.output(gv)
@@ -896,7 +896,7 @@ class Module:
vax1_fused_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0 = Ts.axis.spatial(T.int64(10), ax0_fused_0 * T.int64(10) + ax0_fused_1, dtype="int64")
Ts.reads()
- Ts.writes(matmul_rf_local[vax1_fused_1, T.int64(0), v0])
+ Ts.writes(matmul_rf_local[vax1_fused_1, T.int64(0), v0:v0 + T.int64(1)])
matmul_rf_local[vax1_fused_1, T.int64(0), v0] = T.float32(0.0)
for ax1_fused_0 in range(T.int64(0), T.int64(16)):
for u in range(1):
@@ -904,16 +904,16 @@ class Module:
vax1_fused_1_1 = Ts.axis.spatial(T.int64(16), ax1_fused_1, dtype="int64")
v0_1 = Ts.axis.spatial(T.int64(10), ax0_fused_0 * T.int64(10) + ax0_fused_1, dtype="int64")
vax1_fused_0 = Ts.axis.reduce(T.int64(16), ax1_fused_0, dtype="int64")
- Ts.reads(matmul_rf_local[vax1_fused_1_1, T.int64(0), v0_1], lv[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1], permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1])
- Ts.writes(matmul_rf_local[vax1_fused_1_1, T.int64(0), v0_1])
+ Ts.reads(matmul_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)], lv[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1:vax1_fused_0 * T.int64(16) + vax1_fused_1_1 + T.int64(1)], permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1:v0_1 + T.int64(1)])
+ Ts.writes(matmul_rf_local[vax1_fused_1_1, T.int64(0), v0_1:v0_1 + T.int64(1)])
matmul_rf_local[vax1_fused_1_1, T.int64(0), v0_1] = matmul_rf_local[vax1_fused_1_1, T.int64(0), v0_1] + lv[T.int64(0), vax1_fused_0 * T.int64(16) + vax1_fused_1_1] * permute_dims1[vax1_fused_0 * T.int64(16) + vax1_fused_1_1, v0_1]
for ax1_fused in T.thread_binding(T.int64(10), thread="threadIdx.x"):
for ax0 in T.thread_binding(T.int64(16), thread="threadIdx.y"):
with Ts.sblock("matmul"):
vax1_fused_1_2 = Ts.axis.reduce(T.int64(16), ax0, dtype="int64")
v0_2 = Ts.axis.spatial(T.int64(10), ax1_fused, dtype="int64")
- Ts.reads(matmul_rf_local[vax1_fused_1_2, T.int64(0), v0_2])
- Ts.writes(matmul[T.int64(0), v0_2])
+ Ts.reads(matmul_rf_local[vax1_fused_1_2, T.int64(0), v0_2:v0_2 + T.int64(1)])
+ Ts.writes(matmul[T.int64(0), v0_2:v0_2 + T.int64(1)])
with Ts.init():
matmul[T.int64(0), v0_2] = T.float32(0.0)
matmul[T.int64(0), v0_2] = matmul[T.int64(0), v0_2] + matmul_rf_local[vax1_fused_1_2, T.int64(0), v0_2]
@@ -930,17 +930,17 @@ class Module:
v0 = Ts.axis.spatial(T.int64(256), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) // T.int64(10), dtype="int64")
v1 = Ts.axis.spatial(T.int64(10), (ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1) % T.int64(10), dtype="int64")
Ts.where(ax0_ax1_fused_0 * T.int64(1024) + ax0_ax1_fused_1 < T.int64(2560))
- Ts.reads(fc2_weight[v1, v0])
- Ts.writes(T_transpose[v0, v1])
+ Ts.reads(fc2_weight[v1, v0:v0 + T.int64(1)])
+ Ts.writes(T_transpose[v0, v1:v1 + T.int64(1)])
T_transpose[v0, v1] = fc2_weight[v1, v0]
@R.function
def forward(x: R.Tensor((1, 784), dtype="float32"), fc1_weight: R.Tensor((256, 784), dtype="float32"), fc1_bias: R.Tensor((256,), dtype="float32"), fc2_weight: R.Tensor((10, 256), dtype="float32")) -> R.Tensor((1, 10), dtype="float32"):
R.func_attr({"num_input": 1})
with R.dataflow():
- lv = R.call_dps_packed("fused_relax_permute_dims_relax_matmul_relax_add_relax_nn_relu_cublas", I.Tuple([fc1_weight, x, fc1_bias]), ty_args=[R.Tensor((1, 256), dtype="float32")])
- permute_dims1 = R.call_tir(Module.transpose, I.Tuple([fc2_weight]), ty_args=[R.Tensor((256, 10), dtype="float32")])
- gv = R.call_tir(Module.matmul, I.Tuple([lv, permute_dims1]), ty_args=[R.Tensor((1, 10), dtype="float32")])
+ lv = R.call_dps_packed("fused_relax_permute_dims_relax_matmul_relax_add_relax_nn_relu_cublas", (fc1_weight, x, fc1_bias), ty_args=[R.Tensor((1, 256), dtype="float32")])
+ permute_dims1 = R.call_tir(Module.transpose, (fc2_weight,), ty_args=[R.Tensor((256, 10), dtype="float32")])
+ gv = R.call_tir(Module.matmul, (lv, permute_dims1), ty_args=[R.Tensor((1, 10), dtype="float32")])
R.output(gv)
return gv
diff --git a/docs/how_to/tutorials/e2e_opt_model.html b/docs/how_to/tutorials/e2e_opt_model.html
index 398ab3876ac..733d86785d4 100644
--- a/docs/how_to/tutorials/e2e_opt_model.html
+++ b/docs/how_to/tutorials/e2e_opt_model.html
@@ -667,8 +667,8 @@ PyTorch.</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Downloading: "https://download.pytorch.org/models/resnet18-f37072fd.pth" to /workspace/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth
0%| | 0.00/44.7M [00:00<?, ?B/s]
- 61%|██████▏ | 27.4M/44.7M [00:00<00:00, 286MB/s]
-100%|██████████| 44.7M/44.7M [00:00<00:00, 322MB/s]
+ 55%|█████▌ | 24.8M/44.7M [00:00<00:00, 259MB/s]
+100%|██████████| 44.7M/44.7M [00:00<00:00, 289MB/s]
</pre></div>
</div>
</section>
diff --git a/docs/how_to/tutorials/sg_execution_times.html b/docs/how_to/tutorials/sg_execution_times.html
index 2f9a67832f6..b5cc5309fae 100644
--- a/docs/how_to/tutorials/sg_execution_times.html
+++ b/docs/how_to/tutorials/sg_execution_times.html
@@ -627,7 +627,7 @@ document.write(`
<section id="computation-times">
<span id="sphx-glr-how-to-tutorials-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading">#</a></h1>
-<p><strong>00:18.679</strong> total execution time for 8 files <strong>from how_to/tutorials</strong>:</p>
+<p><strong>00:15.114</strong> total execution time for 8 files <strong>from how_to/tutorials</strong>:</p>
<div class="docutils container">
<style scoped>
<link href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/5.3.0/css/bootstrap.min.css" rel="stylesheet" />
@@ -649,31 +649,31 @@ $(document).ready( function () {
</thead>
<tbody>
<tr class="row-even"><td><p><a class="reference internal" href="optimize_llm.html#sphx-glr-how-to-tutorials-optimize-llm-py"><span class="std std-ref">Optimize Large Language Model</span></a> (<code class="docutils literal notranslate"><span class="pre">optimize_llm.py</span></code>)</p></td>
-<td><p>00:13.225</p></td>
+<td><p>00:10.233</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="import_model.html#sphx-glr-how-to-tutorials-import-model-py"><span class="std std-ref">Importing Models from ML Frameworks</span></a> (<code class="docutils literal notranslate"><span class="pre">import_model.py</span></code>)</p></td>
-<td><p>00:03.664</p></td>
+<td><p>00:03.335</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="e2e_opt_model.html#sphx-glr-how-to-tutorials-e2e-opt-model-py"><span class="std std-ref">End-to-End Optimize Model</span></a> (<code class="docutils literal notranslate"><span class="pre">e2e_opt_model.py</span></code>)</p></td>
-<td><p>00:00.696</p></td>
+<td><p>00:00.621</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="cross_compilation_and_rpc.html#sphx-glr-how-to-tutorials-cross-compilation-and-rpc-py"><span class="std std-ref">Cross Compilation and RPC</span></a> (<code class="docutils literal notranslate"><span class="pre">cross_compilation_and_rpc.py</span></code>)</p></td>
-<td><p>00:00.590</p></td>
+<td><p>00:00.489</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="customize_opt.html#sphx-glr-how-to-tutorials-customize-opt-py"><span class="std std-ref">Customize Optimization</span></a> (<code class="docutils literal notranslate"><span class="pre">customize_opt.py</span></code>)</p></td>
-<td><p>00:00.360</p></td>
+<td><p>00:00.308</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="bring_your_own_codegen.html#sphx-glr-how-to-tutorials-bring-your-own-codegen-py"><span class="std std-ref">Bring Your Own Codegen</span></a> (<code class="docutils literal notranslate"><span class="pre">bring_your_own_codegen.py</span></code>)</p></td>
-<td><p>00:00.137</p></td>
+<td><p>00:00.122</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="mix_python_and_tvm_with_pymodule.html#sphx-glr-how-to-tutorials-mix-python-and-tvm-with-pymodule-py"><span class="std std-ref">Mix Python/PyTorch with TVM Using BasePyModule</span></a> (<code class="docutils literal notranslate"><span class="pre">mix_python_and_tvm_with_pymodule.py</span></code>)</p></td>
-<td><p>00:00.005</p></td>
+<td><p>00:00.004</p></td>
<td><p>0.0</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="export_and_load_executable.html#sphx-glr-how-to-tutorials-export-and-load-executable-py"><span class="std std-ref">Export and Load Relax Executables</span></a> (<code class="docutils literal notranslate"><span class="pre">export_and_load_executable.py</span></code>)</p></td>
diff --git a/docs/reference/api/doxygen/annotated.html b/docs/reference/api/doxygen/annotated.html
index 076f80dd197..78adcdeb7a6 100644
--- a/docs/reference/api/doxygen/annotated.html
+++ b/docs/reference/api/doxygen/annotated.html
@@ -89,9 +89,10 @@ $(function() {
<tr id="row_0_1_5_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01PrimType_01_4.html" target="_self">TypeTraits< PrimType ></a></td><td class="desc"></td></tr>
<tr id="row_0_1_6_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01PrimVar_01_4.html" target="_self">TypeTraits< PrimVar ></a></td><td class="desc"></td></tr>
<tr id="row_0_1_7_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01SeqStmt_01_4.html" target="_self">TypeTraits< SeqStmt ></a></td><td class="desc"></td></tr>
-<tr id="row_0_1_8_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01tirx_1_1TensorVar_01_4.html" target="_self">TypeTraits< tirx::TensorVar ></a></td><td class="desc"></td></tr>
-<tr id="row_0_1_9_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01tvm_1_1StringImm_01_4.html" target="_self">TypeTraits< tvm::StringImm ></a></td><td class="desc"></td></tr>
-<tr id="row_0_1_10_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01TypedExpr_3_01ExpectedType_01_4_01_4.html" target="_self">TypeTraits< TypedExpr< ExpectedType > ></a></td><td class="desc"></td></tr>
+<tr id="row_0_1_8_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01TensorRegion_01_4.html" target="_self">TypeTraits< TensorRegion ></a></td><td class="desc"></td></tr>
+<tr id="row_0_1_9_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01tirx_1_1TensorVar_01_4.html" target="_self">TypeTraits< tirx::TensorVar ></a></td><td class="desc"></td></tr>
+<tr id="row_0_1_10_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01tvm_1_1StringImm_01_4.html" target="_self">TypeTraits< tvm::StringImm ></a></td><td class="desc"></td></tr>
+<tr id="row_0_1_11_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01TypedExpr_3_01ExpectedType_01_4_01_4.html" target="_self">TypeTraits< TypedExpr< ExpectedType > ></a></td><td class="desc"></td></tr>
<tr id="row_0_2_" class="odd" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_2_" class="arrow" onclick="toggleFolder('0_2_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacetvm_1_1prim.html" target="_self">prim</a></td><td class="desc"></td></tr>
<tr id="row_0_2_0_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1prim_1_1Add.html" target="_self">Add</a></td><td class="desc">Managed reference to <a class="el" href="classtvm_1_1prim_1_1AddNode.html" title="a + b">AddNode</a> </td></tr>
<tr id="row_0_2_1_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1prim_1_1AddNode.html" target="_self">AddNode</a></td><td class="desc"><ul>
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<tr id="row_0_6_1_46_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1LiteralDocNode.html" target="_self">LiteralDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents literal value </td></tr>
<tr id="row_0_6_1_47_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html" target="_self">NamespaceDoc</a></td><td class="desc">An owning reference to a deferred script namespace </td></tr>
<tr id="row_0_6_1_48_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html" target="_self">NamespaceDocNode</a></td><td class="desc">A reference to a canonical script namespace </td></tr>
-<tr id="row_0_6_1_49_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html" target="_self">OpCallDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html" title="Doc that represents call to an TIRX operator.">OpCallDocNode</a> </td></tr>
-<tr id="row_0_6_1_50_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html" target="_self">OpCallDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents call to an TIRX operator </td></tr>
-<tr id="row_0_6_1_51_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1OperationDoc.html" target="_self">OperationDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1OperationDocNode.html" title="Doc that represents operation.">OperationDocNode</a> </td></tr>
-<tr id="row_0_6_1_52_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1OperationDocNode.html" target="_self">OperationDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents operation </td></tr>
-<tr id="row_0_6_1_53_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ReturnDoc.html" target="_self">ReturnDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1ReturnDocNode.html" title="Doc that represents return statement.">ReturnDocNode</a> </td></tr>
-<tr id="row_0_6_1_54_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ReturnDocNode.html" target="_self">ReturnDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents return statement </td></tr>
-<tr id="row_0_6_1_55_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ScopeDoc.html" target="_self">ScopeDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1ScopeDocNode.html" title="Doc that represents special scopes.">ScopeDocNode</a> </td></tr>
-<tr id="row_0_6_1_56_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ScopeDocNode.html" target="_self">ScopeDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents special scopes </td></tr>
-<tr id="row_0_6_1_57_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1SliceDoc.html" target="_self">SliceDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1SliceDocNode.html" title="Doc that represents slice in Index expression.">SliceDocNode</a> </td></tr>
-<tr id="row_0_6_1_58_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1SliceDocNode.html" target="_self">SliceDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents slice in Index expression </td></tr>
-<tr id="row_0_6_1_59_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtBlockDoc.html" target="_self">StmtBlockDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1StmtBlockDocNode.html" title="The container doc that holds a list of StmtDoc.">StmtBlockDocNode</a> </td></tr>
-<tr id="row_0_6_1_60_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtBlockDocNode.html" target="_self">StmtBlockDocNode</a></td><td class="desc">The container doc that holds a list of <a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html" title="Reference type of StmtDocNode.">StmtDoc</a> </td></tr>
-<tr id="row_0_6_1_61_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html" target="_self">StmtDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html" title="The base class of statement doc.">StmtDocNode</a> </td></tr>
-<tr id="row_0_6_1_62_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html" target="_self">StmtDocNode</a></td><td class="desc">The base class of statement doc </td></tr>
-<tr id="row_0_6_1_63_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1TupleDoc.html" target="_self">TupleDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1TupleDocNode.html" title="Doc that represents tuple literal.">TupleDocNode</a> </td></tr>
-<tr id="row_0_6_1_64_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1TupleDocNode.html" target="_self">TupleDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents tuple literal </td></tr>
-<tr id="row_0_6_1_65_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1WhileDoc.html" target="_self">WhileDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1WhileDocNode.html" title="Doc that represents while statement.">WhileDocNode</a> </td></tr>
-<tr id="row_0_6_1_66_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1WhileDocNode.html" target="_self">WhileDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents while statement </td></tr>
+<tr id="row_0_6_1_49_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1OperationDoc.html" target="_self">OperationDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1OperationDocNode.html" title="Doc that represents operation.">OperationDocNode</a> </td></tr>
+<tr id="row_0_6_1_50_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1OperationDocNode.html" target="_self">OperationDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents operation </td></tr>
+<tr id="row_0_6_1_51_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ReturnDoc.html" target="_self">ReturnDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1ReturnDocNode.html" title="Doc that represents return statement.">ReturnDocNode</a> </td></tr>
+<tr id="row_0_6_1_52_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ReturnDocNode.html" target="_self">ReturnDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents return statement </td></tr>
+<tr id="row_0_6_1_53_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ScopeDoc.html" target="_self">ScopeDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1ScopeDocNode.html" title="Doc that represents special scopes.">ScopeDocNode</a> </td></tr>
+<tr id="row_0_6_1_54_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ScopeDocNode.html" target="_self">ScopeDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents special scopes </td></tr>
+<tr id="row_0_6_1_55_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1SliceDoc.html" target="_self">SliceDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1SliceDocNode.html" title="Doc that represents slice in Index expression.">SliceDocNode</a> </td></tr>
+<tr id="row_0_6_1_56_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1SliceDocNode.html" target="_self">SliceDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents slice in Index expression </td></tr>
+<tr id="row_0_6_1_57_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtBlockDoc.html" target="_self">StmtBlockDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1StmtBlockDocNode.html" title="The container doc that holds a list of StmtDoc.">StmtBlockDocNode</a> </td></tr>
+<tr id="row_0_6_1_58_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtBlockDocNode.html" target="_self">StmtBlockDocNode</a></td><td class="desc">The container doc that holds a list of <a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html" title="Reference type of StmtDocNode.">StmtDoc</a> </td></tr>
+<tr id="row_0_6_1_59_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html" target="_self">StmtDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html" title="The base class of statement doc.">StmtDocNode</a> </td></tr>
+<tr id="row_0_6_1_60_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html" target="_self">StmtDocNode</a></td><td class="desc">The base class of statement doc </td></tr>
+<tr id="row_0_6_1_61_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1TupleDoc.html" target="_self">TupleDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1TupleDocNode.html" title="Doc that represents tuple literal.">TupleDocNode</a> </td></tr>
+<tr id="row_0_6_1_62_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1TupleDocNode.html" target="_self">TupleDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents tuple literal </td></tr>
+<tr id="row_0_6_1_63_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1WhileDoc.html" target="_self">WhileDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1WhileDocNode.html" title="Doc that represents while statement.">WhileDocNode</a> </td></tr>
+<tr id="row_0_6_1_64_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1WhileDocNode.html" target="_self">WhileDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents while statement </td></tr>
<tr id="row_0_7_" class="odd" style="display:none;"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span id="arr_0_7_" class="arrow" onclick="toggleFolder('0_7_')">►</span><span class="icona"><span class="icon">N</span></span><a class="el" href="namespacetvm_1_1support.html" target="_self">support</a></td><td class="desc"></td></tr>
<tr id="row_0_7_0_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1support_1_1NVTXScopedRange.html" target="_self">NVTXScopedRange</a></td><td class="desc">A class to create a NVTX range. No-op if TVM is not built against NVTX </td></tr>
<tr id="row_0_7_1_" class="odd" style="display:none;"><td class="entry"><span style="width:48px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1support_1_1Serializer.html" target="_self">Serializer</a></td><td class="desc">Primary <a class="el" href="structtvm_1_1support_1_1Serializer.html" title="Primary Serializer template. Specialize for each serializable type.">Serializer</a> template. Specialize for each seri [...]
diff --git a/docs/reference/api/doxygen/classes.html b/docs/reference/api/doxygen/classes.html
index 3492cc4a33e..ab70063e5ea 100644
--- a/docs/reference/api/doxygen/classes.html
+++ b/docs/reference/api/doxygen/classes.html
@@ -112,7 +112,7 @@ $(function() {
<dd><a class="el" href="classtvm_1_1script_1_1ir__builder_1_1details_1_1Namer.html">Namer</a> (<a class="el" href="namespacetvm_1_1script_1_1ir__builder_1_1details.html">tvm::script::ir_builder::details</a>)</dd><dd><a class="el" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html">NamespaceDoc</a> (<a class="el" href="namespacetvm_1_1script_1_1printer.html">tvm::script::printer</a>)</dd><dd><a class="el" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html">NamespaceDocNode [...]
<dl class="classindex even">
<dt class="alphachar"><a id="letter_O" name="letter_O">O</a></dt>
-<dd><a class="el" href="classtvm_1_1ObjectFunctor.html">ObjectFunctor</a> (<a class="el" href="namespacetvm.html">tvm</a>)</dd><dd><a class="el" href="classtvm_1_1ObjectFunctor_3_01R_07NodeArg_00_01Args_8_8_8_08_4.html">ObjectFunctor< R(NodeArg, Args...)></a> (<a class="el" href="namespacetvm.html">tvm</a>)</dd><dd><a class="el" href="classtvm_1_1ObjectMutator.html">ObjectMutator</a> (<a class="el" href="namespacetvm.html">tvm</a>)</dd><dd><a class="el" href="classtvm_1_1ObjectVisi [...]
+<dd><a class="el" href="classtvm_1_1ObjectFunctor.html">ObjectFunctor</a> (<a class="el" href="namespacetvm.html">tvm</a>)</dd><dd><a class="el" href="classtvm_1_1ObjectFunctor_3_01R_07NodeArg_00_01Args_8_8_8_08_4.html">ObjectFunctor< R(NodeArg, Args...)></a> (<a class="el" href="namespacetvm.html">tvm</a>)</dd><dd><a class="el" href="classtvm_1_1ObjectMutator.html">ObjectMutator</a> (<a class="el" href="namespacetvm.html">tvm</a>)</dd><dd><a class="el" href="classtvm_1_1ObjectVisi [...]
<dl class="classindex odd">
<dt class="alphachar"><a id="letter_P" name="letter_P">P</a></dt>
<dd><a class="el" href="classtvm_1_1relax_1_1PackedFuncType.html">PackedFuncType</a> (<a class="el" href="namespacetvm_1_1relax.html">tvm::relax</a>)</dd><dd><a class="el" href="classtvm_1_1relax_1_1PackedFuncTypeNode.html">PackedFuncTypeNode</a> (<a class="el" href="namespacetvm_1_1relax.html">tvm::relax</a>)</dd><dd><a class="el" href="structtvm_1_1relax_1_1PadAttrs.html">PadAttrs</a> (<a class="el" href="namespacetvm_1_1relax.html">tvm::relax</a>)</dd><dd><a class="el" href="structtvm [...]
@@ -127,7 +127,7 @@ $(function() {
<dd><a class="el" href="classtvm_1_1relax_1_1SameShapeConstraint.html">SameShapeConstraint</a> (<a class="el" href="namespacetvm_1_1relax.html">tvm::relax</a>)</dd><dd><a class="el" href="classtvm_1_1relax_1_1SameShapeConstraintNode.html">SameShapeConstraintNode</a> (<a class="el" href="namespacetvm_1_1relax.html">tvm::relax</a>)</dd><dd><a class="el" href="classtvm_1_1tirx_1_1SBijectiveLayout.html">SBijectiveLayout</a> (<a class="el" href="namespacetvm_1_1tirx.html">tvm::tirx</a>)</dd>< [...]
<dl class="classindex odd">
<dt class="alphachar"><a id="letter_T" name="letter_T">T</a></dt>
-<dd><a class="el" href="structtvm_1_1relax_1_1TakeAttrs.html">TakeAttrs</a> (<a class="el" href="namespacetvm_1_1relax.html">tvm::relax</a>)</dd><dd><a class="el" href="structtvm_1_1relax_1_1TakeBackwardAttrs.html">TakeBackwardAttrs</a> (<a class="el" href="namespacetvm_1_1relax.html">tvm::relax</a>)</dd><dd><a class="el" href="classtvm_1_1Target.html">Target</a> (<a class="el" href="namespacetvm.html">tvm</a>)</dd><dd><a class="el" href="classtvm_1_1TargetKind.html">TargetKind</a> (<a c [...]
+<dd><a class="el" href="structtvm_1_1relax_1_1TakeAttrs.html">TakeAttrs</a> (<a class="el" href="namespacetvm_1_1relax.html">tvm::relax</a>)</dd><dd><a class="el" href="structtvm_1_1relax_1_1TakeBackwardAttrs.html">TakeBackwardAttrs</a> (<a class="el" href="namespacetvm_1_1relax.html">tvm::relax</a>)</dd><dd><a class="el" href="classtvm_1_1Target.html">Target</a> (<a class="el" href="namespacetvm.html">tvm</a>)</dd><dd><a class="el" href="classtvm_1_1TargetKind.html">TargetKind</a> (<a c [...]
<dl class="classindex even">
<dt class="alphachar"><a id="letter_U" name="letter_U">U</a></dt>
<dd><a class="el" href="classtvm_1_1UniqueNameSupply.html">UniqueNameSupply</a> (<a class="el" href="namespacetvm.html">tvm</a>)</dd><dd><a class="el" href="classtvm_1_1UniqueNameSupplyNode.html">UniqueNameSupplyNode</a> (<a class="el" href="namespacetvm.html">tvm</a>)</dd><dd><a class="el" href="classtvm_1_1UnknownLoc.html">UnknownLoc</a> (<a class="el" href="namespacetvm.html">tvm</a>)</dd><dd><a class="el" href="classtvm_1_1UnknownLocNode.html">UnknownLocNode</a> (<a class="el" href=" [...]
diff --git a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1Doc.html b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1Doc.html
index 1220ca2baec..8de57dcb2f6 100644
--- a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1Doc.html
+++ b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1Doc.html
@@ -88,7 +88,7 @@ $(function() {
<div class="dynheader">
Inheritance diagram for tvm::script::printer::Doc:</div>
<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1script_1_1printer_1_1Doc__inherit__graph.svg" width="7295" height="770"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
+<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1script_1_1printer_1_1Doc__inherit__graph.svg" width="7024" height="770"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
</div>
<div class="dynheader">
Collaboration diagram for tvm::script::printer::Doc:</div>
diff --git a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1DocNode.html b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1DocNode.html
index 59cc5b77109..415f21d3439 100644
--- a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1DocNode.html
+++ b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1DocNode.html
@@ -90,7 +90,7 @@ $(function() {
<div class="dynheader">
Inheritance diagram for tvm::script::printer::DocNode:</div>
<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1script_1_1printer_1_1DocNode__inherit__graph.svg" width="6251" height="784"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
+<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1script_1_1printer_1_1DocNode__inherit__graph.svg" width="6019" height="784"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
</div>
<div class="dynheader">
Collaboration diagram for tvm::script::printer::DocNode:</div>
diff --git a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1DocNode__inherit__graph.svg b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1DocNode__inherit__graph.svg
index 4868e1bd334..380aa781834 100644
--- a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1DocNode__inherit__graph.svg
+++ b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1DocNode__inherit__graph.svg
@@ -4,8 +4,8 @@
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-->
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- viewBox="0.00 0.00 4688.00 588.00" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
+<svg width="4514pt" height="588pt"
+ viewBox="0.00 0.00 4514.00 588.00" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g id="graph0" class="graph" transform="scale(1 1) rotate(0) translate(4 584)">
<title>tvm::script::printer::DocNode</title>
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@@ -137,20 +137,20 @@
<g id="Node000018" class="node">
<title>Node18</title>
<g id="a_Node000018"><a xlink:href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html" target="_top" xlink:title="The base class of statement doc.">
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-<text text-anchor="start" x="3251.5" y="-301" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
-<text text-anchor="start" x="3260" y="-290" font-family="Helvetica,sans-Serif" font-size="10.00">::StmtDocNode</text>
-<text text-anchor="start" x="3223" y="-275" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
-<text text-anchor="start" x="3236" y="-275" font-family="Helvetica,sans-Serif" font-size="10.00">comment</text>
-<text text-anchor="start" x="3223" y="-260" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
-<text text-anchor="start" x="3236" y="-260" font-family="Helvetica,sans-Serif" font-size="10.00">TVM_FFI_DECLARE_OBJECT</text>
-<text text-anchor="start" x="3236" y="-249" font-family="Helvetica,sans-Serif" font-size="10.00">_INFO()</text>
-<text text-anchor="start" x="3223" y="-234" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
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-<polygon fill="#666666" stroke="#666666" points="3219,-270 3219,-270 3234,-270 3234,-270 3219,-270"/>
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+<polygon fill="white" stroke="transparent" points="3288,-313 3132,-313 3132,-227 3288,-227 3288,-313"/>
+<text text-anchor="start" x="3164.5" y="-301" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
+<text text-anchor="start" x="3173" y="-290" font-family="Helvetica,sans-Serif" font-size="10.00">::StmtDocNode</text>
+<text text-anchor="start" x="3136" y="-275" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="3149" y="-275" font-family="Helvetica,sans-Serif" font-size="10.00">comment</text>
+<text text-anchor="start" x="3136" y="-260" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="3149" y="-260" font-family="Helvetica,sans-Serif" font-size="10.00">TVM_FFI_DECLARE_OBJECT</text>
+<text text-anchor="start" x="3149" y="-249" font-family="Helvetica,sans-Serif" font-size="10.00">_INFO()</text>
+<text text-anchor="start" x="3136" y="-234" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="3149" y="-234" font-family="Helvetica,sans-Serif" font-size="10.00">RegisterReflection()</text>
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+<polygon fill="#666666" stroke="#666666" points="3132,-270 3132,-270 3147,-270 3147,-270 3132,-270"/>
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</g>
</g>
@@ -158,8 +158,8 @@
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<title>Node1->Node18</title>
<g id="a_edge17_Node000001_Node000018"><a xlink:title=" ">
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@@ -589,8 +589,8 @@
<g id="edge18_Node000018_Node000019" class="edge">
<title>Node18->Node19</title>
<g id="a_edge18_Node000018_Node000019"><a xlink:title=" ">
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+<polygon fill="none" stroke="#63b8ff" points="3121.83,-269.48 3131.96,-266.37 3122.1,-262.48 3121.83,-269.48"/>
</a>
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</g>
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<g id="edge19_Node000018_Node000020" class="edge">
<title>Node18->Node20</title>
<g id="a_edge19_Node000018_Node000020"><a xlink:title=" ">
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</a>
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@@ -651,8 +651,8 @@
<g id="edge20_Node000018_Node000021" class="edge">
<title>Node18->Node21</title>
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<g id="edge21_Node000018_Node000022" class="edge">
<title>Node18->Node22</title>
<g id="a_edge21_Node000018_Node000022"><a xlink:title=" ">
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<g id="edge22_Node000018_Node000023" class="edge">
<title>Node18->Node23</title>
<g id="a_edge22_Node000018_Node000023"><a xlink:title=" ">
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@@ -741,8 +741,8 @@
<g id="edge23_Node000018_Node000024" class="edge">
<title>Node18->Node24</title>
<g id="a_edge23_Node000018_Node000024"><a xlink:title=" ">
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@@ -769,8 +769,8 @@
<g id="edge24_Node000018_Node000025" class="edge">
<title>Node18->Node25</title>
<g id="a_edge24_Node000018_Node000025"><a xlink:title=" ">
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+<polygon fill="none" stroke="#63b8ff" points="3206.5,-216.92 3210,-226.92 3213.5,-216.92 3206.5,-216.92"/>
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<g id="edge25_Node000018_Node000026" class="edge">
<title>Node18->Node26</title>
<g id="a_edge25_Node000018_Node000026"><a xlink:title=" ">
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-<polygon fill="none" stroke="#63b8ff" points="3317.56,-216.38 3316.52,-226.92 3323.91,-219.32 3317.56,-216.38"/>
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@@ -833,8 +833,8 @@
<g id="edge26_Node000018_Node000027" class="edge">
<title>Node18->Node27</title>
<g id="a_edge26_Node000018_Node000027"><a xlink:title=" ">
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<g id="edge27_Node000018_Node000028" class="edge">
<title>Node18->Node28</title>
<g id="a_edge27_Node000018_Node000028"><a xlink:title=" ">
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<g id="edge28_Node000018_Node000029" class="edge">
<title>Node18->Node29</title>
<g id="a_edge28_Node000018_Node000029"><a xlink:title=" ">
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<g id="Node000030" class="node">
<title>Node30</title>
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+<polygon fill="#666666" stroke="#666666" points="4002,-80.5 4002,-80.5 4017,-80.5 4017,-80.5 4002,-80.5"/>
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<g id="edge29_Node000018_Node000030" class="edge">
<title>Node18->Node30</title>
<g id="a_edge29_Node000018_Node000030"><a xlink:title=" ">
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<g id="Node000031" class="node">
<title>Node31</title>
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<g id="Node000032" class="node">
<title>Node32</title>
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+<text text-anchor="start" x="4382.5" y="-118.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
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+<text text-anchor="start" x="4367" y="-36.5" font-family="Helvetica,sans-Serif" font-size="10.00">RegisterReflection()</text>
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<title>Node18->Node32</title>
<g id="a_edge31_Node000018_Node000032"><a xlink:title=" ">
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-<text text-anchor="start" x="4528" y="-77.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
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index e4011bcab9b..5b63320d1cd 100644
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+ viewBox="0.00 0.00 5268.00 577.00" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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<title>Node18</title>
<g id="a_Node000018"><a xlink:href="classtvm_1_1script_1_1printer_1_1StmtDoc.html" target="_top" xlink:title="Reference type of StmtDocNode.">
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+<text text-anchor="start" x="3658.5" y="-290" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="3671.5" y="-290" font-family="Helvetica,sans-Serif" font-size="10.00">TVM_FFI_DEFINE_OBJECT</text>
+<text text-anchor="start" x="3671.5" y="-279" font-family="Helvetica,sans-Serif" font-size="10.00">_REF_METHODS_NOTNULLABLE()</text>
+<text text-anchor="start" x="3658.5" y="-264" font-family="Helvetica,sans-Serif" font-size="10.00">#</text>
+<text text-anchor="start" x="3671.5" y="-264" font-family="Helvetica,sans-Serif" font-size="10.00">StmtDoc()</text>
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<title>Node1->Node18</title>
<g id="a_edge17_Node000001_Node000018"><a xlink:title=" ">
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<g id="edge18_Node000018_Node000019" class="edge">
<title>Node18->Node19</title>
<g id="a_edge18_Node000018_Node000019"><a xlink:title=" ">
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<g id="edge19_Node000018_Node000020" class="edge">
<title>Node18->Node20</title>
<g id="a_edge19_Node000018_Node000020"><a xlink:title=" ">
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<g id="edge20_Node000018_Node000021" class="edge">
<title>Node18->Node21</title>
<g id="a_edge20_Node000018_Node000021"><a xlink:title=" ">
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<g id="edge21_Node000018_Node000022" class="edge">
<title>Node18->Node22</title>
<g id="a_edge21_Node000018_Node000022"><a xlink:title=" ">
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<g id="edge22_Node000018_Node000023" class="edge">
<title>Node18->Node23</title>
<g id="a_edge22_Node000018_Node000023"><a xlink:title=" ">
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<g id="edge23_Node000018_Node000024" class="edge">
<title>Node18->Node24</title>
<g id="a_edge23_Node000018_Node000024"><a xlink:title=" ">
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<g id="edge24_Node000018_Node000025" class="edge">
<title>Node18->Node25</title>
<g id="a_edge24_Node000018_Node000025"><a xlink:title=" ">
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<g id="edge25_Node000018_Node000026" class="edge">
<title>Node18->Node26</title>
<g id="a_edge25_Node000018_Node000026"><a xlink:title=" ">
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<g id="edge26_Node000018_Node000027" class="edge">
<title>Node18->Node27</title>
<g id="a_edge26_Node000018_Node000027"><a xlink:title=" ">
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<g id="edge27_Node000018_Node000028" class="edge">
<title>Node18->Node28</title>
<g id="a_edge27_Node000018_Node000028"><a xlink:title=" ">
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<g id="Node000030" class="node">
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<text text-anchor="start" x="4686.5" y="-78" font-family="Helvetica,sans-Serif" font-size="10.00">TVM_FFI_DEFINE_OBJECT</text>
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<g id="Node000031" class="node">
<title>Node31</title>
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<g id="Node000032" class="node">
<title>Node32</title>
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+<text text-anchor="start" x="5122.5" y="-134" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
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+<text text-anchor="start" x="5092.5" y="-93" font-family="Helvetica,sans-Serif" font-size="10.00">WhileDoc()</text>
+<text text-anchor="start" x="5079.5" y="-78" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="5092.5" y="-78" font-family="Helvetica,sans-Serif" font-size="10.00">TVM_FFI_DEFINE_OBJECT</text>
+<text text-anchor="start" x="5092.5" y="-67" font-family="Helvetica,sans-Serif" font-size="10.00">_REF_METHODS_NOTNULLABLE()</text>
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<title>Node18->Node32</title>
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-<g id="Node000033" class="node">
-<title>Node33</title>
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diff --git a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1OpCallDoc-members.html b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1OpCallDoc-members.html
deleted file mode 100644
index d568e585583..00000000000
--- a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1OpCallDoc-members.html
+++ /dev/null
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-<meta name="generator" content="Doxygen 1.9.8"/>
-<meta name="viewport" content="width=device-width, initial-scale=1"/>
-<title>tvm: Member List</title>
-<link href="tabs.css" rel="stylesheet" type="text/css"/>
-<script type="text/javascript" src="jquery.js"></script>
-<script type="text/javascript" src="dynsections.js"></script>
-<link href="search/search.css" rel="stylesheet" type="text/css"/>
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-<script type="text/javascript" src="search/search.js"></script>
-<link href="doxygen.css" rel="stylesheet" type="text/css" />
-</head>
-<body>
-<div id="top"><!-- do not remove this div, it is closed by doxygen! -->
-<div id="titlearea">
-<table cellspacing="0" cellpadding="0">
- <tbody>
- <tr id="projectrow">
- <td id="projectalign">
- <div id="projectname">tvm
- </div>
- </td>
- </tr>
- </tbody>
-</table>
-</div>
-<!-- end header part -->
-<!-- Generated by Doxygen 1.9.8 -->
-<script type="text/javascript">
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-<div class="SRStatus" id="Loading">Loading...</div>
-<div class="SRStatus" id="Searching">Searching...</div>
-<div class="SRStatus" id="NoMatches">No Matches</div>
-</div>
-</div>
-</div>
-</div>
-
-<div id="nav-path" class="navpath">
- <ul>
-<li class="navelem"><a class="el" href="namespacetvm.html">tvm</a></li><li class="navelem"><a class="el" href="namespacetvm_1_1script.html">script</a></li><li class="navelem"><a class="el" href="namespacetvm_1_1script_1_1printer.html">printer</a></li><li class="navelem"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html">OpCallDoc</a></li> </ul>
-</div>
-</div><!-- top -->
-<div class="header">
- <div class="headertitle"><div class="title">tvm::script::printer::OpCallDoc Member List</div></div>
-</div><!--header-->
-<div class="contents">
-
-<p>This is the complete list of members for <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html">tvm::script::printer::OpCallDoc</a>, including all inherited members.</p>
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- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html#accbc6699956d0166032a97e80ad3880d">Doc</a>()=default</td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html">tvm::script::printer::Doc</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
- <tr class="odd"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html#ab8976b239f8ee9da30e3bbd5eb569409">Doc</a>(ffi::ObjectPtr< DocNode > data)</td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html">tvm::script::printer::Doc</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">explicit</span><span class="mlabel">protected</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#ab5b4f91b550e6e9b43f8a5659604da42">OpCallDoc</a>(ExprDoc callee, ffi::Array< Doc > args, ffi::Optional< DictDoc > workspace, ffi::Optional< DictDoc > config, ffi::Optional< ExprDoc > dispatch=std::nullopt)</td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html">tvm::script::printer::OpCallDoc</a></td><td class="entry"><span cl [...]
- <tr class="odd"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html#adec8d59e41d8a4093fb310089bf2c3ba">StmtDoc</a>()=default</td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html">tvm::script::printer::StmtDoc</a></td><td class="entry"><span class="mlabel">protected</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#a6ebc9be8e178115a68d47075669f32a7">TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE</a>(OpCallDoc, StmtDoc, OpCallDocNode)</td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html">tvm::script::printer::OpCallDoc</a></td><td class="entry"></td></tr>
- <tr class="odd"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html#a9e9caa28a84fc631d8b8ec90dfa3a2b9">tvm::script::printer::StmtDoc::TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE</a>(StmtDoc, Doc, StmtDocNode)</td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html">tvm::script::printer::StmtDoc</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html#a7e2ec6a42fa85c58589d3d06722460e8">tvm::script::printer::Doc::TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE</a>(Doc, ffi::ObjectRef, DocNode)</td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html">tvm::script::printer::Doc</a></td><td class="entry"></td></tr>
-</table></div><!-- contents -->
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diff --git a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1OpCallDoc.html b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1OpCallDoc.html
deleted file mode 100644
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-
-<div id="nav-path" class="navpath">
- <ul>
-<li class="navelem"><a class="el" href="namespacetvm.html">tvm</a></li><li class="navelem"><a class="el" href="namespacetvm_1_1script.html">script</a></li><li class="navelem"><a class="el" href="namespacetvm_1_1script_1_1printer.html">printer</a></li><li class="navelem"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html">OpCallDoc</a></li> </ul>
-</div>
-</div><!-- top -->
-<div class="header">
- <div class="summary">
-<a href="#pub-methods">Public Member Functions</a> |
-<a href="classtvm_1_1script_1_1printer_1_1OpCallDoc-members.html">List of all members</a> </div>
- <div class="headertitle"><div class="title">tvm::script::printer::OpCallDoc Class Reference</div></div>
-</div><!--header-->
-<div class="contents">
-
-<p>Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html" title="Doc that represents call to an TIRX operator.">OpCallDocNode</a>.
- <a href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#details">More...</a></p>
-
-<p><code>#include <<a class="el" href="doc_8h_source.html">doc.h</a>></code></p>
-<div class="dynheader">
-Inheritance diagram for tvm::script::printer::OpCallDoc:</div>
-<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1script_1_1printer_1_1OpCallDoc__inherit__graph.svg" width="258" height="570"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
-</div>
-<div class="dynheader">
-Collaboration diagram for tvm::script::printer::OpCallDoc:</div>
-<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1script_1_1printer_1_1OpCallDoc__coll__graph.svg" width="258" height="570"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
-</div>
-<table class="memberdecls">
-<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="pub-methods" name="pub-methods"></a>
-Public Member Functions</h2></td></tr>
-<tr class="memitem:ab5b4f91b550e6e9b43f8a5659604da42" id="r_ab5b4f91b550e6e9b43f8a5659604da42"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#ab5b4f91b550e6e9b43f8a5659604da42">OpCallDoc</a> (<a class="el" href="classtvm_1_1script_1_1printer_1_1ExprDoc.html">ExprDoc</a> callee, ffi::Array< <a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html">Doc</a> > [...]
-<tr class="memdesc:ab5b4f91b550e6e9b43f8a5659604da42"><td class="mdescLeft"> </td><td class="mdescRight">Constructor of <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html" title="Reference type of OpCallDocNode.">OpCallDoc</a>. <br /></td></tr>
-<tr class="separator:ab5b4f91b550e6e9b43f8a5659604da42"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="memitem:a6ebc9be8e178115a68d47075669f32a7" id="r_a6ebc9be8e178115a68d47075669f32a7"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#a6ebc9be8e178115a68d47075669f32a7">TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE</a> (<a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html">OpCallDoc</a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1Stm [...]
-<tr class="separator:a6ebc9be8e178115a68d47075669f32a7"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="inherit_header pub_methods_classtvm_1_1script_1_1printer_1_1StmtDoc"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classtvm_1_1script_1_1printer_1_1StmtDoc')"><img src="closed.png" alt="-"/> Public Member Functions inherited from <a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html">tvm::script::printer::StmtDoc</a></td></tr>
-<tr class="memitem:a9e9caa28a84fc631d8b8ec90dfa3a2b9 inherit pub_methods_classtvm_1_1script_1_1printer_1_1StmtDoc" id="r_a9e9caa28a84fc631d8b8ec90dfa3a2b9"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html#a9e9caa28a84fc631d8b8ec90dfa3a2b9">TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE</a> (<a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html">StmtDoc</a>, < [...]
-<tr class="separator:a9e9caa28a84fc631d8b8ec90dfa3a2b9 inherit pub_methods_classtvm_1_1script_1_1printer_1_1StmtDoc"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="inherit_header pub_methods_classtvm_1_1script_1_1printer_1_1Doc"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classtvm_1_1script_1_1printer_1_1Doc')"><img src="closed.png" alt="-"/> Public Member Functions inherited from <a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html">tvm::script::printer::Doc</a></td></tr>
-<tr class="memitem:a7e2ec6a42fa85c58589d3d06722460e8 inherit pub_methods_classtvm_1_1script_1_1printer_1_1Doc" id="r_a7e2ec6a42fa85c58589d3d06722460e8"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html#a7e2ec6a42fa85c58589d3d06722460e8">TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE</a> (<a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html">Doc</a>, ffi::ObjectRef, < [...]
-<tr class="separator:a7e2ec6a42fa85c58589d3d06722460e8 inherit pub_methods_classtvm_1_1script_1_1printer_1_1Doc"><td class="memSeparator" colspan="2"> </td></tr>
-</table><table class="memberdecls">
-<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="inherited" name="inherited"></a>
-Additional Inherited Members</h2></td></tr>
-<tr class="inherit_header pro_methods_classtvm_1_1script_1_1printer_1_1StmtDoc"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classtvm_1_1script_1_1printer_1_1StmtDoc')"><img src="closed.png" alt="-"/> Protected Member Functions inherited from <a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html">tvm::script::printer::StmtDoc</a></td></tr>
-<tr class="memitem:adec8d59e41d8a4093fb310089bf2c3ba inherit pro_methods_classtvm_1_1script_1_1printer_1_1StmtDoc" id="r_adec8d59e41d8a4093fb310089bf2c3ba"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html#adec8d59e41d8a4093fb310089bf2c3ba">StmtDoc</a> ()=default</td></tr>
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-<tr class="inherit_header pro_methods_classtvm_1_1script_1_1printer_1_1Doc"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classtvm_1_1script_1_1printer_1_1Doc')"><img src="closed.png" alt="-"/> Protected Member Functions inherited from <a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html">tvm::script::printer::Doc</a></td></tr>
-<tr class="memitem:accbc6699956d0166032a97e80ad3880d inherit pro_methods_classtvm_1_1script_1_1printer_1_1Doc" id="r_accbc6699956d0166032a97e80ad3880d"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html#accbc6699956d0166032a97e80ad3880d">Doc</a> ()=default</td></tr>
-<tr class="separator:accbc6699956d0166032a97e80ad3880d inherit pro_methods_classtvm_1_1script_1_1printer_1_1Doc"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="memitem:ab8976b239f8ee9da30e3bbd5eb569409 inherit pro_methods_classtvm_1_1script_1_1printer_1_1Doc" id="r_ab8976b239f8ee9da30e3bbd5eb569409"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html#ab8976b239f8ee9da30e3bbd5eb569409">Doc</a> (ffi::ObjectPtr< <a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html">DocNode</a> > data)</td></tr>
-<tr class="separator:ab8976b239f8ee9da30e3bbd5eb569409 inherit pro_methods_classtvm_1_1script_1_1printer_1_1Doc"><td class="memSeparator" colspan="2"> </td></tr>
-</table>
-<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
-<div class="textblock"><p>Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html" title="Doc that represents call to an TIRX operator.">OpCallDocNode</a>. </p>
-<dl class="section see"><dt>See also</dt><dd><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html" title="Doc that represents call to an TIRX operator.">OpCallDocNode</a> </dd></dl>
-</div><h2 class="groupheader">Constructor & Destructor Documentation</h2>
-<a id="ab5b4f91b550e6e9b43f8a5659604da42" name="ab5b4f91b550e6e9b43f8a5659604da42"></a>
-<h2 class="memtitle"><span class="permalink"><a href="#ab5b4f91b550e6e9b43f8a5659604da42">◆ </a></span>OpCallDoc()</h2>
-
-<div class="memitem">
-<div class="memproto">
-<table class="mlabels">
- <tr>
- <td class="mlabels-left">
- <table class="memname">
- <tr>
- <td class="memname">tvm::script::printer::OpCallDoc::OpCallDoc </td>
- <td>(</td>
- <td class="paramtype"><a class="el" href="classtvm_1_1script_1_1printer_1_1ExprDoc.html">ExprDoc</a> </td>
- <td class="paramname"><em>callee</em>, </td>
- </tr>
- <tr>
- <td class="paramkey"></td>
- <td></td>
- <td class="paramtype">ffi::Array< <a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html">Doc</a> > </td>
- <td class="paramname"><em>args</em>, </td>
- </tr>
- <tr>
- <td class="paramkey"></td>
- <td></td>
- <td class="paramtype">ffi::Optional< <a class="el" href="classtvm_1_1script_1_1printer_1_1DictDoc.html">DictDoc</a> > </td>
- <td class="paramname"><em>workspace</em>, </td>
- </tr>
- <tr>
- <td class="paramkey"></td>
- <td></td>
- <td class="paramtype">ffi::Optional< <a class="el" href="classtvm_1_1script_1_1printer_1_1DictDoc.html">DictDoc</a> > </td>
- <td class="paramname"><em>config</em>, </td>
- </tr>
- <tr>
- <td class="paramkey"></td>
- <td></td>
- <td class="paramtype">ffi::Optional< <a class="el" href="classtvm_1_1script_1_1printer_1_1ExprDoc.html">ExprDoc</a> > </td>
- <td class="paramname"><em>dispatch</em> = <code>std::nullopt</code> </td>
- </tr>
- <tr>
- <td></td>
- <td>)</td>
- <td></td><td></td>
- </tr>
- </table>
- </td>
- <td class="mlabels-right">
-<span class="mlabels"><span class="mlabel">explicit</span></span> </td>
- </tr>
-</table>
-</div><div class="memdoc">
-
-<p>Constructor of <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html" title="Reference type of OpCallDocNode.">OpCallDoc</a>. </p>
-<dl class="params"><dt>Parameters</dt><dd>
- <table class="params">
- <tr><td class="paramname">callee</td><td>The callee of this function call. </td></tr>
- <tr><td class="paramname">args</td><td>The positional arguments. </td></tr>
- <tr><td class="paramname">workspace</td><td>The workspace of this op call. </td></tr>
- <tr><td class="paramname">config</td><td>The config of this op call. </td></tr>
- <tr><td class="paramname">dispatch</td><td>The optional dispatch variant name of this op call. </td></tr>
- </table>
- </dd>
-</dl>
-
-</div>
-</div>
-<h2 class="groupheader">Member Function Documentation</h2>
-<a id="a6ebc9be8e178115a68d47075669f32a7" name="a6ebc9be8e178115a68d47075669f32a7"></a>
-<h2 class="memtitle"><span class="permalink"><a href="#a6ebc9be8e178115a68d47075669f32a7">◆ </a></span>TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE()</h2>
-
-<div class="memitem">
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- <table class="memname">
- <tr>
- <td class="memname">tvm::script::printer::OpCallDoc::TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE </td>
- <td>(</td>
- <td class="paramtype"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html">OpCallDoc</a> </td>
- <td class="paramname">, </td>
- </tr>
- <tr>
- <td class="paramkey"></td>
- <td></td>
- <td class="paramtype"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html">StmtDoc</a> </td>
- <td class="paramname">, </td>
- </tr>
- <tr>
- <td class="paramkey"></td>
- <td></td>
- <td class="paramtype"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">OpCallDocNode</a> </td>
- <td class="paramname"> </td>
- </tr>
- <tr>
- <td></td>
- <td>)</td>
- <td></td><td></td>
- </tr>
- </table>
-</div><div class="memdoc">
-
-</div>
-</div>
-<hr/>The documentation for this class was generated from the following file:<ul>
-<li>include/tvm/script/printer/<a class="el" href="doc_8h_source.html">doc.h</a></li>
-</ul>
-</div><!-- contents -->
-<!-- start footer part -->
-<hr class="footer"/><address class="footer"><small>
-Generated by <a href="https://www.doxygen.org/index.html"><img class="footer" src="doxygen.svg" width="104" height="31" alt="doxygen"/></a> 1.9.8
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diff --git a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1OpCallDocNode-members.html b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1OpCallDocNode-members.html
deleted file mode 100644
index 18a189dd15d..00000000000
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-<li class="navelem"><a class="el" href="namespacetvm.html">tvm</a></li><li class="navelem"><a class="el" href="namespacetvm_1_1script.html">script</a></li><li class="navelem"><a class="el" href="namespacetvm_1_1script_1_1printer.html">printer</a></li><li class="navelem"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">OpCallDocNode</a></li> </ul>
-</div>
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-<div class="header">
- <div class="headertitle"><div class="title">tvm::script::printer::OpCallDocNode Member List</div></div>
-</div><!--header-->
-<div class="contents">
-
-<p>This is the complete list of members for <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">tvm::script::printer::OpCallDocNode</a>, including all inherited members.</p>
-<table class="directory">
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html#a1a0b6c779c2f5f2a41fdf39b63ddff08">_type_mutable</a></td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html">tvm::script::printer::DocNode</a></td><td class="entry"><span class="mlabel">static</span></td></tr>
- <tr class="odd"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#aa251921e11727010772291877807750a">args</a></td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">tvm::script::printer::OpCallDocNode</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#adbcf4a3aabbe1d82f73fc2d5f6154f6b">callee</a></td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">tvm::script::printer::OpCallDocNode</a></td><td class="entry"></td></tr>
- <tr class="odd"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html#a99434a755a816459b365afd7caf52b78">comment</a></td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html">tvm::script::printer::StmtDocNode</a></td><td class="entry"><span class="mlabel">mutable</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ab587d4e63b73fc2411792cba3517b5ae">config</a></td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">tvm::script::printer::OpCallDocNode</a></td><td class="entry"></td></tr>
- <tr class="odd"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#a9463aa1e349fdaa77ee00318eda01047">dispatch</a></td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">tvm::script::printer::OpCallDocNode</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#aa711d33587526cd7b6e3e8c9c005653b">RegisterReflection</a>()</td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">tvm::script::printer::OpCallDocNode</a></td><td class="entry"><span class="mlabel">inline</span><span class="mlabel">static</span></td></tr>
- <tr class="odd"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html#ac0eaa43901fa29108adaa7f51f09565a">source_paths</a></td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html">tvm::script::printer::DocNode</a></td><td class="entry"><span class="mlabel">mutable</span></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html#af0b37df58f9538165af7bd13f03ec7aa">TVM_FFI_DECLARE_OBJECT_INFO</a>("script.printer.StmtDoc", StmtDocNode, DocNode)</td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html">tvm::script::printer::StmtDocNode</a></td><td class="entry"></td></tr>
- <tr class="odd"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html#a63c0233ab2cc0b4e2d2dce9df5b5539f">tvm::script::printer::DocNode::TVM_FFI_DECLARE_OBJECT_INFO</a>("script.printer.Doc", DocNode, ffi::Object)</td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html">tvm::script::printer::DocNode</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#a37c9f827e2e422759bce6978c7b11fc3">TVM_FFI_DECLARE_OBJECT_INFO_FINAL</a>("script.printer.OpCallDoc", OpCallDocNode, StmtDocNode)</td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">tvm::script::printer::OpCallDocNode</a></td><td class="entry"></td></tr>
- <tr class="odd"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ac5eaf7f682b39836acebf055f7c843ed">workspace</a></td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">tvm::script::printer::OpCallDocNode</a></td><td class="entry"></td></tr>
- <tr class="even"><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html#a6202cee16104155937f3e64c703f6885">~DocNode</a>()=default</td><td class="entry"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html">tvm::script::printer::DocNode</a></td><td class="entry"><span class="mlabel">virtual</span></td></tr>
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diff --git a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1OpCallDocNode.html b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1OpCallDocNode.html
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-<div id="nav-path" class="navpath">
- <ul>
-<li class="navelem"><a class="el" href="namespacetvm.html">tvm</a></li><li class="navelem"><a class="el" href="namespacetvm_1_1script.html">script</a></li><li class="navelem"><a class="el" href="namespacetvm_1_1script_1_1printer.html">printer</a></li><li class="navelem"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">OpCallDocNode</a></li> </ul>
-</div>
-</div><!-- top -->
-<div class="header">
- <div class="summary">
-<a href="#pub-methods">Public Member Functions</a> |
-<a href="#pub-static-methods">Static Public Member Functions</a> |
-<a href="#pub-attribs">Public Attributes</a> |
-<a href="classtvm_1_1script_1_1printer_1_1OpCallDocNode-members.html">List of all members</a> </div>
- <div class="headertitle"><div class="title">tvm::script::printer::OpCallDocNode Class Reference</div></div>
-</div><!--header-->
-<div class="contents">
-
-<p><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents call to an TIRX operator.
- <a href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#details">More...</a></p>
-
-<p><code>#include <<a class="el" href="doc_8h_source.html">doc.h</a>></code></p>
-<div class="dynheader">
-Inheritance diagram for tvm::script::printer::OpCallDocNode:</div>
-<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1script_1_1printer_1_1OpCallDocNode__inherit__graph.svg" width="219" height="684"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
-</div>
-<div class="dynheader">
-Collaboration diagram for tvm::script::printer::OpCallDocNode:</div>
-<div class="dyncontent">
-<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1script_1_1printer_1_1OpCallDocNode__coll__graph.svg" width="491" height="722"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
-</div>
-<table class="memberdecls">
-<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="pub-methods" name="pub-methods"></a>
-Public Member Functions</h2></td></tr>
-<tr class="memitem:a37c9f827e2e422759bce6978c7b11fc3" id="r_a37c9f827e2e422759bce6978c7b11fc3"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#a37c9f827e2e422759bce6978c7b11fc3">TVM_FFI_DECLARE_OBJECT_INFO_FINAL</a> ("script.printer.OpCallDoc", <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">OpCallDocNode</a>, <a class="el" href [...]
-<tr class="separator:a37c9f827e2e422759bce6978c7b11fc3"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="inherit_header pub_methods_classtvm_1_1script_1_1printer_1_1StmtDocNode"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classtvm_1_1script_1_1printer_1_1StmtDocNode')"><img src="closed.png" alt="-"/> Public Member Functions inherited from <a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html">tvm::script::printer::StmtDocNode</a></td></tr>
-<tr class="memitem:af0b37df58f9538165af7bd13f03ec7aa inherit pub_methods_classtvm_1_1script_1_1printer_1_1StmtDocNode" id="r_af0b37df58f9538165af7bd13f03ec7aa"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html#af0b37df58f9538165af7bd13f03ec7aa">TVM_FFI_DECLARE_OBJECT_INFO</a> ("script.printer.StmtDoc", <a class="el" href="classtvm_1_1script_1_1printer_1_1St [...]
-<tr class="separator:af0b37df58f9538165af7bd13f03ec7aa inherit pub_methods_classtvm_1_1script_1_1printer_1_1StmtDocNode"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="inherit_header pub_methods_classtvm_1_1script_1_1printer_1_1DocNode"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classtvm_1_1script_1_1printer_1_1DocNode')"><img src="closed.png" alt="-"/> Public Member Functions inherited from <a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html">tvm::script::printer::DocNode</a></td></tr>
-<tr class="memitem:a63c0233ab2cc0b4e2d2dce9df5b5539f inherit pub_methods_classtvm_1_1script_1_1printer_1_1DocNode" id="r_a63c0233ab2cc0b4e2d2dce9df5b5539f"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html#a63c0233ab2cc0b4e2d2dce9df5b5539f">TVM_FFI_DECLARE_OBJECT_INFO</a> ("script.printer.Doc", <a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html"> [...]
-<tr class="separator:a63c0233ab2cc0b4e2d2dce9df5b5539f inherit pub_methods_classtvm_1_1script_1_1printer_1_1DocNode"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="memitem:a6202cee16104155937f3e64c703f6885 inherit pub_methods_classtvm_1_1script_1_1printer_1_1DocNode" id="r_a6202cee16104155937f3e64c703f6885"><td class="memItemLeft" align="right" valign="top">virtual </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html#a6202cee16104155937f3e64c703f6885">~DocNode</a> ()=default</td></tr>
-<tr class="separator:a6202cee16104155937f3e64c703f6885 inherit pub_methods_classtvm_1_1script_1_1printer_1_1DocNode"><td class="memSeparator" colspan="2"> </td></tr>
-</table><table class="memberdecls">
-<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="pub-static-methods" name="pub-static-methods"></a>
-Static Public Member Functions</h2></td></tr>
-<tr class="memitem:aa711d33587526cd7b6e3e8c9c005653b" id="r_aa711d33587526cd7b6e3e8c9c005653b"><td class="memItemLeft" align="right" valign="top">static void </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#aa711d33587526cd7b6e3e8c9c005653b">RegisterReflection</a> ()</td></tr>
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-<tr class="inherit_header pub_static_methods_classtvm_1_1script_1_1printer_1_1StmtDocNode"><td colspan="2" onclick="javascript:toggleInherit('pub_static_methods_classtvm_1_1script_1_1printer_1_1StmtDocNode')"><img src="closed.png" alt="-"/> Static Public Member Functions inherited from <a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html">tvm::script::printer::StmtDocNode</a></td></tr>
-<tr class="memitem:aefcf9256e4c4157c7680a95d00e997b9 inherit pub_static_methods_classtvm_1_1script_1_1printer_1_1StmtDocNode" id="r_aefcf9256e4c4157c7680a95d00e997b9"><td class="memItemLeft" align="right" valign="top">static void </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html#aefcf9256e4c4157c7680a95d00e997b9">RegisterReflection</a> ()</td></tr>
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-<tr class="inherit_header pub_static_methods_classtvm_1_1script_1_1printer_1_1DocNode"><td colspan="2" onclick="javascript:toggleInherit('pub_static_methods_classtvm_1_1script_1_1printer_1_1DocNode')"><img src="closed.png" alt="-"/> Static Public Member Functions inherited from <a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html">tvm::script::printer::DocNode</a></td></tr>
-<tr class="memitem:aa1b21cca3298ed25ceef541db2f39f86 inherit pub_static_methods_classtvm_1_1script_1_1printer_1_1DocNode" id="r_aa1b21cca3298ed25ceef541db2f39f86"><td class="memItemLeft" align="right" valign="top">static void </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html#aa1b21cca3298ed25ceef541db2f39f86">RegisterReflection</a> ()</td></tr>
-<tr class="separator:aa1b21cca3298ed25ceef541db2f39f86 inherit pub_static_methods_classtvm_1_1script_1_1printer_1_1DocNode"><td class="memSeparator" colspan="2"> </td></tr>
-</table><table class="memberdecls">
-<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="pub-attribs" name="pub-attribs"></a>
-Public Attributes</h2></td></tr>
-<tr class="memitem:adbcf4a3aabbe1d82f73fc2d5f6154f6b" id="r_adbcf4a3aabbe1d82f73fc2d5f6154f6b"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtvm_1_1script_1_1printer_1_1ExprDoc.html">ExprDoc</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#adbcf4a3aabbe1d82f73fc2d5f6154f6b">callee</a> {ffi::UnsafeInit()}</td></tr>
-<tr class="memdesc:adbcf4a3aabbe1d82f73fc2d5f6154f6b"><td class="mdescLeft"> </td><td class="mdescRight">The callee of this function call. <br /></td></tr>
-<tr class="separator:adbcf4a3aabbe1d82f73fc2d5f6154f6b"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="memitem:aa251921e11727010772291877807750a" id="r_aa251921e11727010772291877807750a"><td class="memItemLeft" align="right" valign="top">ffi::Array< <a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html">Doc</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#aa251921e11727010772291877807750a">args</a></td></tr>
-<tr class="memdesc:aa251921e11727010772291877807750a"><td class="mdescLeft"> </td><td class="mdescRight">The positional arguments. <br /></td></tr>
-<tr class="separator:aa251921e11727010772291877807750a"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="memitem:ac5eaf7f682b39836acebf055f7c843ed" id="r_ac5eaf7f682b39836acebf055f7c843ed"><td class="memItemLeft" align="right" valign="top">ffi::Optional< <a class="el" href="classtvm_1_1script_1_1printer_1_1DictDoc.html">DictDoc</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ac5eaf7f682b39836acebf055f7c843ed">workspace</a> {std::nullopt}</td></tr>
-<tr class="memdesc:ac5eaf7f682b39836acebf055f7c843ed"><td class="mdescLeft"> </td><td class="mdescRight">The workspace of this op call. <br /></td></tr>
-<tr class="separator:ac5eaf7f682b39836acebf055f7c843ed"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="memitem:ab587d4e63b73fc2411792cba3517b5ae" id="r_ab587d4e63b73fc2411792cba3517b5ae"><td class="memItemLeft" align="right" valign="top">ffi::Optional< <a class="el" href="classtvm_1_1script_1_1printer_1_1DictDoc.html">DictDoc</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ab587d4e63b73fc2411792cba3517b5ae">config</a> {std::nullopt}</td></tr>
-<tr class="memdesc:ab587d4e63b73fc2411792cba3517b5ae"><td class="mdescLeft"> </td><td class="mdescRight">The config of this op call. <br /></td></tr>
-<tr class="separator:ab587d4e63b73fc2411792cba3517b5ae"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="memitem:a9463aa1e349fdaa77ee00318eda01047" id="r_a9463aa1e349fdaa77ee00318eda01047"><td class="memItemLeft" align="right" valign="top">ffi::Optional< <a class="el" href="classtvm_1_1script_1_1printer_1_1ExprDoc.html">ExprDoc</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#a9463aa1e349fdaa77ee00318eda01047">dispatch</a> {std::nullopt}</td></tr>
-<tr class="memdesc:a9463aa1e349fdaa77ee00318eda01047"><td class="mdescLeft"> </td><td class="mdescRight">The optional dispatch variant of this op call. <br /></td></tr>
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-<tr class="inherit_header pub_attribs_classtvm_1_1script_1_1printer_1_1StmtDocNode"><td colspan="2" onclick="javascript:toggleInherit('pub_attribs_classtvm_1_1script_1_1printer_1_1StmtDocNode')"><img src="closed.png" alt="-"/> Public Attributes inherited from <a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html">tvm::script::printer::StmtDocNode</a></td></tr>
-<tr class="memitem:a99434a755a816459b365afd7caf52b78 inherit pub_attribs_classtvm_1_1script_1_1printer_1_1StmtDocNode" id="r_a99434a755a816459b365afd7caf52b78"><td class="memItemLeft" align="right" valign="top">ffi::Optional< ffi::String > </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html#a99434a755a816459b365afd7caf52b78">comment</a> {std::nullopt}</td></tr>
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-<tr class="memitem:ac0eaa43901fa29108adaa7f51f09565a inherit pub_attribs_classtvm_1_1script_1_1printer_1_1DocNode" id="r_ac0eaa43901fa29108adaa7f51f09565a"><td class="memItemLeft" align="right" valign="top">ffi::Array< <a class="el" href="namespacetvm_1_1script_1_1printer.html#aecb78d3edd725763c5f4dca6c3b1822c">AccessPath</a> > </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html#ac0eaa43901fa29108adaa7f51f09565a">sour [...]
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-</table><table class="memberdecls">
-<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="inherited" name="inherited"></a>
-Additional Inherited Members</h2></td></tr>
-<tr class="inherit_header pub_static_attribs_classtvm_1_1script_1_1printer_1_1DocNode"><td colspan="2" onclick="javascript:toggleInherit('pub_static_attribs_classtvm_1_1script_1_1printer_1_1DocNode')"><img src="closed.png" alt="-"/> Static Public Attributes inherited from <a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html">tvm::script::printer::DocNode</a></td></tr>
-<tr class="memitem:a1a0b6c779c2f5f2a41fdf39b63ddff08 inherit pub_static_attribs_classtvm_1_1script_1_1printer_1_1DocNode" id="r_a1a0b6c779c2f5f2a41fdf39b63ddff08"><td class="memItemLeft" align="right" valign="top">static constexpr bool </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocNode.html#a1a0b6c779c2f5f2a41fdf39b63ddff08">_type_mutable</a> = true</td></tr>
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-<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
-<div class="textblock"><p><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents call to an TIRX operator. </p>
-<dl class="section see"><dt>See also</dt><dd><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html" title="Reference type of OpCallDocNode.">OpCallDoc</a> </dd></dl>
-</div><h2 class="groupheader">Member Function Documentation</h2>
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-<h2 class="memtitle"><span class="permalink"><a href="#aa711d33587526cd7b6e3e8c9c005653b">◆ </a></span>RegisterReflection()</h2>
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- <td>(</td>
- <td class="paramname"></td><td>)</td>
- <td></td>
- </tr>
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- <td class="mlabels-right">
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-<h2 class="memtitle"><span class="permalink"><a href="#a37c9f827e2e422759bce6978c7b11fc3">◆ </a></span>TVM_FFI_DECLARE_OBJECT_INFO_FINAL()</h2>
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- <td class="paramname">, </td>
- </tr>
- <tr>
- <td class="paramkey"></td>
- <td></td>
- <td class="paramtype"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">OpCallDocNode</a> </td>
- <td class="paramname">, </td>
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- <tr>
- <td class="paramkey"></td>
- <td></td>
- <td class="paramtype"><a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html">StmtDocNode</a> </td>
- <td class="paramname"> </td>
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- <td>)</td>
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-
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-<h2 class="groupheader">Member Data Documentation</h2>
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-<h2 class="memtitle"><span class="permalink"><a href="#aa251921e11727010772291877807750a">◆ </a></span>args</h2>
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-<p>The positional arguments. </p>
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-<h2 class="memtitle"><span class="permalink"><a href="#adbcf4a3aabbe1d82f73fc2d5f6154f6b">◆ </a></span>callee</h2>
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-<p>The config of this op call. </p>
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-<p>The optional dispatch variant of this op call. </p>
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-<p>The workspace of this op call. </p>
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diff --git a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1StmtDoc.html b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1StmtDoc.html
index 2dbf850b9c2..7ca50dcc689 100644
--- a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1StmtDoc.html
+++ b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1StmtDoc.html
@@ -88,7 +88,7 @@ $(function() {
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+<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1script_1_1printer_1_1StmtDoc__inherit__graph.svg" width="3776" height="590"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
</div>
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Collaboration diagram for tvm::script::printer::StmtDoc:</div>
diff --git a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1StmtDocNode.html b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1StmtDocNode.html
index 777f173ba62..fea99c1d8ec 100644
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+++ b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1StmtDocNode.html
@@ -89,7 +89,7 @@ $(function() {
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+<div class="center"><iframe scrolling="no" frameborder="0" src="classtvm_1_1script_1_1printer_1_1StmtDocNode__inherit__graph.svg" width="3235" height="704"><p><b>This browser is not able to show SVG: try Firefox, Chrome, Safari, or Opera instead.</b></p></iframe></div>
</div>
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Collaboration diagram for tvm::script::printer::StmtDocNode:</div>
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index 14232b73579..532a5eb408b 100644
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@@ -56,8 +56,8 @@
<g id="edge3_Node000001_Node000004" class="edge">
<title>Node1->Node4</title>
<g id="a_edge3_Node000001_Node000004"><a xlink:title=" ">
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+<polygon fill="none" stroke="#63b8ff" points="1120.97,-243.24 1130.96,-239.7 1120.95,-236.24 1120.97,-243.24"/>
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@@ -90,8 +90,8 @@
<g id="edge4_Node000001_Node000005" class="edge">
<title>Node1->Node5</title>
<g id="a_edge4_Node000001_Node000005"><a xlink:title=" ">
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-<polygon fill="none" stroke="#63b8ff" points="1207.65,-242.53 1217.67,-239.08 1207.68,-235.53 1207.65,-242.53"/>
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@@ -118,8 +118,8 @@
<g id="edge5_Node000001_Node000006" class="edge">
<title>Node1->Node6</title>
<g id="a_edge5_Node000001_Node000006"><a xlink:title=" ">
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-<polygon fill="none" stroke="#63b8ff" points="1207.81,-240.66 1217.9,-237.43 1207.99,-233.67 1207.81,-240.66"/>
+<path fill="none" stroke="#63b8ff" d="M1120.27,-235.86C957.77,-229 619.31,-209.24 513,-161 494,-152.38 476.32,-138 461.94,-123.83"/>
+<polygon fill="none" stroke="#63b8ff" points="1120.57,-239.38 1130.71,-236.29 1120.86,-232.38 1120.57,-239.38"/>
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@@ -152,8 +152,8 @@
<g id="edge6_Node000001_Node000007" class="edge">
<title>Node1->Node7</title>
<g id="a_edge6_Node000001_Node000007"><a xlink:title=" ">
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-<polygon fill="none" stroke="#63b8ff" points="1207.78,-237.75 1217.97,-234.86 1208.2,-230.76 1207.78,-237.75"/>
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@@ -180,8 +180,8 @@
<g id="edge7_Node000001_Node000008" class="edge">
<title>Node1->Node8</title>
<g id="a_edge7_Node000001_Node000008"><a xlink:title=" ">
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<g id="edge8_Node000001_Node000009" class="edge">
<title>Node1->Node9</title>
<g id="a_edge8_Node000001_Node000009"><a xlink:title=" ">
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<g id="edge9_Node000001_Node000010" class="edge">
<title>Node1->Node10</title>
<g id="a_edge9_Node000001_Node000010"><a xlink:title=" ">
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+<path fill="none" stroke="#63b8ff" d="M1180.71,-187.78C1169.23,-167 1156.13,-143.29 1145.23,-123.55"/>
+<polygon fill="none" stroke="#63b8ff" points="1177.79,-189.73 1185.69,-196.79 1183.91,-186.35 1177.79,-189.73"/>
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<g id="edge10_Node000001_Node000011" class="edge">
<title>Node1->Node11</title>
<g id="a_edge10_Node000001_Node000011"><a xlink:title=" ">
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-<polygon fill="none" stroke="#63b8ff" points="1292.5,-186.79 1296,-196.79 1299.5,-186.79 1292.5,-186.79"/>
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+<polygon fill="none" stroke="#63b8ff" points="1234.09,-186.35 1232.31,-196.79 1240.21,-189.73 1234.09,-186.35"/>
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<g id="edge11_Node000001_Node000012" class="edge">
<title>Node1->Node12</title>
<g id="a_edge11_Node000001_Node000012"><a xlink:title=" ">
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<g id="edge12_Node000001_Node000013" class="edge">
<title>Node1->Node13</title>
<g id="a_edge12_Node000001_Node000013"><a xlink:title=" ">
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@@ -374,37 +374,29 @@
<g id="edge13_Node000001_Node000014" class="edge">
<title>Node1->Node14</title>
<g id="a_edge13_Node000001_Node000014"><a xlink:title=" ">
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-<polygon fill="none" stroke="#63b8ff" points="1384.12,-233.92 1374.3,-237.91 1384.46,-240.91 1384.12,-233.92"/>
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<g id="Node000015" class="node">
<title>Node15</title>
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-<text text-anchor="start" x="1918" y="-100.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
-<text text-anchor="start" x="1931" y="-100.5" font-family="Helvetica,sans-Serif" font-size="10.00">args</text>
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+<polygon fill="white" stroke="transparent" points="2070,-123.5 1914,-123.5 1914,-37.5 2070,-37.5 2070,-123.5"/>
+<text text-anchor="start" x="1946.5" y="-111.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
+<text text-anchor="start" x="1950.5" y="-100.5" font-family="Helvetica,sans-Serif" font-size="10.00">::ReturnDocNode</text>
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+<text text-anchor="start" x="1931" y="-85.5" font-family="Helvetica,sans-Serif" font-size="10.00">value</text>
<text text-anchor="start" x="1918" y="-70.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
-<text text-anchor="start" x="1931" y="-70.5" font-family="Helvetica,sans-Serif" font-size="10.00">config</text>
-<text text-anchor="start" x="1918" y="-55.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
-<text text-anchor="start" x="1931" y="-55.5" font-family="Helvetica,sans-Serif" font-size="10.00">dispatch</text>
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-<text text-anchor="start" x="1931" y="-14.5" font-family="Helvetica,sans-Serif" font-size="10.00">RegisterReflection()</text>
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+<text text-anchor="start" x="1931" y="-70.5" font-family="Helvetica,sans-Serif" font-size="10.00">TVM_FFI_DECLARE_OBJECT</text>
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+<text text-anchor="start" x="1931" y="-44.5" font-family="Helvetica,sans-Serif" font-size="10.00">RegisterReflection()</text>
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+<polygon fill="#666666" stroke="#666666" points="1914,-80.5 1914,-80.5 1929,-80.5 1929,-80.5 1914,-80.5"/>
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<g id="edge14_Node000001_Node000015" class="edge">
<title>Node1->Node15</title>
<g id="a_edge14_Node000001_Node000015"><a xlink:title=" ">
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<g id="Node000016" class="node">
<title>Node16</title>
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+<g id="a_Node000016"><a xlink:href="classtvm_1_1script_1_1printer_1_1ScopeDocNode.html" target="_top" xlink:title="Doc that represents special scopes.">
+<polygon fill="white" stroke="transparent" points="2244,-146 2088,-146 2088,-15 2244,-15 2244,-146"/>
+<text text-anchor="start" x="2120.5" y="-133.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
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+<text text-anchor="start" x="2105" y="-107.5" font-family="Helvetica,sans-Serif" font-size="10.00">lhs</text>
+<text text-anchor="start" x="2092" y="-92.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="2105" y="-92.5" font-family="Helvetica,sans-Serif" font-size="10.00">rhs</text>
+<text text-anchor="start" x="2092" y="-77.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="2105" y="-77.5" font-family="Helvetica,sans-Serif" font-size="10.00">body</text>
+<text text-anchor="start" x="2092" y="-62.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="2105" y="-62.5" font-family="Helvetica,sans-Serif" font-size="10.00">allow_concise_scoping</text>
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+<text text-anchor="start" x="2105" y="-21.5" font-family="Helvetica,sans-Serif" font-size="10.00">RegisterReflection()</text>
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<g id="a_edge15_Node000001_Node000016"><a xlink:title=" ">
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<g id="Node000017" class="node">
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<title>Node1->Node17</title>
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<g id="Node000002" class="node">
<title>Node2</title>
<g id="a_Node000002"><a xlink:href="classtvm_1_1script_1_1printer_1_1DocNode.html" target="_top" xlink:title="The base class of all Doc.">
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+<text text-anchor="start" x="1163.5" y="-423" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
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+<text text-anchor="start" x="1135" y="-397" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="1148" y="-397" font-family="Helvetica,sans-Serif" font-size="10.00">source_paths</text>
+<text text-anchor="start" x="1135" y="-382" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="1148" y="-382" font-family="Helvetica,sans-Serif" font-size="10.00">_type_mutable</text>
+<text text-anchor="start" x="1135" y="-367" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="1148" y="-367" font-family="Helvetica,sans-Serif" font-size="10.00">TVM_FFI_DECLARE_OBJECT</text>
+<text text-anchor="start" x="1148" y="-356" font-family="Helvetica,sans-Serif" font-size="10.00">_INFO()</text>
+<text text-anchor="start" x="1135" y="-341" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="1148" y="-341" font-family="Helvetica,sans-Serif" font-size="10.00">~DocNode()</text>
+<text text-anchor="start" x="1135" y="-326" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="1148" y="-326" font-family="Helvetica,sans-Serif" font-size="10.00">RegisterReflection()</text>
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+<polygon fill="#666666" stroke="#666666" points="1131,-377 1131,-377 1146,-377 1146,-377 1131,-377"/>
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@@ -544,8 +506,8 @@
<g id="edge1_Node000001_Node000002" class="edge">
<title>Node2->Node1</title>
<g id="a_edge1_Node000001_Node000002"><a xlink:title=" ">
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-<polygon fill="none" stroke="#63b8ff" points="1292.5,-308.75 1296,-318.75 1299.5,-308.75 1292.5,-308.75"/>
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+<polygon fill="none" stroke="#63b8ff" points="1205.5,-308.75 1209,-318.75 1212.5,-308.75 1205.5,-308.75"/>
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<g id="Node000003" class="node">
<title>Node3</title>
<g id="a_Node000003"><a xlink:title=" ">
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-<text text-anchor="start" x="1272" y="-507.5" font-family="Helvetica,sans-Serif" font-size="10.00">ffi::Object</text>
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-<polygon fill="none" stroke="#666666" points="1267,-471 1267,-520 1325,-520 1325,-471 1267,-471"/>
+<polygon fill="white" stroke="transparent" points="1238,-520 1180,-520 1180,-471 1238,-471 1238,-520"/>
+<text text-anchor="start" x="1185" y="-507.5" font-family="Helvetica,sans-Serif" font-size="10.00">ffi::Object</text>
+<text text-anchor="start" x="1207" y="-492.5" font-family="Helvetica,sans-Serif" font-size="10.00"> </text>
+<text text-anchor="start" x="1207" y="-477.5" font-family="Helvetica,sans-Serif" font-size="10.00"> </text>
+<polygon fill="#666666" stroke="#666666" points="1180,-502.5 1180,-502.5 1238,-502.5 1238,-502.5 1180,-502.5"/>
+<polygon fill="#666666" stroke="#666666" points="1180,-487.5 1180,-487.5 1238,-487.5 1238,-487.5 1180,-487.5"/>
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@@ -567,8 +529,8 @@
<g id="edge2_Node000002_Node000003" class="edge">
<title>Node3->Node2</title>
<g id="a_edge2_Node000002_Node000003"><a xlink:title=" ">
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-<polygon fill="none" stroke="#63b8ff" points="1292.5,-460.92 1296,-470.92 1299.5,-460.92 1292.5,-460.92"/>
+<path fill="none" stroke="#63b8ff" d="M1209,-460.87C1209,-452.83 1209,-444.03 1209,-435.26"/>
+<polygon fill="none" stroke="#63b8ff" points="1205.5,-460.92 1209,-470.92 1212.5,-460.92 1205.5,-460.92"/>
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diff --git a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1StmtDoc__inherit__graph.svg b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1StmtDoc__inherit__graph.svg
index 66dcedac74e..63e0f75a56a 100644
--- a/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1StmtDoc__inherit__graph.svg
+++ b/docs/reference/api/doxygen/classtvm_1_1script_1_1printer_1_1StmtDoc__inherit__graph.svg
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- viewBox="0.00 0.00 3035.00 442.00" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
+<svg width="2832pt" height="442pt"
+ viewBox="0.00 0.00 2832.00 442.00" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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<title>tvm::script::printer::StmtDoc</title>
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<g id="Node000001" class="node">
<title>Node1</title>
<g id="a_Node000001"><a xlink:title="Reference type of StmtDocNode.">
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+<polygon fill="#999999" stroke="transparent" points="1504,-223 1319,-223 1319,-137 1504,-137 1504,-223"/>
+<text text-anchor="start" x="1366.5" y="-211" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
+<text text-anchor="start" x="1387.5" y="-200" font-family="Helvetica,sans-Serif" font-size="10.00">::StmtDoc</text>
+<text text-anchor="start" x="1410" y="-185" font-family="Helvetica,sans-Serif" font-size="10.00"> </text>
+<text text-anchor="start" x="1323.5" y="-170" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="1336.5" y="-170" font-family="Helvetica,sans-Serif" font-size="10.00">TVM_FFI_DEFINE_OBJECT</text>
+<text text-anchor="start" x="1336.5" y="-159" font-family="Helvetica,sans-Serif" font-size="10.00">_REF_METHODS_NOTNULLABLE()</text>
+<text text-anchor="start" x="1323.5" y="-144" font-family="Helvetica,sans-Serif" font-size="10.00">#</text>
+<text text-anchor="start" x="1336.5" y="-144" font-family="Helvetica,sans-Serif" font-size="10.00">StmtDoc()</text>
+<polygon fill="#666666" stroke="#666666" points="1319.5,-195 1319.5,-195 1504.5,-195 1504.5,-195 1319.5,-195"/>
+<polygon fill="#666666" stroke="#666666" points="1319.5,-180 1319.5,-180 1504.5,-180 1504.5,-180 1319.5,-180"/>
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<title>Node1->Node4</title>
<g id="a_edge3_Node000001_Node000004"><a xlink:title=" ">
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<g id="edge4_Node000001_Node000005" class="edge">
<title>Node1->Node5</title>
<g id="a_edge4_Node000001_Node000005"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M1410.58,-176.86C1171.8,-171.07 586.08,-151.98 396.5,-101 389.05,-99 381.5,-96.43 374.05,-93.53"/>
-<polygon fill="none" stroke="#63b8ff" points="1410.57,-180.36 1420.65,-177.1 1410.74,-173.36 1410.57,-180.36"/>
+<path fill="none" stroke="#63b8ff" d="M1308.81,-176.02C1086.36,-168.77 566.32,-147.3 396.5,-101 389.15,-99 381.7,-96.45 374.34,-93.59"/>
+<polygon fill="none" stroke="#63b8ff" points="1308.75,-179.52 1318.86,-176.35 1308.98,-172.53 1308.75,-179.52"/>
</a>
</g>
</g>
@@ -106,8 +106,8 @@
<g id="edge5_Node000001_Node000006" class="edge">
<title>Node1->Node6</title>
<g id="a_edge5_Node000001_Node000006"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M1410.63,-175C1204.93,-166.22 749.76,-142.65 599.5,-101 592.16,-98.97 584.71,-96.4 577.36,-93.52"/>
-<polygon fill="none" stroke="#63b8ff" points="1410.69,-178.51 1420.83,-175.43 1410.99,-171.51 1410.69,-178.51"/>
+<path fill="none" stroke="#63b8ff" d="M1308.7,-173.73C1121.03,-163.34 730.22,-137.98 599.5,-101 592.27,-98.95 584.92,-96.4 577.67,-93.55"/>
+<polygon fill="none" stroke="#63b8ff" points="1308.67,-177.23 1318.85,-174.29 1309.06,-170.24 1308.67,-177.23"/>
</a>
</g>
</g>
@@ -134,8 +134,8 @@
<g id="edge6_Node000001_Node000007" class="edge">
<title>Node1->Node7</title>
<g id="a_edge6_Node000001_Node000007"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M1410.6,-178.77C1270.37,-175.98 1012.65,-161.99 802.5,-101 795.37,-98.93 788.14,-96.39 780.98,-93.55"/>
-<polygon fill="none" stroke="#63b8ff" points="1410.84,-182.27 1420.91,-178.96 1410.97,-175.27 1410.84,-182.27"/>
+<path fill="none" stroke="#63b8ff" d="M1308.61,-176.06C1185.78,-170.24 975.29,-152.85 802.5,-101 795.49,-98.9 788.36,-96.34 781.3,-93.52"/>
+<polygon fill="none" stroke="#63b8ff" points="1308.61,-179.57 1318.76,-176.53 1308.93,-172.57 1308.61,-179.57"/>
</a>
</g>
</g>
@@ -162,8 +162,8 @@
<g id="edge7_Node000001_Node000008" class="edge">
<title>Node1->Node8</title>
<g id="a_edge7_Node000001_Node000008"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M1410.56,-172.38C1306.44,-163.56 1141.86,-143.78 1005.5,-101 998.7,-98.87 991.78,-96.33 984.93,-93.56"/>
-<polygon fill="none" stroke="#63b8ff" points="1410.5,-175.89 1420.75,-173.22 1411.08,-168.91 1410.5,-175.89"/>
+<path fill="none" stroke="#63b8ff" d="M1308.64,-166.94C1225.39,-155.36 1105.9,-134.58 1005.5,-101 998.93,-98.8 992.23,-96.26 985.58,-93.51"/>
+<polygon fill="none" stroke="#63b8ff" points="1308.23,-170.42 1318.61,-168.31 1309.18,-163.48 1308.23,-170.42"/>
</a>
</g>
</g>
@@ -190,8 +190,8 @@
<g id="edge8_Node000001_Node000009" class="edge">
<title>Node1->Node9</title>
<g id="a_edge8_Node000001_Node000009"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M1411.06,-158.33C1351.1,-144.87 1274.45,-125.3 1208.5,-101 1202.36,-98.74 1196.1,-96.22 1189.85,-93.55"/>
-<polygon fill="none" stroke="#63b8ff" points="1410.39,-161.76 1420.92,-160.52 1411.91,-154.93 1410.39,-161.76"/>
+<path fill="none" stroke="#63b8ff" d="M1309.33,-141.77C1276.85,-129.4 1240.94,-115.15 1208.5,-101 1203.04,-98.62 1197.45,-96.1 1191.83,-93.52"/>
+<polygon fill="none" stroke="#63b8ff" points="1308.25,-145.1 1318.84,-145.38 1310.73,-138.56 1308.25,-145.1"/>
</a>
</g>
</g>
@@ -218,8 +218,8 @@
<g id="edge9_Node000001_Node000010" class="edge">
<title>Node1->Node10</title>
<g id="a_edge9_Node000001_Node000010"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M1437.78,-131.44C1417.98,-119 1396.77,-105.69 1377.46,-93.56"/>
-<polygon fill="none" stroke="#63b8ff" points="1436.14,-134.54 1446.47,-136.9 1439.86,-128.62 1436.14,-134.54"/>
+<path fill="none" stroke="#63b8ff" d="M1371.83,-128.92C1362.56,-117.22 1352.78,-104.87 1343.82,-93.56"/>
+<polygon fill="none" stroke="#63b8ff" points="1369.2,-131.23 1378.15,-136.9 1374.68,-126.89 1369.2,-131.23"/>
</a>
</g>
</g>
@@ -246,8 +246,8 @@
<g id="edge10_Node000001_Node000011" class="edge">
<title>Node1->Node11</title>
<g id="a_edge10_Node000001_Node000011"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M1513.5,-126.89C1513.5,-115.8 1513.5,-104.22 1513.5,-93.56"/>
-<polygon fill="none" stroke="#63b8ff" points="1510,-126.9 1513.5,-136.9 1517,-126.9 1510,-126.9"/>
+<path fill="none" stroke="#63b8ff" d="M1451.56,-128.92C1460.93,-117.22 1470.8,-104.87 1479.85,-93.56"/>
+<polygon fill="none" stroke="#63b8ff" points="1448.7,-126.9 1445.18,-136.9 1454.16,-131.28 1448.7,-126.9"/>
</a>
</g>
</g>
@@ -274,8 +274,8 @@
<g id="edge11_Node000001_Node000012" class="edge">
<title>Node1->Node12</title>
<g id="a_edge11_Node000001_Node000012"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M1589.22,-131.44C1609.02,-119 1630.23,-105.69 1649.54,-93.56"/>
-<polygon fill="none" stroke="#63b8ff" points="1587.14,-128.62 1580.53,-136.9 1590.86,-134.54 1587.14,-128.62"/>
+<path fill="none" stroke="#63b8ff" d="M1513.71,-141.99C1546.48,-129.58 1582.75,-115.25 1615.5,-101 1620.96,-98.62 1626.55,-96.11 1632.17,-93.53"/>
+<polygon fill="none" stroke="#63b8ff" points="1512.24,-138.81 1504.12,-145.61 1514.71,-145.36 1512.24,-138.81"/>
</a>
</g>
</g>
@@ -302,8 +302,8 @@
<g id="edge12_Node000001_Node000013" class="edge">
<title>Node1->Node13</title>
<g id="a_edge12_Node000001_Node000013"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M1615.94,-158.33C1675.9,-144.87 1752.55,-125.3 1818.5,-101 1824.64,-98.74 1830.9,-96.22 1837.15,-93.55"/>
-<polygon fill="none" stroke="#63b8ff" points="1615.09,-154.93 1606.08,-160.52 1616.61,-161.76 1615.09,-154.93"/>
+<path fill="none" stroke="#63b8ff" d="M1514.2,-167.03C1597.67,-155.47 1717.69,-134.69 1818.5,-101 1825.07,-98.8 1831.77,-96.26 1838.42,-93.52"/>
+<polygon fill="none" stroke="#63b8ff" points="1513.65,-163.57 1504.21,-168.39 1514.59,-170.51 1513.65,-163.57"/>
</a>
</g>
</g>
@@ -330,21 +330,21 @@
<g id="edge13_Node000001_Node000014" class="edge">
<title>Node1->Node14</title>
<g id="a_edge13_Node000001_Node000014"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M1616.44,-172.38C1720.56,-163.56 1885.14,-143.78 2021.5,-101 2028.3,-98.87 2035.22,-96.33 2042.07,-93.56"/>
-<polygon fill="none" stroke="#63b8ff" points="1615.92,-168.91 1606.25,-173.22 1616.5,-175.89 1615.92,-168.91"/>
+<path fill="none" stroke="#63b8ff" d="M1514.29,-176.1C1637.29,-170.31 1848.3,-152.96 2021.5,-101 2028.51,-98.9 2035.64,-96.35 2042.7,-93.53"/>
+<polygon fill="none" stroke="#63b8ff" points="1513.96,-172.61 1504.13,-176.56 1514.28,-179.6 1513.96,-172.61"/>
</a>
</g>
</g>
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<g id="Node000015" class="node">
<title>Node15</title>
-<g id="a_Node000015"><a xlink:href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html" target="_top" xlink:title="Reference type of OpCallDocNode.">
+<g id="a_Node000015"><a xlink:href="classtvm_1_1script_1_1printer_1_1ReturnDoc.html" target="_top" xlink:title="Reference type of ReturnDocNode.">
<polygon fill="white" stroke="transparent" points="2418,-93.5 2233,-93.5 2233,-7.5 2418,-7.5 2418,-93.5"/>
<text text-anchor="start" x="2280.5" y="-81.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
-<text text-anchor="start" x="2297" y="-70.5" font-family="Helvetica,sans-Serif" font-size="10.00">::OpCallDoc</text>
+<text text-anchor="start" x="2297" y="-70.5" font-family="Helvetica,sans-Serif" font-size="10.00">::ReturnDoc</text>
<text text-anchor="start" x="2324" y="-55.5" font-family="Helvetica,sans-Serif" font-size="10.00"> </text>
<text text-anchor="start" x="2237.5" y="-40.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
-<text text-anchor="start" x="2250.5" y="-40.5" font-family="Helvetica,sans-Serif" font-size="10.00">OpCallDoc()</text>
+<text text-anchor="start" x="2250.5" y="-40.5" font-family="Helvetica,sans-Serif" font-size="10.00">ReturnDoc()</text>
<text text-anchor="start" x="2237.5" y="-25.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
<text text-anchor="start" x="2250.5" y="-25.5" font-family="Helvetica,sans-Serif" font-size="10.00">TVM_FFI_DEFINE_OBJECT</text>
<text text-anchor="start" x="2250.5" y="-14.5" font-family="Helvetica,sans-Serif" font-size="10.00">_REF_METHODS_NOTNULLABLE()</text>
@@ -358,27 +358,29 @@
<g id="edge14_Node000001_Node000015" class="edge">
<title>Node1->Node15</title>
<g id="a_edge14_Node000001_Node000015"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M1616.4,-178.77C1756.63,-175.98 2014.35,-161.99 2224.5,-101 2231.63,-98.93 2238.86,-96.39 2246.02,-93.55"/>
-<polygon fill="none" stroke="#63b8ff" points="1616.03,-175.27 1606.09,-178.96 1616.16,-182.27 1616.03,-175.27"/>
+<path fill="none" stroke="#63b8ff" d="M1514.43,-173.73C1702.33,-163.36 2093.62,-138.02 2224.5,-101 2231.73,-98.95 2239.08,-96.4 2246.33,-93.55"/>
+<polygon fill="none" stroke="#63b8ff" points="1514.06,-170.25 1504.26,-174.29 1514.44,-177.24 1514.06,-170.25"/>
</a>
</g>
</g>
<!-- Node16 -->
<g id="Node000016" class="node">
<title>Node16</title>
-<g id="a_Node000016"><a xlink:href="classtvm_1_1script_1_1printer_1_1ReturnDoc.html" target="_top" xlink:title="Reference type of ReturnDocNode.">
-<polygon fill="white" stroke="transparent" points="2621,-93.5 2436,-93.5 2436,-7.5 2621,-7.5 2621,-93.5"/>
-<text text-anchor="start" x="2483.5" y="-81.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
-<text text-anchor="start" x="2500" y="-70.5" font-family="Helvetica,sans-Serif" font-size="10.00">::ReturnDoc</text>
-<text text-anchor="start" x="2527" y="-55.5" font-family="Helvetica,sans-Serif" font-size="10.00"> </text>
-<text text-anchor="start" x="2440.5" y="-40.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
-<text text-anchor="start" x="2453.5" y="-40.5" font-family="Helvetica,sans-Serif" font-size="10.00">ReturnDoc()</text>
-<text text-anchor="start" x="2440.5" y="-25.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
-<text text-anchor="start" x="2453.5" y="-25.5" font-family="Helvetica,sans-Serif" font-size="10.00">TVM_FFI_DEFINE_OBJECT</text>
-<text text-anchor="start" x="2453.5" y="-14.5" font-family="Helvetica,sans-Serif" font-size="10.00">_REF_METHODS_NOTNULLABLE()</text>
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-<polygon fill="#666666" stroke="#666666" points="2436.5,-50.5 2436.5,-50.5 2621.5,-50.5 2621.5,-50.5 2436.5,-50.5"/>
-<polygon fill="none" stroke="#666666" points="2436,-7.5 2436,-93.5 2621,-93.5 2621,-7.5 2436,-7.5"/>
+<g id="a_Node000016"><a xlink:href="classtvm_1_1script_1_1printer_1_1ScopeDoc.html" target="_top" xlink:title="Reference type of ScopeDocNode.">
+<polygon fill="white" stroke="transparent" points="2621,-101 2436,-101 2436,0 2621,0 2621,-101"/>
+<text text-anchor="start" x="2483.5" y="-88.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
+<text text-anchor="start" x="2501.5" y="-77.5" font-family="Helvetica,sans-Serif" font-size="10.00">::ScopeDoc</text>
+<text text-anchor="start" x="2527" y="-62.5" font-family="Helvetica,sans-Serif" font-size="10.00"> </text>
+<text text-anchor="start" x="2440.5" y="-47.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="2453.5" y="-47.5" font-family="Helvetica,sans-Serif" font-size="10.00">ScopeDoc()</text>
+<text text-anchor="start" x="2440.5" y="-32.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="2453.5" y="-32.5" font-family="Helvetica,sans-Serif" font-size="10.00">ScopeDoc()</text>
+<text text-anchor="start" x="2440.5" y="-17.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="2453.5" y="-17.5" font-family="Helvetica,sans-Serif" font-size="10.00">TVM_FFI_DEFINE_OBJECT</text>
+<text text-anchor="start" x="2453.5" y="-6.5" font-family="Helvetica,sans-Serif" font-size="10.00">_REF_METHODS_NOTNULLABLE()</text>
+<polygon fill="#666666" stroke="#666666" points="2436.5,-72.5 2436.5,-72.5 2621.5,-72.5 2621.5,-72.5 2436.5,-72.5"/>
+<polygon fill="#666666" stroke="#666666" points="2436.5,-57.5 2436.5,-57.5 2621.5,-57.5 2621.5,-57.5 2436.5,-57.5"/>
+<polygon fill="none" stroke="#666666" points="2436,0 2436,-101 2621,-101 2621,0 2436,0"/>
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</g>
</g>
@@ -386,29 +388,27 @@
<g id="edge15_Node000001_Node000016" class="edge">
<title>Node1->Node16</title>
<g id="a_edge15_Node000001_Node000016"><a xlink:title=" ">
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-<polygon fill="none" stroke="#63b8ff" points="1616.01,-171.51 1606.17,-175.43 1616.31,-178.51 1616.01,-171.51"/>
+<path fill="none" stroke="#63b8ff" d="M1514.29,-176.03C1736.96,-168.79 2257.51,-147.34 2427.5,-101 2430.23,-100.26 2432.98,-99.44 2435.73,-98.55"/>
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<g id="Node000017" class="node">
<title>Node17</title>
-<g id="a_Node000017"><a xlink:href="classtvm_1_1script_1_1printer_1_1ScopeDoc.html" target="_top" xlink:title="Reference type of ScopeDocNode.">
-<polygon fill="white" stroke="transparent" points="2824,-101 2639,-101 2639,0 2824,0 2824,-101"/>
-<text text-anchor="start" x="2686.5" y="-88.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
-<text text-anchor="start" x="2704.5" y="-77.5" font-family="Helvetica,sans-Serif" font-size="10.00">::ScopeDoc</text>
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-<text text-anchor="start" x="2643.5" y="-47.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
-<text text-anchor="start" x="2656.5" y="-47.5" font-family="Helvetica,sans-Serif" font-size="10.00">ScopeDoc()</text>
-<text text-anchor="start" x="2643.5" y="-32.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
-<text text-anchor="start" x="2656.5" y="-32.5" font-family="Helvetica,sans-Serif" font-size="10.00">ScopeDoc()</text>
-<text text-anchor="start" x="2643.5" y="-17.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
-<text text-anchor="start" x="2656.5" y="-17.5" font-family="Helvetica,sans-Serif" font-size="10.00">TVM_FFI_DEFINE_OBJECT</text>
-<text text-anchor="start" x="2656.5" y="-6.5" font-family="Helvetica,sans-Serif" font-size="10.00">_REF_METHODS_NOTNULLABLE()</text>
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-<polygon fill="#666666" stroke="#666666" points="2639.5,-57.5 2639.5,-57.5 2824.5,-57.5 2824.5,-57.5 2639.5,-57.5"/>
-<polygon fill="none" stroke="#666666" points="2639,0 2639,-101 2824,-101 2824,0 2639,0"/>
+<g id="a_Node000017"><a xlink:href="classtvm_1_1script_1_1printer_1_1WhileDoc.html" target="_top" xlink:title="Reference type of WhileDocNode.">
+<polygon fill="white" stroke="transparent" points="2824,-93.5 2639,-93.5 2639,-7.5 2824,-7.5 2824,-93.5"/>
+<text text-anchor="start" x="2686.5" y="-81.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
+<text text-anchor="start" x="2705.5" y="-70.5" font-family="Helvetica,sans-Serif" font-size="10.00">::WhileDoc</text>
+<text text-anchor="start" x="2730" y="-55.5" font-family="Helvetica,sans-Serif" font-size="10.00"> </text>
+<text text-anchor="start" x="2643.5" y="-40.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="2656.5" y="-40.5" font-family="Helvetica,sans-Serif" font-size="10.00">WhileDoc()</text>
+<text text-anchor="start" x="2643.5" y="-25.5" font-family="Helvetica,sans-Serif" font-size="10.00">+</text>
+<text text-anchor="start" x="2656.5" y="-25.5" font-family="Helvetica,sans-Serif" font-size="10.00">TVM_FFI_DEFINE_OBJECT</text>
+<text text-anchor="start" x="2656.5" y="-14.5" font-family="Helvetica,sans-Serif" font-size="10.00">_REF_METHODS_NOTNULLABLE()</text>
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+<polygon fill="#666666" stroke="#666666" points="2639.5,-50.5 2639.5,-50.5 2824.5,-50.5 2824.5,-50.5 2639.5,-50.5"/>
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@@ -416,36 +416,8 @@
<g id="edge16_Node000001_Node000017" class="edge">
<title>Node1->Node17</title>
<g id="a_edge16_Node000001_Node000017"><a xlink:title=" ">
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-<g id="Node000018" class="node">
-<title>Node18</title>
-<g id="a_Node000018"><a xlink:href="classtvm_1_1script_1_1printer_1_1WhileDoc.html" target="_top" xlink:title="Reference type of WhileDocNode.">
-<polygon fill="white" stroke="transparent" points="3027,-93.5 2842,-93.5 2842,-7.5 3027,-7.5 3027,-93.5"/>
-<text text-anchor="start" x="2889.5" y="-81.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
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</a>
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<g id="Node000002" class="node">
<title>Node2</title>
<g id="a_Node000002"><a xlink:href="classtvm_1_1script_1_1printer_1_1Doc.html" target="_top" xlink:title="Reference type of DocNode.">
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-<text text-anchor="start" x="1438.5" y="-296" font-family="Helvetica,sans-Serif" font-size="10.00">_REF_METHODS_NOTNULLABLE()</text>
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+<text text-anchor="start" x="1354" y="-337" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer::Doc</text>
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+<text text-anchor="start" x="1336.5" y="-296" font-family="Helvetica,sans-Serif" font-size="10.00">_REF_METHODS_NOTNULLABLE()</text>
+<text text-anchor="start" x="1323.5" y="-281" font-family="Helvetica,sans-Serif" font-size="10.00">#</text>
+<text text-anchor="start" x="1336.5" y="-281" font-family="Helvetica,sans-Serif" font-size="10.00">Doc()</text>
+<text text-anchor="start" x="1323.5" y="-266" font-family="Helvetica,sans-Serif" font-size="10.00">#</text>
+<text text-anchor="start" x="1336.5" y="-266" font-family="Helvetica,sans-Serif" font-size="10.00">Doc()</text>
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</a>
</g>
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@@ -473,8 +445,8 @@
<g id="edge1_Node000001_Node000002" class="edge">
<title>Node2->Node1</title>
<g id="a_edge1_Node000001_Node000002"><a xlink:title=" ">
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</a>
</g>
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@@ -482,13 +454,13 @@
<g id="Node000003" class="node">
<title>Node3</title>
<g id="a_Node000003"><a xlink:title=" ">
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-<text text-anchor="start" x="1481.5" y="-421.5" font-family="Helvetica,sans-Serif" font-size="10.00">ffi::ObjectRef</text>
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-<text text-anchor="start" x="1511.5" y="-391.5" font-family="Helvetica,sans-Serif" font-size="10.00"> </text>
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+<text text-anchor="start" x="1379.5" y="-421.5" font-family="Helvetica,sans-Serif" font-size="10.00">ffi::ObjectRef</text>
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</a>
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<g id="edge2_Node000002_Node000003" class="edge">
<title>Node3->Node2</title>
<g id="a_edge2_Node000002_Node000003"><a xlink:title=" ">
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diff --git a/docs/reference/api/doxygen/doc_8h.html b/docs/reference/api/doxygen/doc_8h.html
index 99c4520150c..9dfc2f5fdac 100644
--- a/docs/reference/api/doxygen/doc_8h.html
+++ b/docs/reference/api/doxygen/doc_8h.html
@@ -282,12 +282,6 @@ Classes</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class  </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1DocStringDoc.html">tvm::script::printer::DocStringDoc</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft"> </td><td class="mdescRight">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1DocStringDocNode.html" title="Doc that represents docstring.">DocStringDocNode</a>. <a href="classtvm_1_1script_1_1printer_1_1DocStringDoc.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class  </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">tvm::script::printer::OpCallDocNode</a></td></tr>
-<tr class="memdesc:"><td class="mdescLeft"> </td><td class="mdescRight"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents call to an TIRX operator. <a href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#details">More...</a><br /></td></tr>
-<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
-<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class  </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html">tvm::script::printer::OpCallDoc</a></td></tr>
-<tr class="memdesc:"><td class="mdescLeft"> </td><td class="mdescRight">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html" title="Doc that represents call to an TIRX operator.">OpCallDocNode</a>. <a href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#details">More...</a><br /></td></tr>
-<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class  </td><td class="memItemRight" valign="bottom"><a class="el" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html">tvm::script::printer::NamespaceDocNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft"> </td><td class="mdescRight">A reference to a canonical script namespace. <a href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2"> </td></tr>
diff --git a/docs/reference/api/doxygen/doc_8h_source.html b/docs/reference/api/doxygen/doc_8h_source.html
index 6c8cd23d235..6c9d90bdfcb 100644
--- a/docs/reference/api/doxygen/doc_8h_source.html
+++ b/docs/reference/api/doxygen/doc_8h_source.html
@@ -1009,69 +1009,34 @@ $(document).ready(function() { init_codefold(0); });
</div>
<div class="line"><a id="l01354" name="l01354"></a><span class="lineno"> 1354</span> </div>
<div class="foldopen" id="foldopen01360" data-start="{" data-end="};">
-<div class="line"><a id="l01360" name="l01360"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html"> 1360</a></span><span class="keyword">class </span><a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">OpCallDocNode</a> : <span class="keyword">public</span> <a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html">StmtDocNode</a> {</div>
+<div class="line"><a id="l01360" name="l01360"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html"> 1360</a></span><span class="keyword">class </span><a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html">NamespaceDocNode</a> : <span class="keyword">public</span> <a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1ExprDocNode.html">ExprDocNode</a> {</div>
<div class="line"><a id="l01361" name="l01361"></a><span class="lineno"> 1361</span> <span class="keyword">public</span>:</div>
-<div class="line"><a id="l01363" name="l01363"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#adbcf4a3aabbe1d82f73fc2d5f6154f6b"> 1363</a></span> <a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1ExprDoc.html">ExprDoc</a> <a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#adbcf4a3aabbe1d82f73fc2d5f6154f6b">callee</a>{ffi::UnsafeInit()};</div>
-<div class="line"><a id="l01365" name="l01365"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#aa251921e11727010772291877807750a"> 1365</a></span> ffi::Array<Doc> <a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#aa251921e11727010772291877807750a">args</a>;</div>
-<div class="line"><a id="l01367" name="l01367"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ac5eaf7f682b39836acebf055f7c843ed"> 1367</a></span> ffi::Optional<DictDoc> <a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ac5eaf7f682b39836acebf055f7c843ed">workspace</a>{std::nullopt};</div>
-<div class="line"><a id="l01369" name="l01369"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ab587d4e63b73fc2411792cba3517b5ae"> 1369</a></span> ffi::Optional<DictDoc> <a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ab587d4e63b73fc2411792cba3517b5ae">config</a>{std::nullopt};</div>
-<div class="line"><a id="l01371" name="l01371"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#a9463aa1e349fdaa77ee00318eda01047"> 1371</a></span> ffi::Optional<ExprDoc> <a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#a9463aa1e349fdaa77ee00318eda01047">dispatch</a>{std::nullopt};</div>
-<div class="line"><a id="l01372" name="l01372"></a><span class="lineno"> 1372</span> </div>
-<div class="foldopen" id="foldopen01373" data-start="{" data-end="}">
-<div class="line"><a id="l01373" name="l01373"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#aa711d33587526cd7b6e3e8c9c005653b"> 1373</a></span> <span class="keyword">static</span> <span class="keywordtype">void</span> <a class="code hl_function" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#aa711d33587526cd7b6e3e8c9c005653b">RegisterReflection</a>() {</div>
-<div class="line"><a id="l01374" name="l01374"></a><span class="lineno"> 1374</span> <span class="keyword">namespace </span>refl = tvm::ffi::reflection;</div>
-<div class="line"><a id="l01375" name="l01375"></a><span class="lineno"> 1375</span> refl::ObjectDef<OpCallDocNode>()</div>
-<div class="line"><a id="l01376" name="l01376"></a><span class="lineno"> 1376</span> .def_ro(<span class="stringliteral">"callee"</span>, &<a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#adbcf4a3aabbe1d82f73fc2d5f6154f6b">OpCallDocNode::callee</a>)</div>
-<div class="line"><a id="l01377" name="l01377"></a><span class="lineno"> 1377</span> .def_ro(<span class="stringliteral">"args"</span>, &<a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#aa251921e11727010772291877807750a">OpCallDocNode::args</a>)</div>
-<div class="line"><a id="l01378" name="l01378"></a><span class="lineno"> 1378</span> .def_ro(<span class="stringliteral">"workspace"</span>, &<a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ac5eaf7f682b39836acebf055f7c843ed">OpCallDocNode::workspace</a>)</div>
-<div class="line"><a id="l01379" name="l01379"></a><span class="lineno"> 1379</span> .def_ro(<span class="stringliteral">"config"</span>, &<a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ab587d4e63b73fc2411792cba3517b5ae">OpCallDocNode::config</a>)</div>
-<div class="line"><a id="l01380" name="l01380"></a><span class="lineno"> 1380</span> .def_ro(<span class="stringliteral">"dispatch"</span>, &<a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#a9463aa1e349fdaa77ee00318eda01047">OpCallDocNode::dispatch</a>);</div>
-<div class="line"><a id="l01381" name="l01381"></a><span class="lineno"> 1381</span> }</div>
-</div>
-<div class="line"><a id="l01382" name="l01382"></a><span class="lineno"> 1382</span> </div>
-<div class="line"><a id="l01383" name="l01383"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#a37c9f827e2e422759bce6978c7b11fc3"> 1383</a></span> <a class="code hl_function" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#a37c9f827e2e422759bce6978c7b11fc3">TVM_FFI_DECLARE_OBJECT_INFO_FINAL</a>(<span class="stringliteral">"script.printer.OpCallDoc"</span>, <a class="code hl_class" href="classtvm_1_1script_1_1printer_ [...]
-<div class="line"><a id="l01384" name="l01384"></a><span class="lineno"> 1384</span>};</div>
-</div>
-<div class="line"><a id="l01385" name="l01385"></a><span class="lineno"> 1385</span> </div>
-<div class="foldopen" id="foldopen01391" data-start="{" data-end="};">
-<div class="line"><a id="l01391" name="l01391"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html"> 1391</a></span><span class="keyword">class </span><a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html">OpCallDoc</a> : <span class="keyword">public</span> <a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1StmtDoc.html">StmtDoc</a> {</div>
-<div class="line"><a id="l01392" name="l01392"></a><span class="lineno"> 1392</span> <span class="keyword">public</span>:</div>
-<div class="line"><a id="l01401" name="l01401"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#ab5b4f91b550e6e9b43f8a5659604da42"> 1401</a></span> TVM_DLL <span class="keyword">explicit</span> <a class="code hl_function" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#ab5b4f91b550e6e9b43f8a5659604da42">OpCallDoc</a>(<a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1ExprDoc.html">ExprDoc</a> callee, ffi::Array<Doc> [...]
-<div class="line"><a id="l01402" name="l01402"></a><span class="lineno"> 1402</span> ffi::Optional<DictDoc> config,</div>
-<div class="line"><a id="l01403" name="l01403"></a><span class="lineno"> 1403</span> ffi::Optional<ExprDoc> dispatch = std::nullopt);</div>
-<div class="line"><a id="l01404" name="l01404"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#a6ebc9be8e178115a68d47075669f32a7"> 1404</a></span> <a class="code hl_function" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#a6ebc9be8e178115a68d47075669f32a7">TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE</a>(<a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html">OpCallDoc</a>, <a class="code hl_class" href="clas [...]
-<div class="line"><a id="l01405" name="l01405"></a><span class="lineno"> 1405</span>};</div>
-</div>
-<div class="line"><a id="l01406" name="l01406"></a><span class="lineno"> 1406</span> </div>
-<div class="foldopen" id="foldopen01412" data-start="{" data-end="};">
-<div class="line"><a id="l01412" name="l01412"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html"> 1412</a></span><span class="keyword">class </span><a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html">NamespaceDocNode</a> : <span class="keyword">public</span> <a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1ExprDocNode.html">ExprDocNode</a> {</div>
-<div class="line"><a id="l01413" name="l01413"></a><span class="lineno"> 1413</span> <span class="keyword">public</span>:</div>
-<div class="line"><a id="l01415" name="l01415"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#aff1146b3556123ae0384c7ff0976aac6"> 1415</a></span> ffi::String <a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#aff1146b3556123ae0384c7ff0976aac6">canonical_name</a>;</div>
-<div class="line"><a id="l01416" name="l01416"></a><span class="lineno"> 1416</span> </div>
-<div class="foldopen" id="foldopen01417" data-start="{" data-end="}">
-<div class="line"><a id="l01417" name="l01417"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#a74205c9766e0ce8f1432dd543bed276d"> 1417</a></span> <span class="keyword">static</span> <span class="keywordtype">void</span> <a class="code hl_function" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#a74205c9766e0ce8f1432dd543bed276d">RegisterReflection</a>() {</div>
-<div class="line"><a id="l01418" name="l01418"></a><span class="lineno"> 1418</span> ffi::reflection::ObjectDef<NamespaceDocNode>().def_ro(<span class="stringliteral">"canonical_name"</span>,</div>
-<div class="line"><a id="l01419" name="l01419"></a><span class="lineno"> 1419</span> &<a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#aff1146b3556123ae0384c7ff0976aac6">NamespaceDocNode::canonical_name</a>);</div>
-<div class="line"><a id="l01420" name="l01420"></a><span class="lineno"> 1420</span> }</div>
-</div>
-<div class="line"><a id="l01421" name="l01421"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#a5a9df64c31f7f6898cc1993510766c3a"> 1421</a></span> <a class="code hl_function" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#a5a9df64c31f7f6898cc1993510766c3a">TVM_FFI_DECLARE_OBJECT_INFO_FINAL</a>(<span class="stringliteral">"script.printer.NamespaceDoc"</span>, <a class="code hl_class" href="classtvm_1_1script_1_ [...]
-<div class="line"><a id="l01422" name="l01422"></a><span class="lineno"> 1422</span>};</div>
-</div>
-<div class="line"><a id="l01423" name="l01423"></a><span class="lineno"> 1423</span> </div>
-<div class="foldopen" id="foldopen01427" data-start="{" data-end="};">
-<div class="line"><a id="l01427" name="l01427"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html"> 1427</a></span><span class="keyword">class </span><a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html">NamespaceDoc</a> : <span class="keyword">public</span> <a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1ExprDoc.html">ExprDoc</a> {</div>
-<div class="line"><a id="l01428" name="l01428"></a><span class="lineno"> 1428</span> <span class="keyword">public</span>:</div>
-<div class="line"><a id="l01433" name="l01433"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html#aa16a85483cb58dcdeed759480f606291"> 1433</a></span> TVM_DLL <span class="keyword">explicit</span> <a class="code hl_function" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html#aa16a85483cb58dcdeed759480f606291">NamespaceDoc</a>(ffi::String canonical_name);</div>
-<div class="line"><a id="l01434" name="l01434"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html#af682585e57a399696cfcdd6a49382e73"> 1434</a></span> <a class="code hl_function" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html#af682585e57a399696cfcdd6a49382e73">TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE</a>(<a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html">NamespaceDoc</a>, <a class="code hl_class [...]
-<div class="line"><a id="l01435" name="l01435"></a><span class="lineno"> 1435</span>};</div>
-</div>
-<div class="line"><a id="l01436" name="l01436"></a><span class="lineno"> 1436</span> </div>
-<div class="line"><a id="l01437" name="l01437"></a><span class="lineno"> 1437</span>} <span class="comment">// namespace printer</span></div>
-</div>
-<div class="line"><a id="l01438" name="l01438"></a><span class="lineno"> 1438</span>} <span class="comment">// namespace script</span></div>
-<div class="line"><a id="l01439" name="l01439"></a><span class="lineno"> 1439</span>} <span class="comment">// namespace tvm</span></div>
-<div class="line"><a id="l01440" name="l01440"></a><span class="lineno"> 1440</span> </div>
-<div class="line"><a id="l01441" name="l01441"></a><span class="lineno"> 1441</span><span class="preprocessor">#endif </span><span class="comment">// TVM_SCRIPT_PRINTER_DOC_H_</span></div>
+<div class="line"><a id="l01363" name="l01363"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#aff1146b3556123ae0384c7ff0976aac6"> 1363</a></span> ffi::String <a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#aff1146b3556123ae0384c7ff0976aac6">canonical_name</a>;</div>
+<div class="line"><a id="l01364" name="l01364"></a><span class="lineno"> 1364</span> </div>
+<div class="foldopen" id="foldopen01365" data-start="{" data-end="}">
+<div class="line"><a id="l01365" name="l01365"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#a74205c9766e0ce8f1432dd543bed276d"> 1365</a></span> <span class="keyword">static</span> <span class="keywordtype">void</span> <a class="code hl_function" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#a74205c9766e0ce8f1432dd543bed276d">RegisterReflection</a>() {</div>
+<div class="line"><a id="l01366" name="l01366"></a><span class="lineno"> 1366</span> ffi::reflection::ObjectDef<NamespaceDocNode>().def_ro(<span class="stringliteral">"canonical_name"</span>,</div>
+<div class="line"><a id="l01367" name="l01367"></a><span class="lineno"> 1367</span> &<a class="code hl_variable" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#aff1146b3556123ae0384c7ff0976aac6">NamespaceDocNode::canonical_name</a>);</div>
+<div class="line"><a id="l01368" name="l01368"></a><span class="lineno"> 1368</span> }</div>
+</div>
+<div class="line"><a id="l01369" name="l01369"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#a5a9df64c31f7f6898cc1993510766c3a"> 1369</a></span> <a class="code hl_function" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#a5a9df64c31f7f6898cc1993510766c3a">TVM_FFI_DECLARE_OBJECT_INFO_FINAL</a>(<span class="stringliteral">"script.printer.NamespaceDoc"</span>, <a class="code hl_class" href="classtvm_1_1script_1_ [...]
+<div class="line"><a id="l01370" name="l01370"></a><span class="lineno"> 1370</span>};</div>
+</div>
+<div class="line"><a id="l01371" name="l01371"></a><span class="lineno"> 1371</span> </div>
+<div class="foldopen" id="foldopen01375" data-start="{" data-end="};">
+<div class="line"><a id="l01375" name="l01375"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html"> 1375</a></span><span class="keyword">class </span><a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html">NamespaceDoc</a> : <span class="keyword">public</span> <a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1ExprDoc.html">ExprDoc</a> {</div>
+<div class="line"><a id="l01376" name="l01376"></a><span class="lineno"> 1376</span> <span class="keyword">public</span>:</div>
+<div class="line"><a id="l01381" name="l01381"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html#aa16a85483cb58dcdeed759480f606291"> 1381</a></span> TVM_DLL <span class="keyword">explicit</span> <a class="code hl_function" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html#aa16a85483cb58dcdeed759480f606291">NamespaceDoc</a>(ffi::String canonical_name);</div>
+<div class="line"><a id="l01382" name="l01382"></a><span class="lineno"><a class="line" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html#af682585e57a399696cfcdd6a49382e73"> 1382</a></span> <a class="code hl_function" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html#af682585e57a399696cfcdd6a49382e73">TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE</a>(<a class="code hl_class" href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html">NamespaceDoc</a>, <a class="code hl_class [...]
+<div class="line"><a id="l01383" name="l01383"></a><span class="lineno"> 1383</span>};</div>
+</div>
+<div class="line"><a id="l01384" name="l01384"></a><span class="lineno"> 1384</span> </div>
+<div class="line"><a id="l01385" name="l01385"></a><span class="lineno"> 1385</span>} <span class="comment">// namespace printer</span></div>
+</div>
+<div class="line"><a id="l01386" name="l01386"></a><span class="lineno"> 1386</span>} <span class="comment">// namespace script</span></div>
+<div class="line"><a id="l01387" name="l01387"></a><span class="lineno"> 1387</span>} <span class="comment">// namespace tvm</span></div>
+<div class="line"><a id="l01388" name="l01388"></a><span class="lineno"> 1388</span> </div>
+<div class="line"><a id="l01389" name="l01389"></a><span class="lineno"> 1389</span><span class="preprocessor">#endif </span><span class="comment">// TVM_SCRIPT_PRINTER_DOC_H_</span></div>
<div class="ttc" id="aclasstvm_1_1FloatImm_html"><div class="ttname"><a href="classtvm_1_1FloatImm.html">tvm::FloatImm</a></div><div class="ttdoc">Managed reference class to FloatImmNode.</div><div class="ttdef"><b>Definition</b> expr.h:232</div></div>
<div class="ttc" id="aclasstvm_1_1IntImm_html"><div class="ttname"><a href="classtvm_1_1IntImm.html">tvm::IntImm</a></div><div class="ttdoc">Managed reference class to IntImmNode.</div><div class="ttdef"><b>Definition</b> expr.h:152</div></div>
<div class="ttc" id="aclasstvm_1_1IntImm_html_a232b7695930771cd5f3cf7723d5f80a5"><div class="ttname"><a href="classtvm_1_1IntImm.html#a232b7695930771cd5f3cf7723d5f80a5">tvm::IntImm::Int64</a></div><div class="ttdeci">static IntImm Int64(ffi::BigInt value, Location loc=UnknownLoc())</div><div class="ttdoc">Construct a scalar int64 constant.</div><div class="ttdef"><b>Definition</b> expr.h:195</div></div>
@@ -1267,24 +1232,13 @@ $(document).ready(function() { init_codefold(0); });
<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1LiteralDoc_html_adf5050e0e390f618d0badcd56a2ecf66"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1LiteralDoc.html#adf5050e0e390f618d0badcd56a2ecf66">tvm::script::printer::LiteralDoc::Float</a></div><div class="ttdeci">static LiteralDoc Float(double v, const ffi::Optional< AccessPath > &p)</div><div class="ttdoc">Create a LiteralDoc to represent float.</div><div class="ttdef"><b>Definition</b> doc.h:295</div></div>
<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1LiteralDoc_html_af50fe059e494e0e68395cd49abcd0b8f"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1LiteralDoc.html#af50fe059e494e0e68395cd49abcd0b8f">tvm::script::printer::LiteralDoc::None</a></div><div class="ttdeci">static LiteralDoc None(const ffi::Optional< AccessPath > &p)</div><div class="ttdoc">Create a LiteralDoc to represent None/null/empty value.</div><div class="ttdef"><b>Definition</b> doc.h:261</d [...]
<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1LiteralDoc_html_aff9ffe0ea5415919afa1fdc8f85a9867"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1LiteralDoc.html#aff9ffe0ea5415919afa1fdc8f85a9867">tvm::script::printer::LiteralDoc::Str</a></div><div class="ttdeci">static LiteralDoc Str(const ffi::String &v, const ffi::Optional< AccessPath > &p)</div><div class="ttdoc">Create a LiteralDoc to represent string.</div><div class="ttdef"><b>Definition</b> doc [...]
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1NamespaceDocNode_html"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html">tvm::script::printer::NamespaceDocNode</a></div><div class="ttdoc">A reference to a canonical script namespace.</div><div class="ttdef"><b>Definition</b> doc.h:1412</div></div>
+<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1NamespaceDocNode_html"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html">tvm::script::printer::NamespaceDocNode</a></div><div class="ttdoc">A reference to a canonical script namespace.</div><div class="ttdef"><b>Definition</b> doc.h:1360</div></div>
<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1NamespaceDocNode_html_a5a9df64c31f7f6898cc1993510766c3a"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#a5a9df64c31f7f6898cc1993510766c3a">tvm::script::printer::NamespaceDocNode::TVM_FFI_DECLARE_OBJECT_INFO_FINAL</a></div><div class="ttdeci">TVM_FFI_DECLARE_OBJECT_INFO_FINAL("script.printer.NamespaceDoc", NamespaceDocNode, ExprDocNode)</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1NamespaceDocNode_html_a74205c9766e0ce8f1432dd543bed276d"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#a74205c9766e0ce8f1432dd543bed276d">tvm::script::printer::NamespaceDocNode::RegisterReflection</a></div><div class="ttdeci">static void RegisterReflection()</div><div class="ttdef"><b>Definition</b> doc.h:1417</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1NamespaceDocNode_html_aff1146b3556123ae0384c7ff0976aac6"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#aff1146b3556123ae0384c7ff0976aac6">tvm::script::printer::NamespaceDocNode::canonical_name</a></div><div class="ttdeci">ffi::String canonical_name</div><div class="ttdoc">The namespace name before alias resolution.</div><div class="ttdef"><b>Definition</b> doc.h:1415</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1NamespaceDoc_html"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html">tvm::script::printer::NamespaceDoc</a></div><div class="ttdoc">An owning reference to a deferred script namespace.</div><div class="ttdef"><b>Definition</b> doc.h:1427</div></div>
+<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1NamespaceDocNode_html_a74205c9766e0ce8f1432dd543bed276d"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#a74205c9766e0ce8f1432dd543bed276d">tvm::script::printer::NamespaceDocNode::RegisterReflection</a></div><div class="ttdeci">static void RegisterReflection()</div><div class="ttdef"><b>Definition</b> doc.h:1365</div></div>
+<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1NamespaceDocNode_html_aff1146b3556123ae0384c7ff0976aac6"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#aff1146b3556123ae0384c7ff0976aac6">tvm::script::printer::NamespaceDocNode::canonical_name</a></div><div class="ttdeci">ffi::String canonical_name</div><div class="ttdoc">The namespace name before alias resolution.</div><div class="ttdef"><b>Definition</b> doc.h:1363</div></div>
+<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1NamespaceDoc_html"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html">tvm::script::printer::NamespaceDoc</a></div><div class="ttdoc">An owning reference to a deferred script namespace.</div><div class="ttdef"><b>Definition</b> doc.h:1375</div></div>
<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1NamespaceDoc_html_aa16a85483cb58dcdeed759480f606291"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html#aa16a85483cb58dcdeed759480f606291">tvm::script::printer::NamespaceDoc::NamespaceDoc</a></div><div class="ttdeci">NamespaceDoc(ffi::String canonical_name)</div><div class="ttdoc">Construct a deferred namespace reference.</div></div>
<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1NamespaceDoc_html_af682585e57a399696cfcdd6a49382e73"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1NamespaceDoc.html#af682585e57a399696cfcdd6a49382e73">tvm::script::printer::NamespaceDoc::TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE</a></div><div class="ttdeci">TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE(NamespaceDoc, ExprDoc, NamespaceDocNode)</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OpCallDocNode_html"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html">tvm::script::printer::OpCallDocNode</a></div><div class="ttdoc">Doc that represents call to an TIRX operator.</div><div class="ttdef"><b>Definition</b> doc.h:1360</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OpCallDocNode_html_a37c9f827e2e422759bce6978c7b11fc3"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#a37c9f827e2e422759bce6978c7b11fc3">tvm::script::printer::OpCallDocNode::TVM_FFI_DECLARE_OBJECT_INFO_FINAL</a></div><div class="ttdeci">TVM_FFI_DECLARE_OBJECT_INFO_FINAL("script.printer.OpCallDoc", OpCallDocNode, StmtDocNode)</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OpCallDocNode_html_a9463aa1e349fdaa77ee00318eda01047"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#a9463aa1e349fdaa77ee00318eda01047">tvm::script::printer::OpCallDocNode::dispatch</a></div><div class="ttdeci">ffi::Optional< ExprDoc > dispatch</div><div class="ttdoc">The optional dispatch variant of this op call.</div><div class="ttdef"><b>Definition</b> doc.h:1371</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OpCallDocNode_html_aa251921e11727010772291877807750a"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#aa251921e11727010772291877807750a">tvm::script::printer::OpCallDocNode::args</a></div><div class="ttdeci">ffi::Array< Doc > args</div><div class="ttdoc">The positional arguments.</div><div class="ttdef"><b>Definition</b> doc.h:1365</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OpCallDocNode_html_aa711d33587526cd7b6e3e8c9c005653b"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#aa711d33587526cd7b6e3e8c9c005653b">tvm::script::printer::OpCallDocNode::RegisterReflection</a></div><div class="ttdeci">static void RegisterReflection()</div><div class="ttdef"><b>Definition</b> doc.h:1373</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OpCallDocNode_html_ab587d4e63b73fc2411792cba3517b5ae"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ab587d4e63b73fc2411792cba3517b5ae">tvm::script::printer::OpCallDocNode::config</a></div><div class="ttdeci">ffi::Optional< DictDoc > config</div><div class="ttdoc">The config of this op call.</div><div class="ttdef"><b>Definition</b> doc.h:1369</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OpCallDocNode_html_ac5eaf7f682b39836acebf055f7c843ed"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ac5eaf7f682b39836acebf055f7c843ed">tvm::script::printer::OpCallDocNode::workspace</a></div><div class="ttdeci">ffi::Optional< DictDoc > workspace</div><div class="ttdoc">The workspace of this op call.</div><div class="ttdef"><b>Definition</b> doc.h:1367</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OpCallDocNode_html_adbcf4a3aabbe1d82f73fc2d5f6154f6b"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#adbcf4a3aabbe1d82f73fc2d5f6154f6b">tvm::script::printer::OpCallDocNode::callee</a></div><div class="ttdeci">ExprDoc callee</div><div class="ttdoc">The callee of this function call.</div><div class="ttdef"><b>Definition</b> doc.h:1363</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OpCallDoc_html"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html">tvm::script::printer::OpCallDoc</a></div><div class="ttdoc">Reference type of OpCallDocNode.</div><div class="ttdef"><b>Definition</b> doc.h:1391</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OpCallDoc_html_a6ebc9be8e178115a68d47075669f32a7"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#a6ebc9be8e178115a68d47075669f32a7">tvm::script::printer::OpCallDoc::TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE</a></div><div class="ttdeci">TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE(OpCallDoc, StmtDoc, OpCallDocNode)</div></div>
-<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OpCallDoc_html_ab5b4f91b550e6e9b43f8a5659604da42"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#ab5b4f91b550e6e9b43f8a5659604da42">tvm::script::printer::OpCallDoc::OpCallDoc</a></div><div class="ttdeci">OpCallDoc(ExprDoc callee, ffi::Array< Doc > args, ffi::Optional< DictDoc > workspace, ffi::Optional< DictDoc > config, ffi::Optional< ExprDoc > dispatch=std::nullopt)</div><div cl [...]
<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OperationDocNode_html"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OperationDocNode.html">tvm::script::printer::OperationDocNode</a></div><div class="ttdoc">Doc that represents operation.</div><div class="ttdef"><b>Definition</b> doc.h:536</div></div>
<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OperationDocNode_html_a28358416397c95540a48852710c17385"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OperationDocNode.html#a28358416397c95540a48852710c17385">tvm::script::printer::OperationDocNode::TVM_FFI_DECLARE_OBJECT_INFO_FINAL</a></div><div class="ttdeci">TVM_FFI_DECLARE_OBJECT_INFO_FINAL("script.printer.OperationDoc", OperationDocNode, ExprDocNode)</div></div>
<div class="ttc" id="aclasstvm_1_1script_1_1printer_1_1OperationDocNode_html_a2d6086cff6613d467c7606a1a71c7e63"><div class="ttname"><a href="classtvm_1_1script_1_1printer_1_1OperationDocNode.html#a2d6086cff6613d467c7606a1a71c7e63">tvm::script::printer::OperationDocNode::operands</a></div><div class="ttdeci">ffi::Array< ExprDoc > operands</div><div class="ttdoc">Operands of this expression.</div><div class="ttdef"><b>Definition</b> doc.h:580</div></div>
diff --git a/docs/reference/api/doxygen/functions_a.html b/docs/reference/api/doxygen/functions_a.html
index ed19fefb325..d17564bb01c 100644
--- a/docs/reference/api/doxygen/functions_a.html
+++ b/docs/reference/api/doxygen/functions_a.html
@@ -115,7 +115,7 @@ $(function() {
<li>alpha : <a class="el" href="structtvm_1_1relax_1_1LeakyReluAttrs.html#ad391f46f46531b0053f70ab2042ac1e0">tvm::relax::LeakyReluAttrs</a></li>
<li>Analyzer() : <a class="el" href="classtvm_1_1sym_1_1Analyzer.html#a22d86e55cc1b339ba90f04c9d49bce77">tvm::sym::Analyzer</a>, <a class="el" href="classtvm_1_1sym_1_1Z3Prover.html#a88d594816df596eed10643082b0d0805">tvm::sym::Z3Prover</a></li>
<li>AnalyzerObj() : <a class="el" href="classtvm_1_1sym_1_1AnalyzerObj.html#aca86b9c3fdd851c0d094450bbb8f9459">tvm::sym::AnalyzerObj</a>, <a class="el" href="classtvm_1_1sym_1_1CanonicalSimplifier.html#ab502b81f91a3692606541f1ec44911de">tvm::sym::CanonicalSimplifier</a>, <a class="el" href="classtvm_1_1sym_1_1ConstIntBoundAnalyzer.html#ab502b81f91a3692606541f1ec44911de">tvm::sym::ConstIntBoundAnalyzer</a>, <a class="el" href="classtvm_1_1sym_1_1IntSetAnalyzer.html#ab502b81f91a3 [...]
-<li>And() : <a class="el" href="classtvm_1_1prim_1_1And.html#a41a71a1db6bcf32bc0d94bb1684d959c">tvm::prim::And</a></li>
+<li>And() : <a class="el" href="classtvm_1_1prim_1_1And.html#ae6c2c33f3bbd04ec0f9e80beb06cac48">tvm::prim::And</a></li>
<li>AndNode() : <a class="el" href="classtvm_1_1prim_1_1AndNode.html#a79b06dadaf22214c79c2b14c08f70f8a">tvm::prim::AndNode</a></li>
<li>AndPattern() : <a class="el" href="classtvm_1_1relax_1_1AndPattern.html#a027c47e6b406c0412ec0fe313838a75d">tvm::relax::AndPattern</a></li>
<li>Annotate() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#ac54076d59c43238501c609768448b8e6">tvm::s_tir::ScheduleNode</a></li>
@@ -126,7 +126,7 @@ $(function() {
<li>annotations : <a class="el" href="classtvm_1_1ForNode.html#ab9ae1f41c715c0a8c8dcdcf3b4c9823f">tvm::ForNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1SBlockNode.html#ae70f381c587a0a085367e74309ebfe2f">tvm::s_tir::SBlockNode</a>, <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1s__tir_1_1SBlockFrameNode.html#a5238ce3fae21d21fc62330c207cf08e2">tvm::script::ir_builder::s_tir::SBlockFrameNode</a></li>
<li>AnyType() : <a class="el" href="classtvm_1_1AnyType.html#aa6f0d2a293f42367dbbca4faf18465ed">tvm::AnyType</a></li>
<li>Append() : <a class="el" href="classtvm_1_1s__tir_1_1TraceNode.html#a93902e5023c347080e3b6c593f6c3416">tvm::s_tir::TraceNode</a></li>
-<li>Apply() : <a class="el" href="classtvm_1_1LambdaExprNode.html#ac9f3da9a6668b480a2abb8321cf5c682">tvm::LambdaExprNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1MeasureCallbackNode.html#a1315d1f34b41f106b2947eb9497e6661">tvm::s_tir::meta_schedule::MeasureCallbackNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1MutatorNode.html#af48a9ed250598032967394ef661e55c6">tvm::s_tir::meta_schedule::MutatorNode</a>, <a class="el" href="classtvm [...]
+<li>Apply() : <a class="el" href="classtvm_1_1LambdaExprNode.html#ac9f3da9a6668b480a2abb8321cf5c682">tvm::LambdaExprNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1MeasureCallbackNode.html#a1315d1f34b41f106b2947eb9497e6661">tvm::s_tir::meta_schedule::MeasureCallbackNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1MutatorNode.html#af48a9ed250598032967394ef661e55c6">tvm::s_tir::meta_schedule::MutatorNode</a>, <a class="el" href="classtvm [...]
<li>apply_softmax : <a class="el" href="structtvm_1_1relax_1_1MultiboxTransformLocAttrs.html#a2edaf8d654ebb18f47b4a3ef2e6810f4">tvm::relax::MultiboxTransformLocAttrs</a></li>
<li>ApplyCustomRule() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1ScheduleRule.html#a41980394c9b3c2add7969b99cb9971a6">tvm::s_tir::meta_schedule::ScheduleRule</a></li>
<li>ApplyJSONToSchedule() : <a class="el" href="classtvm_1_1s__tir_1_1Trace.html#a8fa54d5d3ba0fdad42544432eacf0c69">tvm::s_tir::Trace</a></li>
@@ -135,7 +135,7 @@ $(function() {
<li>arg_types : <a class="el" href="classtvm_1_1FuncTypeNode.html#aa8e067bd61ced30bc55f637f4792aef4">tvm::FuncTypeNode</a></li>
<li>ArgInfo() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1ArgInfo.html#a986a0662c8dafbc4ba7c6a48d721a3fb">tvm::s_tir::meta_schedule::ArgInfo</a></li>
<li>ArgKind : <a class="el" href="structtvm_1_1runtime_1_1vm_1_1Instruction.html#ad009411831e6f77c97ea9bf65e88ba6b">tvm::runtime::vm::Instruction</a></li>
-<li>args : <a class="el" href="classtvm_1_1CallNode.html#a323af62ed5243b5db00eb1832f842a1c">tvm::CallNode</a>, <a class="el" href="classtvm_1_1RegionStmtNode.html#aa0ff83b20975a305cff8622fcfed9cbe">tvm::RegionStmtNode</a>, <a class="el" href="classtvm_1_1relax_1_1CallPatternNode.html#a747a5214b15a6288560fdd359eeb7c75">tvm::relax::CallPatternNode</a>, <a class="el" href="classtvm_1_1relax_1_1SameShapeConstraintNode.html#ac5f5eb8f9a7e1f83966726767fec6568">tvm::relax::SameShapeCon [...]
+<li>args : <a class="el" href="classtvm_1_1CallNode.html#a323af62ed5243b5db00eb1832f842a1c">tvm::CallNode</a>, <a class="el" href="classtvm_1_1RegionStmtNode.html#aa0ff83b20975a305cff8622fcfed9cbe">tvm::RegionStmtNode</a>, <a class="el" href="classtvm_1_1relax_1_1CallPatternNode.html#a747a5214b15a6288560fdd359eeb7c75">tvm::relax::CallPatternNode</a>, <a class="el" href="classtvm_1_1relax_1_1SameShapeConstraintNode.html#ac5f5eb8f9a7e1f83966726767fec6568">tvm::relax::SameShapeCon [...]
<li>args_info : <a class="el" href="classtvm_1_1OpNode.html#a1106cc90ca7823f513807317116b87e0">tvm::OpNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1MeasureCandidateNode.html#a3eaf9e7d35f07938f40ae6b056fd9522">tvm::s_tir::meta_schedule::MeasureCandidateNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1RunnerInputNode.html#adda3434c59e17fe2b9159ac1e0b105e4">tvm::s_tir::meta_schedule::RunnerInputNode</a>, <a class="el" href="classtvm_1_1 [...]
<li>artifact_path : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1BuilderResultNode.html#a6b42b9c07eafa45985402eac9379b380">tvm::s_tir::meta_schedule::BuilderResultNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1RunnerInputNode.html#aa654ac5e47a68b46e70271d1652188ee">tvm::s_tir::meta_schedule::RunnerInputNode</a></li>
<li>AsCondition() : <a class="el" href="classtvm_1_1relax_1_1DFConstraintNode.html#a3514ef6fe106812d23d06463faae9d7e">tvm::relax::DFConstraintNode</a>, <a class="el" href="classtvm_1_1relax_1_1SameShapeConstraintNode.html#a15a1ed26b5e2590d87fee3d1a1601072">tvm::relax::SameShapeConstraintNode</a></li>
diff --git a/docs/reference/api/doxygen/functions_c.html b/docs/reference/api/doxygen/functions_c.html
index 29f4670c9e0..b9258e06433 100644
--- a/docs/reference/api/doxygen/functions_c.html
+++ b/docs/reference/api/doxygen/functions_c.html
@@ -76,10 +76,10 @@ $(function() {
<li>CacheInplace() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#a09f1cd626bf8514c3e7d8393039d5c0e">tvm::s_tir::ScheduleNode</a></li>
<li>CacheRead() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#a1859bce31d9f5bed202ca90e9b6ab85d">tvm::s_tir::ScheduleNode</a></li>
<li>CacheWrite() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#adb8919ca972244ea4eb13e9e5e4063df">tvm::s_tir::ScheduleNode</a></li>
-<li>Call() : <a class="el" href="classtvm_1_1Call.html#a9ea62a2cf30af9dd03892d9b7ac9e3de">tvm::Call</a>, <a class="el" href="structtvm_1_1runtime_1_1vm_1_1Instruction.html#a70b9e9c1632058a9bfbaecb00a2926c2">tvm::runtime::vm::Instruction</a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1ExprDocNode.html#a84661ae5560b5daf2084443fb8c93e1d">tvm::script::printer::ExprDocNode</a></li>
+<li>Call() : <a class="el" href="classtvm_1_1Call.html#a26304eac4f5299ac4b4862105a9f5cd5">tvm::Call</a>, <a class="el" href="structtvm_1_1runtime_1_1vm_1_1Instruction.html#a70b9e9c1632058a9bfbaecb00a2926c2">tvm::runtime::vm::Instruction</a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1ExprDocNode.html#a84661ae5560b5daf2084443fb8c93e1d">tvm::script::printer::ExprDocNode</a></li>
<li>callbacks : <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1IRBuilderFrameNode.html#a45f552bb19d593f4ecc4b3b5d69cf8dc">tvm::script::ir_builder::IRBuilderFrameNode</a>, <a class="el" href="classtvm_1_1tirx_1_1DispatchContextNode.html#a3e48b15d23856ba7c084531dae51fb7b">tvm::tirx::DispatchContextNode</a></li>
<li>CallDoc() : <a class="el" href="classtvm_1_1script_1_1printer_1_1CallDoc.html#ae26a9378550bb5750464fd299b33e9ed">tvm::script::printer::CallDoc</a></li>
-<li>callee : <a class="el" href="classtvm_1_1CallSiteLocNode.html#a40365565ed92a9de7a0b2023befbc306">tvm::CallSiteLocNode</a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1CallDocNode.html#afd99b131a9accf85284b528203e71413">tvm::script::printer::CallDocNode</a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#adbcf4a3aabbe1d82f73fc2d5f6154f6b">tvm::script::printer::OpCallDocNode</a></li>
+<li>callee : <a class="el" href="classtvm_1_1CallSiteLocNode.html#a40365565ed92a9de7a0b2023befbc306">tvm::CallSiteLocNode</a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1CallDocNode.html#afd99b131a9accf85284b528203e71413">tvm::script::printer::CallDocNode</a></li>
<li>caller : <a class="el" href="classtvm_1_1CallSiteLocNode.html#af6317bd3ebd9e9c2a8d9e39d91cfafe9">tvm::CallSiteLocNode</a></li>
<li>CallNode() : <a class="el" href="classtvm_1_1CallNode.html#adf837eb3faa5535c97311eb0f2ccb0e0">tvm::CallNode</a></li>
<li>CallPacked() : <a class="el" href="classtvm_1_1runtime_1_1SessionObj.html#af5afdb77fe43ac0591c872648ee820d4">tvm::runtime::SessionObj</a></li>
@@ -117,7 +117,7 @@ $(function() {
<li>ClearDispatch() : <a class="el" href="classtvm_1_1ObjectFunctor_3_01R_07NodeArg_00_01Args_8_8_8_08_4.html#a386da1d439515ecf52b8dddde6b178dd">tvm::ObjectFunctor< R(NodeArg, Args...)></a></li>
<li>clip : <a class="el" href="structtvm_1_1relax_1_1MultiboxTransformLocAttrs.html#a72744968ebdca190d8c51ab5ac5d6e2c">tvm::relax::MultiboxTransformLocAttrs</a></li>
<li>Clone() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1MutatorNode.html#aae3e2b8f500bcb9a417dfdd2cf2f9d88">tvm::s_tir::meta_schedule::MutatorNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1PostprocNode.html#af5cf3bb5b41bb579661916a6f3ec1200">tvm::s_tir::meta_schedule::PostprocNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1PyMutatorNode.html#a20b39ff62a8f6963f0a07c9f1530d6e6">tvm::s_tir::meta_schedule::PyMutatorNode [...]
-<li>CmpOpNode() : <a class="el" href="classtvm_1_1prim_1_1CmpOpNode.html#aa0067945121c62c729074e2567a971a1">tvm::prim::CmpOpNode< T ></a></li>
+<li>CmpOpNode() : <a class="el" href="classtvm_1_1prim_1_1CmpOpNode.html#a98e606d5a175cf0c9e2b1246c1979110">tvm::prim::CmpOpNode< T ></a></li>
<li>code() : <a class="el" href="classtvm_1_1PrimType.html#a0d4b4cdc6d1307df9540202d86fb6f5e">tvm::PrimType</a></li>
<li>coeff : <a class="el" href="classtvm_1_1sym_1_1ModularSetNode.html#a7104eb112d27fb5b026d7f051463fc00">tvm::sym::ModularSetNode</a></li>
<li>combiner : <a class="el" href="classtvm_1_1te_1_1ReduceNode.html#a9908b5a5102d5fa15bbca52125c4b901">tvm::te::ReduceNode</a></li>
@@ -136,7 +136,6 @@ $(function() {
<li>Concrete() : <a class="el" href="classtvm_1_1s__tir_1_1Schedule.html#a201df3b4dea486314be5ed26cc283b27">tvm::s_tir::Schedule</a></li>
<li>cond : <a class="el" href="classtvm_1_1relax_1_1IfExprNode.html#a6fe48357f17d2a412839db1e72308139">tvm::relax::IfExprNode</a>, <a class="el" href="structtvm_1_1runtime_1_1vm_1_1Instruction.html#a0a9bcefef97c5a7fd11a1dc5103669a2">tvm::runtime::vm::Instruction</a></li>
<li>condition : <a class="el" href="classtvm_1_1AssertStmtNode.html#a42219a8d7a570a32b37fb4c1dd705a03">tvm::AssertStmtNode</a>, <a class="el" href="classtvm_1_1IfNode.html#a4e77795d3f6677cf272cbedac0fd70cd">tvm::IfNode</a>, <a class="el" href="classtvm_1_1prim_1_1SelectNode.html#a7be5da5d136256b91131ace2e5c55cb9">tvm::prim::SelectNode</a>, <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1ir_1_1AssertFrameNode.html#ae23a7e2026a82b0707302f4e3b2babcd">tvm::script::ir_build [...]
-<li>config : <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ab587d4e63b73fc2411792cba3517b5ae">tvm::script::printer::OpCallDocNode</a></li>
<li>Config : <a class="el" href="classtvm_1_1TargetTagRegistry.html#a6971395bfc555f734aac2e38ef0cdd50">tvm::TargetTagRegistry</a></li>
<li>config : <a class="el" href="classtvm_1_1transform_1_1PassContextNode.html#a3eefdea0d7b623abd48b2fb3341631a5">tvm::transform::PassContextNode</a></li>
<li>ConfigMap : <a class="el" href="classtvm_1_1ConfigSchema.html#af15d53ca8f6383ebf23fbec5dd684d5d">tvm::ConfigSchema</a></li>
@@ -154,17 +153,17 @@ $(function() {
<li>Continue() : <a class="el" href="classtvm_1_1Continue.html#ac8c135897f6026ccf33c8d8c02ff8827">tvm::Continue</a></li>
<li>ContinueDoc() : <a class="el" href="classtvm_1_1script_1_1printer_1_1ContinueDoc.html#a3cd20ba5a6587b7d19bfc72e451985bb">tvm::script::printer::ContinueDoc</a></li>
<li>ConvertConstant() : <a class="el" href="classtvm_1_1relax_1_1ExecBuilderNode.html#ac0323caf936e8dc48bcffb6e04a825e8">tvm::relax::ExecBuilderNode</a></li>
-<li>ConvertFallbackValue() : <a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01Expr_01_4.html#a6f4773ee3e012981e082c428d06c5b4d">tvm::ffi::TypeTraits< Expr ></a>, <a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01FloatImm_01_4.html#a2d1f8eb0eaebb896586a4f6914ef1596">tvm::ffi::TypeTraits< FloatImm ></a>, <a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01IntExpr_01_4.html#a04e5c69ff8fe02aeae0407d31441da67">tvm::ffi::TypeTraits< IntExpr ></a>, <a c [...]
+<li>ConvertFallbackValue() : <a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01Expr_01_4.html#a3ac03c8423e9d3ac76c7f81b80623eb9">tvm::ffi::TypeTraits< Expr ></a>, <a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01FloatImm_01_4.html#a2d1f8eb0eaebb896586a4f6914ef1596">tvm::ffi::TypeTraits< FloatImm ></a>, <a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01IntExpr_01_4.html#a04e5c69ff8fe02aeae0407d31441da67">tvm::ffi::TypeTraits< IntExpr ></a>, <a c [...]
<li>coord_start : <a class="el" href="structtvm_1_1relax_1_1NonMaximumSuppressionAttrs.html#ae7348ffbe5e56d404d819c33b0b1ee17">tvm::relax::NonMaximumSuppressionAttrs</a></li>
<li>coordinate_transformation_mode : <a class="el" href="structtvm_1_1relax_1_1Resize2DAttrs.html#ae06df270d320a24daf50f8bf4785d356">tvm::relax::Resize2DAttrs</a>, <a class="el" href="structtvm_1_1relax_1_1Resize3DAttrs.html#aa8fa3788651d5b45ca9cf43e810ede9f">tvm::relax::Resize3DAttrs</a></li>
<li>Copy() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#a9f97ca31fd603a33ac6d7e688f018201">tvm::s_tir::ScheduleNode</a></li>
<li>CopyDataFromTo() : <a class="el" href="classtvm_1_1runtime_1_1DeviceAPI.html#a2f8bed30e62ddd50f02989cbd8a03824">tvm::runtime::DeviceAPI</a></li>
-<li>CopyFrom() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#a6ae739044fd444403bf0a013c5bcd71e">tvm::runtime::Tensor</a></li>
+<li>CopyFrom() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#a4d04ea6025670c4853c4b20ce25edfee">tvm::runtime::Tensor</a></li>
<li>CopyFromBytes() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#ab906e1a006435e988b0e3262bf605da9">tvm::runtime::Tensor</a></li>
<li>CopyFromTo() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#aa215b42c46dd617a25f8240aa5dbb1b5">tvm::runtime::Tensor</a></li>
<li>CopyFromWorker0() : <a class="el" href="classtvm_1_1runtime_1_1SessionObj.html#a6dcb310d5c3a8ca38aaedac7c9d1456d">tvm::runtime::SessionObj</a></li>
<li>CopyOnWrite() : <a class="el" href="classtvm_1_1relax_1_1BindingBlock.html#a974926705d8c711b39f14a3eecd06823">tvm::relax::BindingBlock</a></li>
-<li>CopyTo() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#a9470fc8dc75556e8a0ff7b9b7d76537a">tvm::runtime::Tensor</a></li>
+<li>CopyTo() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#a7590ee11d02a8e2da8ac1b55f8d752bc">tvm::runtime::Tensor</a></li>
<li>CopyToBytes() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#a22c2884b50b94c6d3731ad88e1a5848b">tvm::runtime::Tensor</a></li>
<li>CopyToWorker0() : <a class="el" href="classtvm_1_1runtime_1_1SessionObj.html#a49c2c7066fff2cb998ba6aedf4f3b9c3">tvm::runtime::SessionObj</a></li>
<li>CopyWithDType() : <a class="el" href="classtvm_1_1PrimVar.html#a982fc1e284ee1f0505439b686b34afb9">tvm::PrimVar</a>, <a class="el" href="classtvm_1_1Var.html#a3930c2126518b3b0d8810ca39576759c">tvm::Var</a></li>
diff --git a/docs/reference/api/doxygen/functions_d.html b/docs/reference/api/doxygen/functions_d.html
index c8287da455f..17737cf974d 100644
--- a/docs/reference/api/doxygen/functions_d.html
+++ b/docs/reference/api/doxygen/functions_d.html
@@ -148,9 +148,7 @@ $(function() {
<li>DisallowDynamicLoop() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1Postproc.html#a0c76697b380d59359c4db9cb1afc3d54">tvm::s_tir::meta_schedule::Postproc</a></li>
<li>DiscoWorker() : <a class="el" href="classtvm_1_1runtime_1_1DiscoWorker.html#a089d3adcb982ccae8a8f760d2b52a080">tvm::runtime::DiscoWorker</a></li>
<li>DiscoWorker::Impl : <a class="el" href="classtvm_1_1runtime_1_1DiscoWorker.html#a379c6dd5a183ed1df75515f7f21a3f49">tvm::runtime::DiscoWorker</a></li>
-<li>Dispatch() : <a class="el" href="classtvm_1_1ExprFunctor_3_01R_07const_01Expr_01_6_00_01Args_8_8_8_08_4.html#a8b267961edf7db8ed2eea10db0964932">tvm::ExprFunctor< R(const Expr &, Args...)></a></li>
-<li>dispatch : <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#a9463aa1e349fdaa77ee00318eda01047">tvm::script::printer::OpCallDocNode</a></li>
-<li>Dispatch() : <a class="el" href="classtvm_1_1tirx_1_1StmtFunctor_3_01R_07const_01Stmt_01_6_00_01Args_8_8_8_08_4.html#afe2459adeed04fc2dadd0c7195de9a94">tvm::tirx::StmtFunctor< R(const Stmt &, Args...)></a></li>
+<li>Dispatch() : <a class="el" href="classtvm_1_1ExprFunctor_3_01R_07const_01Expr_01_6_00_01Args_8_8_8_08_4.html#a8b267961edf7db8ed2eea10db0964932">tvm::ExprFunctor< R(const Expr &, Args...)></a>, <a class="el" href="classtvm_1_1tirx_1_1StmtFunctor_3_01R_07const_01Stmt_01_6_00_01Args_8_8_8_08_4.html#afe2459adeed04fc2dadd0c7195de9a94">tvm::tirx::StmtFunctor< R(const Stmt &, Args...)></a></li>
<li>Dispatch_() : <a class="el" href="classtvm_1_1ExprFunctor_3_01R_07const_01Expr_01_6_00_01Args_8_8_8_08_4.html#ae7c1f64e45937ce0ca299c9841cc64aa">tvm::ExprFunctor< R(const Expr &, Args...)></a>, <a class="el" href="classtvm_1_1s__tir_1_1StmtFunctor_3_01R_07const_01Stmt_01_6_00_01Args_8_8_8_08_4.html#a786d4cbf0189d554d062d6140bab7105">tvm::s_tir::StmtFunctor< R(const Stmt &, Args...)></a>, <a class="el" href="classtvm_1_1tirx_1_1StmtFunctor_3_01R_07const_0 [...]
<li>DispatchContext() : <a class="el" href="classtvm_1_1tirx_1_1DispatchContext.html#a1fdf4c8b2157474c5d4ed1934bf96180">tvm::tirx::DispatchContext</a></li>
<li>DispatchDefault_() : <a class="el" href="classtvm_1_1ExprFunctor_3_01R_07const_01Expr_01_6_00_01Args_8_8_8_08_4.html#a49bf8ac54583bb0b30725a4dd76c2a18">tvm::ExprFunctor< R(const Expr &, Args...)></a>, <a class="el" href="classtvm_1_1tirx_1_1StmtFunctor_3_01R_07const_01Stmt_01_6_00_01Args_8_8_8_08_4.html#a940a20c15f7997ff74477f8450144816">tvm::tirx::StmtFunctor< R(const Stmt &, Args...)></a></li>
diff --git a/docs/reference/api/doxygen/functions_func_c.html b/docs/reference/api/doxygen/functions_func_c.html
index c95d3359e00..d81fe47196f 100644
--- a/docs/reference/api/doxygen/functions_func_c.html
+++ b/docs/reference/api/doxygen/functions_func_c.html
@@ -79,7 +79,7 @@ $(function() {
<li>Call() : <a class="el" href="classtvm_1_1Call.html#a26304eac4f5299ac4b4862105a9f5cd5">tvm::Call</a>, <a class="el" href="structtvm_1_1runtime_1_1vm_1_1Instruction.html#a70b9e9c1632058a9bfbaecb00a2926c2">tvm::runtime::vm::Instruction</a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1ExprDocNode.html#a84661ae5560b5daf2084443fb8c93e1d">tvm::script::printer::ExprDocNode</a></li>
<li>CallDoc() : <a class="el" href="classtvm_1_1script_1_1printer_1_1CallDoc.html#ae26a9378550bb5750464fd299b33e9ed">tvm::script::printer::CallDoc</a></li>
<li>CallNode() : <a class="el" href="classtvm_1_1CallNode.html#adf837eb3faa5535c97311eb0f2ccb0e0">tvm::CallNode</a></li>
-<li>CallPacked() : <a class="el" href="classtvm_1_1runtime_1_1SessionObj.html#a3e5a412f242d3e466f9b359852fcc0fa">tvm::runtime::SessionObj</a></li>
+<li>CallPacked() : <a class="el" href="classtvm_1_1runtime_1_1SessionObj.html#af5afdb77fe43ac0591c872648ee820d4">tvm::runtime::SessionObj</a></li>
<li>CallPattern() : <a class="el" href="classtvm_1_1relax_1_1CallPattern.html#ac023536d9162e5dad42e100b8aa829b9">tvm::relax::CallPattern</a></li>
<li>CallSiteLoc() : <a class="el" href="classtvm_1_1CallSiteLoc.html#ae2aae7fd46c6fc066082e3000fc361b2">tvm::CallSiteLoc</a></li>
<li>CallWithPacked() : <a class="el" href="classtvm_1_1runtime_1_1SessionObj.html#a10bd253529384336ccf3aab3ece98882">tvm::runtime::SessionObj</a></li>
@@ -126,15 +126,15 @@ $(function() {
<li>Continue() : <a class="el" href="classtvm_1_1Continue.html#ac8c135897f6026ccf33c8d8c02ff8827">tvm::Continue</a></li>
<li>ContinueDoc() : <a class="el" href="classtvm_1_1script_1_1printer_1_1ContinueDoc.html#a3cd20ba5a6587b7d19bfc72e451985bb">tvm::script::printer::ContinueDoc</a></li>
<li>ConvertConstant() : <a class="el" href="classtvm_1_1relax_1_1ExecBuilderNode.html#ac0323caf936e8dc48bcffb6e04a825e8">tvm::relax::ExecBuilderNode</a></li>
-<li>ConvertFallbackValue() : <a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01Expr_01_4.html#a6f4773ee3e012981e082c428d06c5b4d">tvm::ffi::TypeTraits< Expr ></a>, <a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01FloatImm_01_4.html#a2d1f8eb0eaebb896586a4f6914ef1596">tvm::ffi::TypeTraits< FloatImm ></a>, <a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01IntExpr_01_4.html#a04e5c69ff8fe02aeae0407d31441da67">tvm::ffi::TypeTraits< IntExpr ></a>, <a c [...]
+<li>ConvertFallbackValue() : <a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01Expr_01_4.html#a6f4773ee3e012981e082c428d06c5b4d">tvm::ffi::TypeTraits< Expr ></a>, <a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01FloatImm_01_4.html#a2d1f8eb0eaebb896586a4f6914ef1596">tvm::ffi::TypeTraits< FloatImm ></a>, <a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01IntExpr_01_4.html#a04e5c69ff8fe02aeae0407d31441da67">tvm::ffi::TypeTraits< IntExpr ></a>, <a c [...]
<li>Copy() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#a9f97ca31fd603a33ac6d7e688f018201">tvm::s_tir::ScheduleNode</a></li>
-<li>CopyDataFromTo() : <a class="el" href="classtvm_1_1runtime_1_1DeviceAPI.html#a2f8bed30e62ddd50f02989cbd8a03824">tvm::runtime::DeviceAPI</a></li>
+<li>CopyDataFromTo() : <a class="el" href="classtvm_1_1runtime_1_1DeviceAPI.html#ada4c726e7885d4cb3b83dafd8418fa13">tvm::runtime::DeviceAPI</a></li>
<li>CopyFrom() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#a6ae739044fd444403bf0a013c5bcd71e">tvm::runtime::Tensor</a></li>
<li>CopyFromBytes() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#ab906e1a006435e988b0e3262bf605da9">tvm::runtime::Tensor</a></li>
<li>CopyFromTo() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#aa215b42c46dd617a25f8240aa5dbb1b5">tvm::runtime::Tensor</a></li>
<li>CopyFromWorker0() : <a class="el" href="classtvm_1_1runtime_1_1SessionObj.html#a6dcb310d5c3a8ca38aaedac7c9d1456d">tvm::runtime::SessionObj</a></li>
<li>CopyOnWrite() : <a class="el" href="classtvm_1_1relax_1_1BindingBlock.html#a974926705d8c711b39f14a3eecd06823">tvm::relax::BindingBlock</a></li>
-<li>CopyTo() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#a7590ee11d02a8e2da8ac1b55f8d752bc">tvm::runtime::Tensor</a></li>
+<li>CopyTo() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#a9470fc8dc75556e8a0ff7b9b7d76537a">tvm::runtime::Tensor</a></li>
<li>CopyToBytes() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#a22c2884b50b94c6d3731ad88e1a5848b">tvm::runtime::Tensor</a></li>
<li>CopyToWorker0() : <a class="el" href="classtvm_1_1runtime_1_1SessionObj.html#a49c2c7066fff2cb998ba6aedf4f3b9c3">tvm::runtime::SessionObj</a></li>
<li>CopyWithDType() : <a class="el" href="classtvm_1_1PrimVar.html#a982fc1e284ee1f0505439b686b34afb9">tvm::PrimVar</a>, <a class="el" href="classtvm_1_1Var.html#a3930c2126518b3b0d8810ca39576759c">tvm::Var</a></li>
diff --git a/docs/reference/api/doxygen/functions_func_g.html b/docs/reference/api/doxygen/functions_func_g.html
index 1ab3c6cfc7d..2e2c31c46ee 100644
--- a/docs/reference/api/doxygen/functions_func_g.html
+++ b/docs/reference/api/doxygen/functions_func_g.html
@@ -79,8 +79,8 @@ $(function() {
<li>get() : <a class="el" href="classtvm_1_1DictAttrs.html#ad8f7996b9debb6eb1bf729251f3b78b3">tvm::DictAttrs</a></li>
<li>Get() : <a class="el" href="classtvm_1_1EnvFunc.html#a4743fb115d189998a1c92f267de91272">tvm::EnvFunc</a>, <a class="el" href="classtvm_1_1Op.html#a3b206bfa4134d41a4001b7915d05dff5">tvm::Op</a></li>
<li>get() : <a class="el" href="classtvm_1_1OpAttrMap.html#adbee48a3d975f50cc812fec1a4543eaa">tvm::OpAttrMap< ValueType ></a>, <a class="el" href="classtvm_1_1relax_1_1Binding.html#af3305881e12b4a6f2d1013a04060fadd">tvm::relax::Binding</a></li>
-<li>Get() : <a class="el" href="classtvm_1_1relax_1_1ExecBuilderNode.html#a73c216f7f77ba02083adb8483551ed55">tvm::relax::ExecBuilderNode</a>, <a class="el" href="classtvm_1_1runtime_1_1DeviceAPI.html#a2b100fe3a7f95c2d11376ae3b2fdb6a2">tvm::runtime::DeviceAPI</a>, <a class="el" href="structtvm_1_1runtime_1_1ThreadLocalDiscoWorker.html#a69a26e7fced7ff0a61faf48d9a5d8dc5">tvm::runtime::ThreadLocalDiscoWorker</a>, <a class="el" href="classtvm_1_1s__tir_1_1InstructionKind.html#a7c41f [...]
-<li>get() : <a class="el" href="classtvm_1_1tirx_1_1TensorVar.html#a7be51b1e4832a1dd37187cd29da72fde">tvm::tirx::TensorVar</a>, <a class="el" href="classtvm_1_1With.html#ab35df63e7c2a021c1656131f627adb60">tvm::With< ContextType ></a></li>
+<li>Get() : <a class="el" href="classtvm_1_1relax_1_1ExecBuilderNode.html#a73c216f7f77ba02083adb8483551ed55">tvm::relax::ExecBuilderNode</a>, <a class="el" href="classtvm_1_1runtime_1_1DeviceAPI.html#a2b100fe3a7f95c2d11376ae3b2fdb6a2">tvm::runtime::DeviceAPI</a>, <a class="el" href="structtvm_1_1runtime_1_1ThreadLocalDiscoWorker.html#a69a26e7fced7ff0a61faf48d9a5d8dc5">tvm::runtime::ThreadLocalDiscoWorker</a>, <a class="el" href="classtvm_1_1s__tir_1_1InstructionKind.html#a7c41f [...]
+<li>get() : <a class="el" href="classtvm_1_1tirx_1_1TensorVar.html#a7be51b1e4832a1dd37187cd29da72fde">tvm::tirx::TensorVar</a>, <a class="el" href="classtvm_1_1With.html#aeba9bd793f52d87f0d1635cccf7bd337">tvm::With< ContextType ></a></li>
<li>GetAllocator() : <a class="el" href="classtvm_1_1runtime_1_1memory_1_1MemoryManager.html#adf54a15a89cdfc4698c1a5a95542e407">tvm::runtime::memory::MemoryManager</a></li>
<li>GetAllTuningRecords() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1DatabaseNode.html#af2b0a7e2305c8222d02971ea4b3c66fa">tvm::s_tir::meta_schedule::DatabaseNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1PyDatabaseNode.html#af2898ac3be0dd1ccf587b7671e593e40">tvm::s_tir::meta_schedule::PyDatabaseNode</a></li>
<li>GetAnalyzer() : <a class="el" href="classtvm_1_1relax_1_1BlockBuilderNode.html#a8562b7497e5f1032aa86f7eee0867e5a">tvm::relax::BlockBuilderNode</a></li>
diff --git a/docs/reference/api/doxygen/functions_func_o.html b/docs/reference/api/doxygen/functions_func_o.html
index 4b059b73a2b..b88130ad441 100644
--- a/docs/reference/api/doxygen/functions_func_o.html
+++ b/docs/reference/api/doxygen/functions_func_o.html
@@ -80,8 +80,7 @@ $(function() {
<li>OpaqueExpr() : <a class="el" href="classtvm_1_1OpaqueExpr.html#afd17da96046bfe1522adcd996454818a">tvm::OpaqueExpr</a></li>
<li>OpaqueFunc() : <a class="el" href="classtvm_1_1relax_1_1FuncType.html#a56b337d9d4d107eaa00b973cfcdd17fc">tvm::relax::FuncType</a></li>
<li>OpaqueType() : <a class="el" href="classtvm_1_1OpaqueType.html#a6c374ff2d7cb64952ec2e7067e438d8f">tvm::OpaqueType</a></li>
-<li>OpCallDoc() : <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#ab5b4f91b550e6e9b43f8a5659604da42">tvm::script::printer::OpCallDoc</a></li>
-<li>OpDef() : <a class="el" href="classtvm_1_1OpDef.html#ae559110ef55e803c57acae0a17e1e4e5">tvm::OpDef</a></li>
+<li>OpDef() : <a class="el" href="classtvm_1_1OpDef.html#a8e02417e15311a6c0955146acf2074f8">tvm::OpDef</a></li>
<li>Operation() : <a class="el" href="classtvm_1_1te_1_1Operation.html#a7bc69f793cb5cbc99bf20fed8617d487">tvm::te::Operation</a></li>
<li>OperationDoc() : <a class="el" href="classtvm_1_1script_1_1printer_1_1OperationDoc.html#a4cb1202058caaf27c3ed6f2951af28e3">tvm::script::printer::OperationDoc</a></li>
<li>operator PatternSeq() : <a class="el" href="classtvm_1_1relax_1_1DFPattern.html#afce09ce23acba783755ac41f21145b0f">tvm::relax::DFPattern</a></li>
@@ -89,7 +88,7 @@ $(function() {
<li>operator Var() : <a class="el" href="classtvm_1_1PrimVar.html#aa0bcffe86bfbe598728e862a15f4f4b3">tvm::PrimVar</a></li>
<li>operator!=() : <a class="el" href="classtvm_1_1Expr.html#a86bd9da75268e479e3bbe61729dce8ac">tvm::Expr</a>, <a class="el" href="classtvm_1_1relax_1_1NestedMsg.html#ae2848ef30c8566feec482c045bd27673">tvm::relax::NestedMsg< T ></a>, <a class="el" href="classtvm_1_1te_1_1Tensor.html#a9b3e114d34dda7e093663a9a9548140f">tvm::te::Tensor</a></li>
<li>operator&() : <a class="el" href="classtvm_1_1relax_1_1DFPattern.html#a935b45987613932342fba50b4f809834">tvm::relax::DFPattern</a></li>
-<li>operator()() : <a class="el" href="classtvm_1_1EnvFunc.html#ae3e0102263bfb4741599a06c627814cb">tvm::EnvFunc</a>, <a class="el" href="classtvm_1_1ExprFunctor_3_01R_07const_01Expr_01_6_00_01Args_8_8_8_08_4.html#a8e6a3f03309c393f7700f594ed68afda">tvm::ExprFunctor< R(const Expr &, Args...)></a>, <a class="el" href="classtvm_1_1ObjectFunctor_3_01R_07NodeArg_00_01Args_8_8_8_08_4.html#a832a7c23af840d60ec067b1475e72ee9">tvm::ObjectFunctor< R(NodeArg, Args...)></a>, [...]
+<li>operator()() : <a class="el" href="classtvm_1_1EnvFunc.html#ae3e0102263bfb4741599a06c627814cb">tvm::EnvFunc</a>, <a class="el" href="classtvm_1_1ExprFunctor_3_01R_07const_01Expr_01_6_00_01Args_8_8_8_08_4.html#a8e6a3f03309c393f7700f594ed68afda">tvm::ExprFunctor< R(const Expr &, Args...)></a>, <a class="el" href="classtvm_1_1ObjectFunctor_3_01R_07NodeArg_00_01Args_8_8_8_08_4.html#a832a7c23af840d60ec067b1475e72ee9">tvm::ObjectFunctor< R(NodeArg, Args...)></a>, [...]
<li>operator*() : <a class="el" href="classtvm_1_1With.html#aa5cf1df354008179241e268deaa5a2eb">tvm::With< ContextType ></a></li>
<li>operator->() : <a class="el" href="classtvm_1_1DictAttrs.html#a49deabd670cdf006037faba59a79ed34">tvm::DictAttrs</a>, <a class="el" href="classtvm_1_1EnvFunc.html#ad715c2b953c2f7ed0c5b4577fbb5c7e3">tvm::EnvFunc</a>, <a class="el" href="classtvm_1_1IRModule.html#aa659bf3e65fb7b1351b5be8826924e66">tvm::IRModule</a>, <a class="el" href="classtvm_1_1relax_1_1Binding.html#ab23c4b7cf09ff329b94ebb90e11d23f7">tvm::relax::Binding</a>, <a class="el" href="classtvm_1_1relax_1_1Dataf [...]
<li>operator<() : <a class="el" href="classtvm_1_1Expr.html#afb14020d9ae652a64a6f15dcba073c0e">tvm::Expr</a></li>
diff --git a/docs/reference/api/doxygen/functions_func_r.html b/docs/reference/api/doxygen/functions_func_r.html
index 02238627580..6aafc1d244a 100644
--- a/docs/reference/api/doxygen/functions_func_r.html
+++ b/docs/reference/api/doxygen/functions_func_r.html
@@ -94,7 +94,7 @@ $(function() {
<li>RegisterAttrValidator() : <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1tirx_1_1FunctionFrameNode.html#a7dd7e92a47fad94c39b5071c14a9c7e8">tvm::script::ir_builder::tirx::FunctionFrameNode</a></li>
<li>RegisterConfigOption() : <a class="el" href="classtvm_1_1transform_1_1PassContext.html#a2618668ab11d8604c7c9a93e0ec527d2">tvm::transform::PassContext</a></li>
<li>RegisterOrGet() : <a class="el" href="classtvm_1_1TargetKindRegistry.html#a6123b4525e715d7353e445fa5f9b2165">tvm::TargetKindRegistry</a></li>
-<li>RegisterReflection() : <a class="el" href="classtvm_1_1AnyTypeNode.html#a690f7c61281e3bad083941de759696f8">tvm::AnyTypeNode</a>, <a class="el" href="classtvm_1_1ArgumentInfoNode.html#a3f35036e53337a3a86ee7ca34235f4fa">tvm::ArgumentInfoNode</a>, <a class="el" href="classtvm_1_1AssertStmtNode.html#a0080cbf046fc715b400b0ed5d6ad055a">tvm::AssertStmtNode</a>, <a class="el" href="structtvm_1_1backend_1_1cuda_1_1TCGen05InstrDescriptorAttrs.html#a45c9818d95451ccf4eb79c0c3b5b6116">t [...]
+<li>RegisterReflection() : <a class="el" href="classtvm_1_1AnyTypeNode.html#a690f7c61281e3bad083941de759696f8">tvm::AnyTypeNode</a>, <a class="el" href="classtvm_1_1ArgumentInfoNode.html#a3f35036e53337a3a86ee7ca34235f4fa">tvm::ArgumentInfoNode</a>, <a class="el" href="classtvm_1_1AssertStmtNode.html#a0080cbf046fc715b400b0ed5d6ad055a">tvm::AssertStmtNode</a>, <a class="el" href="structtvm_1_1backend_1_1cuda_1_1TCGen05InstrDescriptorAttrs.html#a45c9818d95451ccf4eb79c0c3b5b6116">t [...]
<li>ReIndex() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#a2cb4cef0537e66429d40860594780aaa">tvm::s_tir::ScheduleNode</a></li>
<li>ReindexCacheRead() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#ae521878b0f82d4dcf4932b34c0f11476">tvm::s_tir::ScheduleNode</a></li>
<li>ReindexCacheWrite() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#ac2cdcd319867c595140eb958e28b4173">tvm::s_tir::ScheduleNode</a></li>
diff --git a/docs/reference/api/doxygen/functions_func_t.html b/docs/reference/api/doxygen/functions_func_t.html
index d1e7e035550..09bd1a61ca7 100644
--- a/docs/reference/api/doxygen/functions_func_t.html
+++ b/docs/reference/api/doxygen/functions_func_t.html
@@ -131,11 +131,11 @@ $(function() {
<li>TupleTypeNode() : <a class="el" href="classtvm_1_1TupleTypeNode.html#a1e9cbe8e91816366c181fb888ddc18d9">tvm::TupleTypeNode</a></li>
<li>TVM_DEFINE_OBJECT_REF_COW_METHOD() : <a class="el" href="classtvm_1_1AssertStmt.html#a401d1c786573cba184a5053bed4a7168">tvm::AssertStmt</a>, <a class="el" href="classtvm_1_1Bind.html#a2e0a42528e5b2510f08d3ff3c43d34ba">tvm::Bind</a>, <a class="el" href="classtvm_1_1Break.html#aacfb1c86342879e973b81c1343f3dffe">tvm::Break</a>, <a class="el" href="classtvm_1_1Call.html#ac7f8d11aa54e549a1154d2d2bd25c461">tvm::Call</a>, <a class="el" href="classtvm_1_1Continue.html#a17b5846e008e [...]
<li>TVM_FFI_DECLARE_OBJECT_INFO() : <a class="el" href="classtvm_1_1AttrsNode.html#ae4806aea36c99253f52625489497803e">tvm::AttrsNode</a>, <a class="el" href="classtvm_1_1BaseFuncNode.html#a92a7f720142c275784235eb9905ee835">tvm::BaseFuncNode</a>, <a class="el" href="classtvm_1_1ConstantNode.html#a7ac1b77b387c65100e701bc11dc958e0">tvm::ConstantNode</a>, <a class="el" href="classtvm_1_1ExprNode.html#a79424fe36b005bfd36e56dfcfcb4a118">tvm::ExprNode</a>, <a class="el" href="classtvm [...]
-<li>TVM_FFI_DECLARE_OBJECT_INFO_FINAL() : <a class="el" href="classtvm_1_1AnyTypeNode.html#a1c2008016781a41f62c803986aaad81f">tvm::AnyTypeNode</a>, <a class="el" href="classtvm_1_1ArgumentInfoNode.html#ad5d4e5da3f0998f96b3155ae48b844cc">tvm::ArgumentInfoNode</a>, <a class="el" href="classtvm_1_1AssertStmtNode.html#ae06276577882fd897fac8ad3b2b0398b">tvm::AssertStmtNode</a>, <a class="el" href="structtvm_1_1backend_1_1cuda_1_1TCGen05InstrDescriptorAttrs.html#ae268a401d28b4d0221b1 [...]
+<li>TVM_FFI_DECLARE_OBJECT_INFO_FINAL() : <a class="el" href="classtvm_1_1AnyTypeNode.html#a1c2008016781a41f62c803986aaad81f">tvm::AnyTypeNode</a>, <a class="el" href="classtvm_1_1ArgumentInfoNode.html#ad5d4e5da3f0998f96b3155ae48b844cc">tvm::ArgumentInfoNode</a>, <a class="el" href="classtvm_1_1AssertStmtNode.html#ae06276577882fd897fac8ad3b2b0398b">tvm::AssertStmtNode</a>, <a class="el" href="structtvm_1_1backend_1_1cuda_1_1TCGen05InstrDescriptorAttrs.html#ae268a401d28b4d0221b1 [...]
<li>TVM_FFI_DECLARE_OBJECT_INFO_PREDEFINED_TYPE_KEY() : <a class="el" href="classtvm_1_1prim_1_1BinaryOpNode.html#a4ea9d6d505a52f8c48703981630df05c">tvm::prim::BinaryOpNode< T ></a>, <a class="el" href="classtvm_1_1prim_1_1CmpOpNode.html#a6f8cddcdbc85626674cffa6d59c585d7">tvm::prim::CmpOpNode< T ></a></li>
<li>TVM_FFI_DECLARE_OBJECT_INFO_STATIC() : <a class="el" href="classtvm_1_1runtime_1_1DRefObj.html#a18ed3c1a2f001484e33295fd0b7476aa">tvm::runtime::DRefObj</a></li>
<li>TVM_FFI_DEFINE_DEFAULT_COPY_MOVE_AND_ASSIGN() : <a class="el" href="classtvm_1_1tirx_1_1TensorVar.html#a706fea2f129ede37fe7980fda59a3bd1">tvm::tirx::TensorVar</a></li>
-<li>TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE() : <a class="el" href="classtvm_1_1AnyType.html#a801577ea879428083b5da2e81a58e62f">tvm::AnyType</a>, <a class="el" href="classtvm_1_1AssertStmt.html#a701cd68f5cd3422d0b868f538d1686c4">tvm::AssertStmt</a>, <a class="el" href="classtvm_1_1BaseFunc.html#a496463fef22ee43ebd9ace59626a0348">tvm::BaseFunc</a>, <a class="el" href="classtvm_1_1Bind.html#a62bd2536776c6a0c835d49b58749b2b9">tvm::Bind</a>, <a class="el" href="classtvm_1_1Br [...]
+<li>TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE() : <a class="el" href="classtvm_1_1AnyType.html#a801577ea879428083b5da2e81a58e62f">tvm::AnyType</a>, <a class="el" href="classtvm_1_1AssertStmt.html#a701cd68f5cd3422d0b868f538d1686c4">tvm::AssertStmt</a>, <a class="el" href="classtvm_1_1BaseFunc.html#a496463fef22ee43ebd9ace59626a0348">tvm::BaseFunc</a>, <a class="el" href="classtvm_1_1Bind.html#a62bd2536776c6a0c835d49b58749b2b9">tvm::Bind</a>, <a class="el" href="classtvm_1_1Br [...]
<li>TVM_FFI_DEFINE_OBJECT_REF_METHODS_NULLABLE() : <a class="el" href="classtvm_1_1ArgumentInfo.html#ad079f3045ac104e7107ebc3197447462">tvm::ArgumentInfo</a>, <a class="el" href="classtvm_1_1Attrs.html#af88d2fff186ab0af971db3a281cae1ce">tvm::Attrs</a>, <a class="el" href="classtvm_1_1GlobalInfo.html#af82b716ca0477f2bd23aa4a526466126">tvm::GlobalInfo</a>, <a class="el" href="classtvm_1_1Range.html#a592353a8a4642af3d8e26d246436d37e">tvm::Range</a>, <a class="el" href="classtvm_1_ [...]
<li>ty() : <a class="el" href="classtvm_1_1TypedExpr.html#a7d83b1f31a1cc6f0774df309e207e678">tvm::TypedExpr< ExpectedType ></a></li>
<li>type() : <a class="el" href="classtvm_1_1runtime_1_1memory_1_1Allocator.html#a5690ce0a8e9e25bd8e5568173cc0b1bb">tvm::runtime::memory::Allocator</a>, <a class="el" href="classtvm_1_1tirx_1_1TensorVar.html#a42fcd94536191d8b98f75a6a0bfc3f7a">tvm::tirx::TensorVar</a></li>
diff --git a/docs/reference/api/doxygen/functions_g.html b/docs/reference/api/doxygen/functions_g.html
index 03a91a8b354..acdca8994af 100644
--- a/docs/reference/api/doxygen/functions_g.html
+++ b/docs/reference/api/doxygen/functions_g.html
@@ -79,8 +79,8 @@ $(function() {
<li>get() : <a class="el" href="classtvm_1_1DictAttrs.html#ad8f7996b9debb6eb1bf729251f3b78b3">tvm::DictAttrs</a></li>
<li>Get() : <a class="el" href="classtvm_1_1EnvFunc.html#a4743fb115d189998a1c92f267de91272">tvm::EnvFunc</a>, <a class="el" href="classtvm_1_1Op.html#a3b206bfa4134d41a4001b7915d05dff5">tvm::Op</a></li>
<li>get() : <a class="el" href="classtvm_1_1OpAttrMap.html#adbee48a3d975f50cc812fec1a4543eaa">tvm::OpAttrMap< ValueType ></a>, <a class="el" href="classtvm_1_1relax_1_1Binding.html#af3305881e12b4a6f2d1013a04060fadd">tvm::relax::Binding</a></li>
-<li>Get() : <a class="el" href="classtvm_1_1relax_1_1ExecBuilderNode.html#a73c216f7f77ba02083adb8483551ed55">tvm::relax::ExecBuilderNode</a>, <a class="el" href="classtvm_1_1runtime_1_1DeviceAPI.html#a2b100fe3a7f95c2d11376ae3b2fdb6a2">tvm::runtime::DeviceAPI</a>, <a class="el" href="structtvm_1_1runtime_1_1ThreadLocalDiscoWorker.html#a69a26e7fced7ff0a61faf48d9a5d8dc5">tvm::runtime::ThreadLocalDiscoWorker</a>, <a class="el" href="classtvm_1_1s__tir_1_1InstructionKind.html#a7c41f [...]
-<li>get() : <a class="el" href="classtvm_1_1tirx_1_1TensorVar.html#a7be51b1e4832a1dd37187cd29da72fde">tvm::tirx::TensorVar</a>, <a class="el" href="classtvm_1_1With.html#ab35df63e7c2a021c1656131f627adb60">tvm::With< ContextType ></a></li>
+<li>Get() : <a class="el" href="classtvm_1_1relax_1_1ExecBuilderNode.html#a73c216f7f77ba02083adb8483551ed55">tvm::relax::ExecBuilderNode</a>, <a class="el" href="classtvm_1_1runtime_1_1DeviceAPI.html#a2b100fe3a7f95c2d11376ae3b2fdb6a2">tvm::runtime::DeviceAPI</a>, <a class="el" href="structtvm_1_1runtime_1_1ThreadLocalDiscoWorker.html#a69a26e7fced7ff0a61faf48d9a5d8dc5">tvm::runtime::ThreadLocalDiscoWorker</a>, <a class="el" href="classtvm_1_1s__tir_1_1InstructionKind.html#a7c41f [...]
+<li>get() : <a class="el" href="classtvm_1_1tirx_1_1TensorVar.html#a7be51b1e4832a1dd37187cd29da72fde">tvm::tirx::TensorVar</a>, <a class="el" href="classtvm_1_1With.html#aeba9bd793f52d87f0d1635cccf7bd337">tvm::With< ContextType ></a></li>
<li>get_implicit_defs : <a class="el" href="structtvm_1_1script_1_1printer_1_1DocTranslatorVTable.html#af9d494dc72a2ee56d8b2903c660241bd">tvm::script::printer::DocTranslatorVTable</a></li>
<li>GetAllocator() : <a class="el" href="classtvm_1_1runtime_1_1memory_1_1MemoryManager.html#adf54a15a89cdfc4698c1a5a95542e407">tvm::runtime::memory::MemoryManager</a></li>
<li>GetAllTuningRecords() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1DatabaseNode.html#af2b0a7e2305c8222d02971ea4b3c66fa">tvm::s_tir::meta_schedule::DatabaseNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1PyDatabaseNode.html#af2898ac3be0dd1ccf587b7671e593e40">tvm::s_tir::meta_schedule::PyDatabaseNode</a></li>
diff --git a/docs/reference/api/doxygen/functions_i.html b/docs/reference/api/doxygen/functions_i.html
index b4827dae98d..eb21dc3ed0c 100644
--- a/docs/reference/api/doxygen/functions_i.html
+++ b/docs/reference/api/doxygen/functions_i.html
@@ -80,7 +80,7 @@ $(function() {
<li>IfExpr() : <a class="el" href="classtvm_1_1relax_1_1IfExpr.html#a49940cd017c27d91996a9b074b58d655">tvm::relax::IfExpr</a></li>
<li>IfExprNode() : <a class="el" href="classtvm_1_1relax_1_1IfExprNode.html#a55ca891d9d4cba196c5f06dd487a342b">tvm::relax::IfExprNode</a></li>
<li>IfFrame() : <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1ir_1_1IfFrame.html#a8338fb3df01c06e28cddc8b39123a1ac">tvm::script::ir_builder::ir::IfFrame</a>, <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1relax_1_1IfFrame.html#abd5e125b569a7f39be94aadb6c4d5286">tvm::script::ir_builder::relax::IfFrame</a></li>
-<li>IfFrameNode() : <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1ir_1_1IfFrameNode.html#a5ef6a96bf59d1bfeb41ca7b54f9bcb3b">tvm::script::ir_builder::ir::IfFrameNode</a>, <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1relax_1_1IfFrameNode.html#ab9f377825f41a88f1267fcb5e589ce46">tvm::script::ir_builder::relax::IfFrameNode</a></li>
+<li>IfFrameNode() : <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1ir_1_1IfFrameNode.html#a99081e2338a38138e5f50f87626d9ea0">tvm::script::ir_builder::ir::IfFrameNode</a>, <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1relax_1_1IfFrameNode.html#a7afbfae19e6f56825e3af3639b3f7283">tvm::script::ir_builder::relax::IfFrameNode</a></li>
<li>IfNode() : <a class="el" href="classtvm_1_1IfNode.html#a717f270aedf170e267871eaf6a4187b4">tvm::IfNode</a></li>
<li>ignore_index : <a class="el" href="structtvm_1_1relax_1_1NLLLossAttrs.html#a87e28de97dd6dca1a8938de0258cbd0c">tvm::relax::NLLLossAttrs</a></li>
<li>Immediate() : <a class="el" href="classtvm_1_1runtime_1_1vm_1_1Instruction_1_1Arg.html#a596cc51f4b7267e37c8bdfb4bf815ce7">tvm::runtime::vm::Instruction::Arg</a></li>
@@ -98,7 +98,7 @@ $(function() {
<li>IndexMap() : <a class="el" href="classtvm_1_1tirx_1_1IndexMap.html#a3a3b7f1bc73d27c42b03a796e32f3f2f">tvm::tirx::IndexMap</a></li>
<li>IndexMapNode() : <a class="el" href="classtvm_1_1tirx_1_1IndexMapNode.html#a5a248dc1754f4ab7542649d239f5385c">tvm::tirx::IndexMapNode</a></li>
<li>IndexOf() : <a class="el" href="classtvm_1_1tirx_1_1SLayout.html#a0b8b58402c140e48bad57a9828913a55">tvm::tirx::SLayout</a></li>
-<li>IndexWithNegativeIndices() : <a class="el" href="classtvm_1_1te_1_1Tensor.html#a13b0c7e854e12eb1ee7420cd9e96e7a2">tvm::te::Tensor</a></li>
+<li>IndexWithNegativeIndices() : <a class="el" href="classtvm_1_1te_1_1Tensor.html#a1727a7e0ad4c9c74f17763d3b5e694b6">tvm::te::Tensor</a></li>
<li>indices : <a class="el" href="classtvm_1_1prim_1_1ShuffleNode.html#af32cb091064aaa4d755c2f70ec17f914">tvm::prim::ShuffleNode</a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1IndexDocNode.html#a406f0d327c8b615a7b249c86acb37c90">tvm::script::printer::IndexDocNode</a>, <a class="el" href="classtvm_1_1sym_1_1IterMapResultNode.html#aea207cc301ef8d1ac0118c27e4a31f44">tvm::sym::IterMapResultNode</a>, <a class="el" href="classtvm_1_1TensorLoadNode.html#a306e3757ba3c016463d [...]
<li>indices_or_sections : <a class="el" href="structtvm_1_1relax_1_1SplitAttrs.html#ac1efeac656d482df8cdc3010fca82bcc">tvm::relax::SplitAttrs</a></li>
<li>Info() : <a class="el" href="classtvm_1_1transform_1_1PassNode.html#ab602b215ed172c9f09cf0fa2862858af">tvm::transform::PassNode</a>, <a class="el" href="classtvm_1_1transform_1_1SequentialNode.html#a4873bfc55a74cb39b692884b7b9aa5c2">tvm::transform::SequentialNode</a></li>
diff --git a/docs/reference/api/doxygen/functions_o.html b/docs/reference/api/doxygen/functions_o.html
index 060ac0bb16b..195d90064ae 100644
--- a/docs/reference/api/doxygen/functions_o.html
+++ b/docs/reference/api/doxygen/functions_o.html
@@ -90,29 +90,28 @@ $(function() {
<li>OpaqueFunc() : <a class="el" href="classtvm_1_1relax_1_1FuncType.html#ab0dc03dab6153122672e81d522d00f23">tvm::relax::FuncType</a></li>
<li>OpaqueType() : <a class="el" href="classtvm_1_1OpaqueType.html#a6c374ff2d7cb64952ec2e7067e438d8f">tvm::OpaqueType</a></li>
<li>OpAttrMap : <a class="el" href="classtvm_1_1OpNode.html#a456b137fe45c117890899cb9248d610d">tvm::OpNode</a></li>
-<li>OpCallDoc() : <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html#ab5b4f91b550e6e9b43f8a5659604da42">tvm::script::printer::OpCallDoc</a></li>
<li>OpDef() : <a class="el" href="classtvm_1_1OpDef.html#a33390a82b1c8342781e14b554aeadd8a">tvm::OpDef</a>, <a class="el" href="classtvm_1_1OpNode.html#a37a86f4a96f25f4cfd35717248877f6b">tvm::OpNode</a></li>
<li>operands : <a class="el" href="classtvm_1_1script_1_1printer_1_1OperationDocNode.html#a2d6086cff6613d467c7606a1a71c7e63">tvm::script::printer::OperationDocNode</a></li>
-<li>Operation() : <a class="el" href="classtvm_1_1te_1_1Operation.html#a7bc69f793cb5cbc99bf20fed8617d487">tvm::te::Operation</a></li>
+<li>Operation() : <a class="el" href="classtvm_1_1te_1_1Operation.html#acac0ade4a74dcfd1ebb76971b9a2fbf8">tvm::te::Operation</a></li>
<li>OperationDoc() : <a class="el" href="classtvm_1_1script_1_1printer_1_1OperationDoc.html#a4cb1202058caaf27c3ed6f2951af28e3">tvm::script::printer::OperationDoc</a></li>
<li>operator PatternSeq() : <a class="el" href="classtvm_1_1relax_1_1DFPattern.html#afce09ce23acba783755ac41f21145b0f">tvm::relax::DFPattern</a></li>
<li>operator PrimExpr() : <a class="el" href="classtvm_1_1te_1_1Tensor_1_1Slice.html#ab4d687e16bdccebe425e327fc3f2f4ba">tvm::te::Tensor::Slice</a></li>
<li>operator Var() : <a class="el" href="classtvm_1_1PrimVar.html#aa0bcffe86bfbe598728e862a15f4f4b3">tvm::PrimVar</a></li>
<li>operator!=() : <a class="el" href="classtvm_1_1Expr.html#a86bd9da75268e479e3bbe61729dce8ac">tvm::Expr</a>, <a class="el" href="classtvm_1_1relax_1_1NestedMsg.html#ae2848ef30c8566feec482c045bd27673">tvm::relax::NestedMsg< T ></a>, <a class="el" href="classtvm_1_1te_1_1Tensor.html#a9b3e114d34dda7e093663a9a9548140f">tvm::te::Tensor</a></li>
<li>operator&() : <a class="el" href="classtvm_1_1relax_1_1DFPattern.html#a935b45987613932342fba50b4f809834">tvm::relax::DFPattern</a></li>
-<li>operator()() : <a class="el" href="classtvm_1_1EnvFunc.html#ae3e0102263bfb4741599a06c627814cb">tvm::EnvFunc</a>, <a class="el" href="classtvm_1_1ExprFunctor_3_01R_07const_01Expr_01_6_00_01Args_8_8_8_08_4.html#a8e6a3f03309c393f7700f594ed68afda">tvm::ExprFunctor< R(const Expr &, Args...)></a>, <a class="el" href="classtvm_1_1ObjectFunctor_3_01R_07NodeArg_00_01Args_8_8_8_08_4.html#a832a7c23af840d60ec067b1475e72ee9">tvm::ObjectFunctor< R(NodeArg, Args...)></a>, [...]
+<li>operator()() : <a class="el" href="classtvm_1_1EnvFunc.html#ae3e0102263bfb4741599a06c627814cb">tvm::EnvFunc</a>, <a class="el" href="classtvm_1_1ExprFunctor_3_01R_07const_01Expr_01_6_00_01Args_8_8_8_08_4.html#a8e6a3f03309c393f7700f594ed68afda">tvm::ExprFunctor< R(const Expr &, Args...)></a>, <a class="el" href="classtvm_1_1ObjectFunctor_3_01R_07NodeArg_00_01Args_8_8_8_08_4.html#a832a7c23af840d60ec067b1475e72ee9">tvm::ObjectFunctor< R(NodeArg, Args...)></a>, [...]
<li>operator*() : <a class="el" href="classtvm_1_1With.html#ad3295bc94ed82ce7fee08f89c148a909">tvm::With< ContextType ></a></li>
-<li>operator->() : <a class="el" href="classtvm_1_1DictAttrs.html#a49deabd670cdf006037faba59a79ed34">tvm::DictAttrs</a>, <a class="el" href="classtvm_1_1EnvFunc.html#ad715c2b953c2f7ed0c5b4577fbb5c7e3">tvm::EnvFunc</a>, <a class="el" href="classtvm_1_1IRModule.html#aa659bf3e65fb7b1351b5be8826924e66">tvm::IRModule</a>, <a class="el" href="classtvm_1_1relax_1_1Binding.html#ab23c4b7cf09ff329b94ebb90e11d23f7">tvm::relax::Binding</a>, <a class="el" href="classtvm_1_1relax_1_1Dataf [...]
+<li>operator->() : <a class="el" href="classtvm_1_1DictAttrs.html#a49deabd670cdf006037faba59a79ed34">tvm::DictAttrs</a>, <a class="el" href="classtvm_1_1EnvFunc.html#ad715c2b953c2f7ed0c5b4577fbb5c7e3">tvm::EnvFunc</a>, <a class="el" href="classtvm_1_1IRModule.html#aa659bf3e65fb7b1351b5be8826924e66">tvm::IRModule</a>, <a class="el" href="classtvm_1_1relax_1_1Binding.html#ab23c4b7cf09ff329b94ebb90e11d23f7">tvm::relax::Binding</a>, <a class="el" href="classtvm_1_1relax_1_1Dataf [...]
<li>operator<() : <a class="el" href="classtvm_1_1Expr.html#afb14020d9ae652a64a6f15dcba073c0e">tvm::Expr</a></li>
<li>operator<< : <a class="el" href="structtvm_1_1runtime_1_1vm_1_1Instruction.html#a96e81961242155a0fc04368a7e40f108">tvm::runtime::vm::Instruction</a>, <a class="el" href="classtvm_1_1tirx_1_1SLayout.html#a10de755752d4abaadacd878efd5564bb">tvm::tirx::SLayout</a>, <a class="el" href="classtvm_1_1tirx_1_1SLayoutAxis.html#a3e059e61f3816d17898c490224d58352">tvm::tirx::SLayoutAxis</a></li>
-<li>operator=() : <a class="el" href="classtvm_1_1DictAttrs.html#ab5ead58c71f54fc3413e3decfc5ea25e">tvm::DictAttrs</a>, <a class="el" href="classtvm_1_1ObjectMutator.html#ac281620e7ef712b0d1d782010347b32c">tvm::ObjectMutator</a>, <a class="el" href="classtvm_1_1ObjectVisitor.html#a2ba5c163c86b3c6d75c600cfca5316e8">tvm::ObjectVisitor</a>, <a class="el" href="classtvm_1_1OpDef.html#a4fd0ba9aa4cee8b4df5c498f0352130a">tvm::OpDef</a>, <a class="el" href="classtvm_1_1relax_1_1Binding [...]
+<li>operator=() : <a class="el" href="classtvm_1_1DictAttrs.html#ab5ead58c71f54fc3413e3decfc5ea25e">tvm::DictAttrs</a>, <a class="el" href="classtvm_1_1ObjectMutator.html#ac281620e7ef712b0d1d782010347b32c">tvm::ObjectMutator</a>, <a class="el" href="classtvm_1_1ObjectVisitor.html#a2ba5c163c86b3c6d75c600cfca5316e8">tvm::ObjectVisitor</a>, <a class="el" href="classtvm_1_1OpDef.html#a4fd0ba9aa4cee8b4df5c498f0352130a">tvm::OpDef</a>, <a class="el" href="classtvm_1_1relax_1_1Binding [...]
<li>operator==() : <a class="el" href="classtvm_1_1Expr.html#a637231cfc91838b8f14745ac199b5fbf">tvm::Expr</a>, <a class="el" href="classtvm_1_1relax_1_1NestedMsg.html#a7ff83c8d829af5173621b5ee4083035d">tvm::relax::NestedMsg< T ></a>, <a class="el" href="structtvm_1_1relax_1_1PairCons.html#aa6cbcacb9599e8119f89f814fb5b1b8f">tvm::relax::PairCons</a>, <a class="el" href="classtvm_1_1te_1_1Tensor.html#a1f1bad4907113ec2b508ee0a3c44ed40">tvm::te::Tensor</a>, <a class="el" href= [...]
<li>operator[]() : <a class="el" href="classtvm_1_1OpAttrMap.html#a4fc0b35fb4712e54a43c8a475c417748">tvm::OpAttrMap< ValueType ></a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1ExprDoc.html#a9b9183116fd8d329e1eaf7399653c36e">tvm::script::printer::ExprDoc</a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1ExprDocNode.html#a9ac536aaf8c5e482fcef24da025111bb">tvm::script::printer::ExprDocNode</a>, <a class="el" href="classtvm_1_1SeqStmt.html#ab6abb64244118383 [...]
<li>operator|() : <a class="el" href="classtvm_1_1relax_1_1DFPattern.html#a421011ffe33c4b8406a141a676a0a7e1">tvm::relax::DFPattern</a></li>
<li>operator~() : <a class="el" href="classtvm_1_1relax_1_1DFPattern.html#abce844fe4314f8af18c2a0e38b0dad3b">tvm::relax::DFPattern</a></li>
<li>OpRegistry : <a class="el" href="classtvm_1_1OpNode.html#af7ebaf5af32d51226208f533e6d5cb1d">tvm::OpNode</a></li>
<li>opt_level : <a class="el" href="classtvm_1_1transform_1_1PassContextNode.html#af166034a8746d65044eea0a2673de991">tvm::transform::PassContextNode</a>, <a class="el" href="classtvm_1_1transform_1_1PassInfoNode.html#a8e22e5767cd899bb9aef1ee1c529a2a7">tvm::transform::PassInfoNode</a></li>
-<li>Or() : <a class="el" href="classtvm_1_1prim_1_1Or.html#aa1257f22496020499206210a6c37e054">tvm::prim::Or</a></li>
+<li>Or() : <a class="el" href="classtvm_1_1prim_1_1Or.html#a4c4befcd5780cb449900142e826de9df">tvm::prim::Or</a></li>
<li>OrderedUnionDatabase() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1Database.html#aade8f036b4e9e5d088fe51b23e40ee38">tvm::s_tir::meta_schedule::Database</a></li>
<li>original_fn_ptr_ : <a class="el" href="classtvm_1_1relax_1_1DataflowBlockRewriteNode.html#a20f44bd03d79fcaa77be014a6835bc44">tvm::relax::DataflowBlockRewriteNode</a></li>
<li>OrNode() : <a class="el" href="classtvm_1_1prim_1_1OrNode.html#a46f0030ca61d7834a45b330afe255e96">tvm::prim::OrNode</a></li>
diff --git a/docs/reference/api/doxygen/functions_r.html b/docs/reference/api/doxygen/functions_r.html
index a632496fd09..6d7e1a32e60 100644
--- a/docs/reference/api/doxygen/functions_r.html
+++ b/docs/reference/api/doxygen/functions_r.html
@@ -106,7 +106,7 @@ $(function() {
<li>RegisterAttrValidator() : <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1tirx_1_1FunctionFrameNode.html#a7dd7e92a47fad94c39b5071c14a9c7e8">tvm::script::ir_builder::tirx::FunctionFrameNode</a></li>
<li>RegisterConfigOption() : <a class="el" href="classtvm_1_1transform_1_1PassContext.html#a2618668ab11d8604c7c9a93e0ec527d2">tvm::transform::PassContext</a></li>
<li>RegisterOrGet() : <a class="el" href="classtvm_1_1TargetKindRegistry.html#a6123b4525e715d7353e445fa5f9b2165">tvm::TargetKindRegistry</a></li>
-<li>RegisterReflection() : <a class="el" href="classtvm_1_1AnyTypeNode.html#a690f7c61281e3bad083941de759696f8">tvm::AnyTypeNode</a>, <a class="el" href="classtvm_1_1ArgumentInfoNode.html#a3f35036e53337a3a86ee7ca34235f4fa">tvm::ArgumentInfoNode</a>, <a class="el" href="classtvm_1_1AssertStmtNode.html#a0080cbf046fc715b400b0ed5d6ad055a">tvm::AssertStmtNode</a>, <a class="el" href="structtvm_1_1backend_1_1cuda_1_1TCGen05InstrDescriptorAttrs.html#a45c9818d95451ccf4eb79c0c3b5b6116">t [...]
+<li>RegisterReflection() : <a class="el" href="classtvm_1_1AnyTypeNode.html#a690f7c61281e3bad083941de759696f8">tvm::AnyTypeNode</a>, <a class="el" href="classtvm_1_1ArgumentInfoNode.html#a3f35036e53337a3a86ee7ca34235f4fa">tvm::ArgumentInfoNode</a>, <a class="el" href="classtvm_1_1AssertStmtNode.html#a0080cbf046fc715b400b0ed5d6ad055a">tvm::AssertStmtNode</a>, <a class="el" href="structtvm_1_1backend_1_1cuda_1_1TCGen05InstrDescriptorAttrs.html#a45c9818d95451ccf4eb79c0c3b5b6116">t [...]
<li>ReIndex() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#a2cb4cef0537e66429d40860594780aaa">tvm::s_tir::ScheduleNode</a></li>
<li>ReindexCacheRead() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#ae521878b0f82d4dcf4932b34c0f11476">tvm::s_tir::ScheduleNode</a></li>
<li>ReindexCacheWrite() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#ac2cdcd319867c595140eb958e28b4173">tvm::s_tir::ScheduleNode</a></li>
diff --git a/docs/reference/api/doxygen/functions_s.html b/docs/reference/api/doxygen/functions_s.html
index b45066ced2a..35430edc3ed 100644
--- a/docs/reference/api/doxygen/functions_s.html
+++ b/docs/reference/api/doxygen/functions_s.html
@@ -185,7 +185,7 @@ $(function() {
<li>size : <a class="el" href="structtvm_1_1runtime_1_1memory_1_1Buffer.html#af2afe517225832a1c10252a8034abdd9">tvm::runtime::memory::Buffer</a></li>
<li>Size() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1DatabaseNode.html#a8a86444b56c2ea48a661c535c6986b13">tvm::s_tir::meta_schedule::DatabaseNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1PyDatabaseNode.html#a920db92fd78e012a24ae4921218349b6">tvm::s_tir::meta_schedule::PyDatabaseNode</a></li>
<li>size() : <a class="el" href="classtvm_1_1ScopeStack.html#a553f51623dd0d55317ca023e8cbb2b33">tvm::ScopeStack< T ></a>, <a class="el" href="classtvm_1_1SeqStmt.html#a35ff0b53c6f4411006ef0c25f702e64e">tvm::SeqStmt</a>, <a class="el" href="classtvm_1_1SeqStmtNode.html#acbfca1c16427532747e80175e2815a8a">tvm::SeqStmtNode</a>, <a class="el" href="structtvm_1_1tirx_1_1ActiveSet.html#a411ae885eedcc8dd916b1006914f12f5">tvm::tirx::ActiveSet</a>, <a class="el" href="classtvm_1_1W [...]
-<li>SLayout() : <a class="el" href="classtvm_1_1tirx_1_1SLayout.html#af5d67c1ac260699b1ca637ab2053d37d">tvm::tirx::SLayout</a></li>
+<li>SLayout() : <a class="el" href="classtvm_1_1tirx_1_1SLayout.html#a33961a815fbf438e38c526c3b0de2dc3">tvm::tirx::SLayout</a></li>
<li>Slice() : <a class="el" href="classtvm_1_1te_1_1Tensor_1_1Slice.html#ab314819e8bcca6421e9a4f33e48578c3">tvm::te::Tensor::Slice</a>, <a class="el" href="classtvm_1_1tirx_1_1ComposeLayoutNode.html#a03af3801970aa925d4ccc5ad5dab4ffc">tvm::tirx::ComposeLayoutNode</a>, <a class="el" href="classtvm_1_1tirx_1_1LayoutNode.html#abcf6cd2ebb6dab87215fdca0183b439f">tvm::tirx::LayoutNode</a>, <a class="el" href="classtvm_1_1tirx_1_1TileLayoutNode.html#a1369f26719f092520d1967997d987424">t [...]
<li>SliceDoc() : <a class="el" href="classtvm_1_1script_1_1printer_1_1SliceDoc.html#af2678e96cf9d1c82e4468b6bad8bf4e9">tvm::script::printer::SliceDoc</a></li>
<li>soft_nms_sigma : <a class="el" href="structtvm_1_1relax_1_1NonMaximumSuppressionAttrs.html#a64596b167473f3bc8aff3ddcfd7d4e4b">tvm::relax::NonMaximumSuppressionAttrs</a></li>
diff --git a/docs/reference/api/doxygen/functions_t.html b/docs/reference/api/doxygen/functions_t.html
index fd17f4e177d..ccd483c14be 100644
--- a/docs/reference/api/doxygen/functions_t.html
+++ b/docs/reference/api/doxygen/functions_t.html
@@ -89,7 +89,7 @@ $(function() {
<li>TaskScheduler() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1TaskScheduler.html#a25daa154a4bacc6a29be32301984a22b">tvm::s_tir::meta_schedule::TaskScheduler</a></li>
<li>te_grad_kwargs : <a class="el" href="structtvm_1_1relax_1_1CallTIRWithGradAttrs.html#afad3a6b3d8350e9c02736d09aaf90bd1">tvm::relax::CallTIRWithGradAttrs</a></li>
<li>te_grad_name : <a class="el" href="structtvm_1_1relax_1_1CallTIRWithGradAttrs.html#a9a9a9fa22fc80aff2d71b46e6515879a">tvm::relax::CallTIRWithGradAttrs</a></li>
-<li>Tensor() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#a13828a9652f856b2e654c143cd29eee6">tvm::runtime::Tensor</a>, <a class="el" href="classtvm_1_1te_1_1Tensor.html#af6b777ba59ab1afb6d4da3fb9f38a357">tvm::te::Tensor</a></li>
+<li>Tensor() : <a class="el" href="classtvm_1_1runtime_1_1Tensor.html#a13828a9652f856b2e654c143cd29eee6">tvm::runtime::Tensor</a>, <a class="el" href="classtvm_1_1te_1_1Tensor.html#a7d6e6bba3b098fc14f7f74a98fe28537">tvm::te::Tensor</a></li>
<li>tensor_ty : <a class="el" href="classtvm_1_1relax_1_1distributed_1_1DTensorTypeNode.html#a26dc2379bb166c7fe99d45858f69de42">tvm::relax::distributed::DTensorTypeNode</a></li>
<li>TensorDom() : <a class="el" href="structtvm_1_1te_1_1TensorDom.html#a1c1c057115d9dbeec11ff717bf18430b">tvm::te::TensorDom</a></li>
<li>TensorInfo() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1TensorInfo.html#acf73abc700776ff27a54c5bfbb8d5ccd">tvm::s_tir::meta_schedule::TensorInfo</a></li>
@@ -100,11 +100,11 @@ $(function() {
<li>TensorLoadNode() : <a class="el" href="classtvm_1_1TensorLoadNode.html#a08f60369caf2ad19924ef22ef0d98f74">tvm::TensorLoadNode</a></li>
<li>TensorMapType() : <a class="el" href="classtvm_1_1tirx_1_1TensorMapType.html#a7c2e43be08f81b8cb9e9913607264f91">tvm::tirx::TensorMapType</a></li>
<li>TensorRegion() : <a class="el" href="classtvm_1_1TensorRegion.html#abb98087a654cb1db8aee73371bf913ea">tvm::TensorRegion</a></li>
-<li>TensorRegionNode() : <a class="el" href="classtvm_1_1TensorRegionNode.html#a045dbc6ccb25d900abfe062611fd2005">tvm::TensorRegionNode</a></li>
+<li>TensorRegionNode() : <a class="el" href="classtvm_1_1TensorRegionNode.html#a735f61a61ac13e6950927646f1d470a2">tvm::TensorRegionNode</a></li>
<li>TensorRegionType() : <a class="el" href="classtvm_1_1TensorRegionType.html#a2132aa9ab39f0a8fbb1c09f791bd2a8c">tvm::TensorRegionType</a></li>
<li>TensorStore() : <a class="el" href="classtvm_1_1TensorStore.html#ab861ba55d3414cf43a4f3aa90933cb33">tvm::TensorStore</a></li>
<li>TensorStoreNode() : <a class="el" href="classtvm_1_1TensorStoreNode.html#a50bcf9d8d1719a2260af9eb445470291">tvm::TensorStoreNode</a></li>
-<li>TensorType() : <a class="el" href="classtvm_1_1relax_1_1TensorType.html#ae41d1240dfabfeb8039262b9802960ae">tvm::relax::TensorType</a>, <a class="el" href="classtvm_1_1tirx_1_1TensorType.html#a05111660c3b9db58c77d775e03a29014">tvm::tirx::TensorType</a></li>
+<li>TensorType() : <a class="el" href="classtvm_1_1relax_1_1TensorType.html#aaf0a2c1bc2de029fb2949793c1895e5c">tvm::relax::TensorType</a>, <a class="el" href="classtvm_1_1tirx_1_1TensorType.html#a05111660c3b9db58c77d775e03a29014">tvm::tirx::TensorType</a></li>
<li>TensorTypeNode() : <a class="el" href="classtvm_1_1tirx_1_1TensorTypeNode.html#a5ae44e202ab143e98e27b17b702f3eaa">tvm::tirx::TensorTypeNode</a></li>
<li>TensorVar() : <a class="el" href="classtvm_1_1tirx_1_1TensorVar.html#af04669651eeae9466cdf16e7396933d8">tvm::tirx::TensorVar</a></li>
<li>TerminateTask() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1TaskSchedulerNode.html#a47eca9f404e554a68aad9df5a9ec9745">tvm::s_tir::meta_schedule::TaskSchedulerNode</a></li>
@@ -123,7 +123,7 @@ $(function() {
<li>tile_layout : <a class="el" href="classtvm_1_1tirx_1_1ComposeLayoutNode.html#a4c90358e33fcb3f5e9c8dddf7329b814">tvm::tirx::ComposeLayoutNode</a></li>
<li>TileLayout() : <a class="el" href="classtvm_1_1tirx_1_1TileLayout.html#a9317589823ea5b704d135721be94431e">tvm::tirx::TileLayout</a></li>
<li>TimedScope() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1Profiler.html#aa808076cd8e770318d18a1cf7fa1d5c7">tvm::s_tir::meta_schedule::Profiler</a></li>
-<li>TIRFrame() : <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1tirx_1_1TIRFrame.html#a2494400e71e245dd6ef829c22e979783">tvm::script::ir_builder::tirx::TIRFrame</a></li>
+<li>TIRFrame() : <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1tirx_1_1TIRFrame.html#aa8117c4c56bc11ece758742b208f3386">tvm::script::ir_builder::tirx::TIRFrame</a></li>
<li>to_users_ : <a class="el" href="classtvm_1_1relax_1_1DataflowBlockRewriteNode.html#a667829eb57e5e2ca06817f15dc4e45ff">tvm::relax::DataflowBlockRewriteNode</a></li>
<li>ToConfig() : <a class="el" href="classtvm_1_1TargetNode.html#ace76fa9881beb34df981af0d42723021">tvm::TargetNode</a></li>
<li>ToDual() : <a class="el" href="classtvm_1_1tirx_1_1SLayoutAxis.html#ad46be2c6241a2451a2e86e743fa91106">tvm::tirx::SLayoutAxis</a></li>
@@ -135,7 +135,7 @@ $(function() {
<li>total_timer : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1ProfilerNode.html#a471ccef4fb1252ba84603deb04b4337d">tvm::s_tir::meta_schedule::ProfilerNode</a></li>
<li>TouchTask() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1TaskSchedulerNode.html#a96dad2bf37679aba787f4e4b81c979f9">tvm::s_tir::meta_schedule::TaskSchedulerNode</a></li>
<li>trace : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1TuningRecordNode.html#a6c420954230cab91f9b839852eafe7fd">tvm::s_tir::meta_schedule::TuningRecordNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#a181cd324ae42a93a5308454122d10ff3">tvm::s_tir::ScheduleNode</a></li>
-<li>Trace() : <a class="el" href="classtvm_1_1s__tir_1_1Trace.html#a894c9a4fca263f9ad13cec46ac74de11">tvm::s_tir::Trace</a></li>
+<li>Trace() : <a class="el" href="classtvm_1_1s__tir_1_1Trace.html#aab8cc9848fd4be6164533a515937978c">tvm::s_tir::Trace</a></li>
<li>Traced() : <a class="el" href="classtvm_1_1s__tir_1_1Schedule.html#a5e3700664d2588ecb67b05d537fe3bbb">tvm::s_tir::Schedule</a></li>
<li>training : <a class="el" href="structtvm_1_1relax_1_1BatchNormAttrs.html#a4dad5a52a849719b33e28fa68042616a">tvm::relax::BatchNormAttrs</a></li>
<li>TRandState : <a class="el" href="classtvm_1_1s__tir_1_1LinearCongruentialEngine.html#ac02f5a19918906c1af2518756a76e488">tvm::s_tir::LinearCongruentialEngine</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1TuneContext.html#a4194936898b815ebd28227cd9a263096">tvm::s_tir::meta_schedule::TuneContext</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1TuneContextNode.html#aa2734f0544f44ca1171e768835dc02b4">tvm::s_tir::meta_schedule::TuneContextNode</a></li>
@@ -166,17 +166,18 @@ $(function() {
<li>TupleTypeNode() : <a class="el" href="classtvm_1_1TupleTypeNode.html#a1e9cbe8e91816366c181fb888ddc18d9">tvm::TupleTypeNode</a></li>
<li>TVM_DEFINE_OBJECT_REF_COW_METHOD() : <a class="el" href="classtvm_1_1AssertStmt.html#a401d1c786573cba184a5053bed4a7168">tvm::AssertStmt</a>, <a class="el" href="classtvm_1_1Bind.html#a2e0a42528e5b2510f08d3ff3c43d34ba">tvm::Bind</a>, <a class="el" href="classtvm_1_1Break.html#aacfb1c86342879e973b81c1343f3dffe">tvm::Break</a>, <a class="el" href="classtvm_1_1Call.html#ac7f8d11aa54e549a1154d2d2bd25c461">tvm::Call</a>, <a class="el" href="classtvm_1_1Continue.html#a17b5846e008e [...]
<li>TVM_FFI_DECLARE_OBJECT_INFO() : <a class="el" href="classtvm_1_1AttrsNode.html#ae4806aea36c99253f52625489497803e">tvm::AttrsNode</a>, <a class="el" href="classtvm_1_1BaseFuncNode.html#a92a7f720142c275784235eb9905ee835">tvm::BaseFuncNode</a>, <a class="el" href="classtvm_1_1ConstantNode.html#a7ac1b77b387c65100e701bc11dc958e0">tvm::ConstantNode</a>, <a class="el" href="classtvm_1_1ExprNode.html#a79424fe36b005bfd36e56dfcfcb4a118">tvm::ExprNode</a>, <a class="el" href="classtvm [...]
-<li>TVM_FFI_DECLARE_OBJECT_INFO_FINAL() : <a class="el" href="classtvm_1_1AnyTypeNode.html#a1c2008016781a41f62c803986aaad81f">tvm::AnyTypeNode</a>, <a class="el" href="classtvm_1_1ArgumentInfoNode.html#ad5d4e5da3f0998f96b3155ae48b844cc">tvm::ArgumentInfoNode</a>, <a class="el" href="classtvm_1_1AssertStmtNode.html#ae06276577882fd897fac8ad3b2b0398b">tvm::AssertStmtNode</a>, <a class="el" href="structtvm_1_1backend_1_1cuda_1_1TCGen05InstrDescriptorAttrs.html#ae268a401d28b4d0221b1 [...]
+<li>TVM_FFI_DECLARE_OBJECT_INFO_FINAL() : <a class="el" href="classtvm_1_1AnyTypeNode.html#a1c2008016781a41f62c803986aaad81f">tvm::AnyTypeNode</a>, <a class="el" href="classtvm_1_1ArgumentInfoNode.html#ad5d4e5da3f0998f96b3155ae48b844cc">tvm::ArgumentInfoNode</a>, <a class="el" href="classtvm_1_1AssertStmtNode.html#ae06276577882fd897fac8ad3b2b0398b">tvm::AssertStmtNode</a>, <a class="el" href="structtvm_1_1backend_1_1cuda_1_1TCGen05InstrDescriptorAttrs.html#ae268a401d28b4d0221b1 [...]
<li>TVM_FFI_DECLARE_OBJECT_INFO_PREDEFINED_TYPE_KEY() : <a class="el" href="classtvm_1_1prim_1_1BinaryOpNode.html#a4ea9d6d505a52f8c48703981630df05c">tvm::prim::BinaryOpNode< T ></a>, <a class="el" href="classtvm_1_1prim_1_1CmpOpNode.html#a6f8cddcdbc85626674cffa6d59c585d7">tvm::prim::CmpOpNode< T ></a></li>
<li>TVM_FFI_DECLARE_OBJECT_INFO_STATIC() : <a class="el" href="classtvm_1_1runtime_1_1DRefObj.html#a18ed3c1a2f001484e33295fd0b7476aa">tvm::runtime::DRefObj</a></li>
<li>TVM_FFI_DEFINE_DEFAULT_COPY_MOVE_AND_ASSIGN() : <a class="el" href="classtvm_1_1tirx_1_1TensorVar.html#a706fea2f129ede37fe7980fda59a3bd1">tvm::tirx::TensorVar</a></li>
-<li>TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE() : <a class="el" href="classtvm_1_1AnyType.html#a801577ea879428083b5da2e81a58e62f">tvm::AnyType</a>, <a class="el" href="classtvm_1_1AssertStmt.html#a701cd68f5cd3422d0b868f538d1686c4">tvm::AssertStmt</a>, <a class="el" href="classtvm_1_1BaseFunc.html#a496463fef22ee43ebd9ace59626a0348">tvm::BaseFunc</a>, <a class="el" href="classtvm_1_1Bind.html#a62bd2536776c6a0c835d49b58749b2b9">tvm::Bind</a>, <a class="el" href="classtvm_1_1Br [...]
+<li>TVM_FFI_DEFINE_OBJECT_REF_METHODS_NOTNULLABLE() : <a class="el" href="classtvm_1_1AnyType.html#a801577ea879428083b5da2e81a58e62f">tvm::AnyType</a>, <a class="el" href="classtvm_1_1AssertStmt.html#a701cd68f5cd3422d0b868f538d1686c4">tvm::AssertStmt</a>, <a class="el" href="classtvm_1_1BaseFunc.html#a496463fef22ee43ebd9ace59626a0348">tvm::BaseFunc</a>, <a class="el" href="classtvm_1_1Bind.html#a62bd2536776c6a0c835d49b58749b2b9">tvm::Bind</a>, <a class="el" href="classtvm_1_1Br [...]
<li>TVM_FFI_DEFINE_OBJECT_REF_METHODS_NULLABLE() : <a class="el" href="classtvm_1_1ArgumentInfo.html#ad079f3045ac104e7107ebc3197447462">tvm::ArgumentInfo</a>, <a class="el" href="classtvm_1_1Attrs.html#af88d2fff186ab0af971db3a281cae1ce">tvm::Attrs</a>, <a class="el" href="classtvm_1_1GlobalInfo.html#af82b716ca0477f2bd23aa4a526466126">tvm::GlobalInfo</a>, <a class="el" href="classtvm_1_1Range.html#a592353a8a4642af3d8e26d246436d37e">tvm::Range</a>, <a class="el" href="classtvm_1_ [...]
<li>ty : <a class="el" href="classtvm_1_1ExprNode.html#a4c2a9b792a5ec422d8e04d6d78707fcb">tvm::ExprNode</a>, <a class="el" href="classtvm_1_1relax_1_1MatchCastNode.html#a93a4d080db242436bdee1ae702536324">tvm::relax::MatchCastNode</a>, <a class="el" href="classtvm_1_1relax_1_1TypePatternNode.html#a4c785bb96db69e2bb8b6741009483279">tvm::relax::TypePatternNode</a>, <a class="el" href="classtvm_1_1TypedExpr.html#a7d83b1f31a1cc6f0774df309e207e678">tvm::TypedExpr< ExpectedType > [...]
<li>ty_args : <a class="el" href="classtvm_1_1CallNode.html#aea255b3c2342dc40ac3b2a4af9d332a0">tvm::CallNode</a></li>
<li>ty_args_info : <a class="el" href="classtvm_1_1OpNode.html#a59a1176e5da55aa98a8447c2da8e3830">tvm::OpNode</a></li>
+<li>type : <a class="el" href="structtvm_1_1relax_1_1PairCons.html#aa7fe6fdef3ab68d2f5176485000646b9">tvm::relax::PairCons</a></li>
<li>Type : <a class="el" href="structtvm_1_1relax_1_1PairCons.html#ab64ed8db46c468684a6e00fcb6530647">tvm::relax::PairCons</a></li>
-<li>type : <a class="el" href="structtvm_1_1relax_1_1PairCons.html#aa7fe6fdef3ab68d2f5176485000646b9">tvm::relax::PairCons</a>, <a class="el" href="classtvm_1_1runtime_1_1memory_1_1Allocator.html#a5690ce0a8e9e25bd8e5568173cc0b1bb">tvm::runtime::memory::Allocator</a>, <a class="el" href="classtvm_1_1tirx_1_1TensorVar.html#a42fcd94536191d8b98f75a6a0bfc3f7a">tvm::tirx::TensorVar</a></li>
+<li>type() : <a class="el" href="classtvm_1_1runtime_1_1memory_1_1Allocator.html#a5690ce0a8e9e25bd8e5568173cc0b1bb">tvm::runtime::memory::Allocator</a>, <a class="el" href="classtvm_1_1tirx_1_1TensorVar.html#a42fcd94536191d8b98f75a6a0bfc3f7a">tvm::tirx::TensorVar</a></li>
<li>type_params : <a class="el" href="classtvm_1_1script_1_1printer_1_1FunctionDocNode.html#a6b3656238d197981cf25870e7f7bb1ab">tvm::script::printer::FunctionDocNode</a></li>
<li>type_str : <a class="el" href="structtvm_1_1ConfigSchema_1_1OptionEntry.html#a196a591fb39df500cf45fe3ec15e7a8d">tvm::ConfigSchema::OptionEntry</a></li>
<li>TypedEnvFunc() : <a class="el" href="classtvm_1_1TypedEnvFunc_3_01R_07Args_8_8_8_08_4.html#a41a6b9014d0feeb628ca7edfd0d26f0b">tvm::TypedEnvFunc< R(Args...)></a></li>
diff --git a/docs/reference/api/doxygen/functions_v.html b/docs/reference/api/doxygen/functions_v.html
index 8086555c85f..528905bb85c 100644
--- a/docs/reference/api/doxygen/functions_v.html
+++ b/docs/reference/api/doxygen/functions_v.html
@@ -82,7 +82,7 @@ $(function() {
<li>value_to_bound_var : <a class="el" href="classtvm_1_1relax_1_1transform_1_1PatternCheckContextNode.html#a015fa5f7ff630ae7aa065fc169817f9f">tvm::relax::transform::PatternCheckContextNode</a></li>
<li>values : <a class="el" href="classtvm_1_1relax_1_1ShapeExprNode.html#a0b018e0a288a46268ab03b0f4fd54e1c">tvm::relax::ShapeExprNode</a>, <a class="el" href="classtvm_1_1relax_1_1ShapeTypeNode.html#add3416d082274253baf955642455fcf6">tvm::relax::ShapeTypeNode</a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1DictDocNode.html#af448345c2b322d0a35453c8b602e50d3">tvm::script::printer::DictDocNode</a></li>
<li>var : <a class="el" href="classtvm_1_1BindNode.html#a949f264baee2e8012335b8a1df58cddd">tvm::BindNode</a>, <a class="el" href="classtvm_1_1prim_1_1LetNode.html#a46efb191894de5fe00445a43c3d683a7">tvm::prim::LetNode</a>, <a class="el" href="classtvm_1_1relax_1_1BindingNode.html#a31222a9c83a8532274cd8a56f991157b">tvm::relax::BindingNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1IterVarNode.html#a358127fd9f63fadfcdd2f20bdff4d705">tvm::s_tir::IterVarNode</a>, <a class="el" h [...]
-<li>Var() : <a class="el" href="classtvm_1_1Var.html#ab1e43f83b3c137b969c484465eb65337">tvm::Var</a></li>
+<li>Var() : <a class="el" href="classtvm_1_1Var.html#ae5aba21bb7c1a09774273f4f2b5ef0d8">tvm::Var</a></li>
<li>var_args_info : <a class="el" href="classtvm_1_1OpNode.html#a126f0c272afde9f28489d80e446fb5c8">tvm::OpNode</a></li>
<li>var_get_or_alloc_id : <a class="el" href="structtvm_1_1script_1_1printer_1_1DocTranslatorVTable.html#adaf16dc3885bed39cc9daba196e5abd1">tvm::script::printer::DocTranslatorVTable</a></li>
<li>var_name : <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1relax_1_1IfFrameNode.html#ab7e517b6100fa4c236bd88cc1a9a600a">tvm::script::ir_builder::relax::IfFrameNode</a></li>
@@ -91,7 +91,7 @@ $(function() {
<li>var_ty_args_info : <a class="el" href="classtvm_1_1OpNode.html#ab6e6b14ea08f87dbb30148bae6a6d5a6">tvm::OpNode</a></li>
<li>var_usages : <a class="el" href="classtvm_1_1relax_1_1transform_1_1PatternCheckContextNode.html#afa29eae60eeea28891d6efebf3ef61fa">tvm::relax::transform::PatternCheckContextNode</a></li>
<li>VarBinding() : <a class="el" href="classtvm_1_1relax_1_1VarBinding.html#afb0005363849fbf3f188657fcd2c247b">tvm::relax::VarBinding</a></li>
-<li>VarBindingNode() : <a class="el" href="classtvm_1_1relax_1_1VarBindingNode.html#a3d62925ef25535c562bfbc6e9ee86ee7">tvm::relax::VarBindingNode</a></li>
+<li>VarBindingNode() : <a class="el" href="classtvm_1_1relax_1_1VarBindingNode.html#ad553ea0582fd478684eb10480ca9fff1">tvm::relax::VarBindingNode</a></li>
<li>varg_default_wildcard : <a class="el" href="classtvm_1_1relax_1_1CallPatternNode.html#a06bae27dbf4398894632f88f75f6f623">tvm::relax::CallPatternNode</a></li>
<li>VarGetOrAllocId() : <a class="el" href="classtvm_1_1script_1_1printer_1_1DocTranslatorObj.html#ad177ca6b4dd438224afdf993dbf7002c">tvm::script::printer::DocTranslatorObj</a></li>
<li>variances : <a class="el" href="structtvm_1_1relax_1_1MultiboxTransformLocAttrs.html#a867153646fdde09eb89aa93c330a0355">tvm::relax::MultiboxTransformLocAttrs</a></li>
diff --git a/docs/reference/api/doxygen/functions_vars_a.html b/docs/reference/api/doxygen/functions_vars_a.html
index e87b0fc7dd4..c4f9d93db90 100644
--- a/docs/reference/api/doxygen/functions_vars_a.html
+++ b/docs/reference/api/doxygen/functions_vars_a.html
@@ -96,7 +96,7 @@ $(function() {
<li>annotations : <a class="el" href="classtvm_1_1ForNode.html#ab9ae1f41c715c0a8c8dcdcf3b4c9823f">tvm::ForNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1SBlockNode.html#ae70f381c587a0a085367e74309ebfe2f">tvm::s_tir::SBlockNode</a>, <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1s__tir_1_1SBlockFrameNode.html#a5238ce3fae21d21fc62330c207cf08e2">tvm::script::ir_builder::s_tir::SBlockFrameNode</a></li>
<li>apply_softmax : <a class="el" href="structtvm_1_1relax_1_1MultiboxTransformLocAttrs.html#a2edaf8d654ebb18f47b4a3ef2e6810f4">tvm::relax::MultiboxTransformLocAttrs</a></li>
<li>arg_types : <a class="el" href="classtvm_1_1FuncTypeNode.html#aa8e067bd61ced30bc55f637f4792aef4">tvm::FuncTypeNode</a></li>
-<li>args : <a class="el" href="classtvm_1_1CallNode.html#a323af62ed5243b5db00eb1832f842a1c">tvm::CallNode</a>, <a class="el" href="classtvm_1_1RegionStmtNode.html#aa0ff83b20975a305cff8622fcfed9cbe">tvm::RegionStmtNode</a>, <a class="el" href="classtvm_1_1relax_1_1CallPatternNode.html#a747a5214b15a6288560fdd359eeb7c75">tvm::relax::CallPatternNode</a>, <a class="el" href="classtvm_1_1relax_1_1SameShapeConstraintNode.html#ac5f5eb8f9a7e1f83966726767fec6568">tvm::relax::SameShapeCon [...]
+<li>args : <a class="el" href="classtvm_1_1CallNode.html#a323af62ed5243b5db00eb1832f842a1c">tvm::CallNode</a>, <a class="el" href="classtvm_1_1RegionStmtNode.html#aa0ff83b20975a305cff8622fcfed9cbe">tvm::RegionStmtNode</a>, <a class="el" href="classtvm_1_1relax_1_1CallPatternNode.html#a747a5214b15a6288560fdd359eeb7c75">tvm::relax::CallPatternNode</a>, <a class="el" href="classtvm_1_1relax_1_1SameShapeConstraintNode.html#ac5f5eb8f9a7e1f83966726767fec6568">tvm::relax::SameShapeCon [...]
<li>args_info : <a class="el" href="classtvm_1_1OpNode.html#a1106cc90ca7823f513807317116b87e0">tvm::OpNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1MeasureCandidateNode.html#a3eaf9e7d35f07938f40ae6b056fd9522">tvm::s_tir::meta_schedule::MeasureCandidateNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1RunnerInputNode.html#adda3434c59e17fe2b9159ac1e0b105e4">tvm::s_tir::meta_schedule::RunnerInputNode</a>, <a class="el" href="classtvm_1_1 [...]
<li>artifact_path : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1BuilderResultNode.html#a6b42b9c07eafa45985402eac9379b380">tvm::s_tir::meta_schedule::BuilderResultNode</a>, <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1RunnerInputNode.html#aa654ac5e47a68b46e70271d1652188ee">tvm::s_tir::meta_schedule::RunnerInputNode</a></li>
<li>assume_inbound : <a class="el" href="structtvm_1_1relax_1_1StridedSliceAttrs.html#a8168d3fe82679449981a4e26ba3b84ba">tvm::relax::StridedSliceAttrs</a></li>
diff --git a/docs/reference/api/doxygen/functions_vars_c.html b/docs/reference/api/doxygen/functions_vars_c.html
index c3368769d3a..c9f763e0f96 100644
--- a/docs/reference/api/doxygen/functions_vars_c.html
+++ b/docs/reference/api/doxygen/functions_vars_c.html
@@ -73,7 +73,7 @@ $(function() {
<h3><a id="index_c" name="index_c"></a>- c -</h3><ul>
<li>callbacks : <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1IRBuilderFrameNode.html#a45f552bb19d593f4ecc4b3b5d69cf8dc">tvm::script::ir_builder::IRBuilderFrameNode</a>, <a class="el" href="classtvm_1_1tirx_1_1DispatchContextNode.html#a3e48b15d23856ba7c084531dae51fb7b">tvm::tirx::DispatchContextNode</a></li>
-<li>callee : <a class="el" href="classtvm_1_1CallSiteLocNode.html#a40365565ed92a9de7a0b2023befbc306">tvm::CallSiteLocNode</a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1CallDocNode.html#afd99b131a9accf85284b528203e71413">tvm::script::printer::CallDocNode</a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#adbcf4a3aabbe1d82f73fc2d5f6154f6b">tvm::script::printer::OpCallDocNode</a></li>
+<li>callee : <a class="el" href="classtvm_1_1CallSiteLocNode.html#a40365565ed92a9de7a0b2023befbc306">tvm::CallSiteLocNode</a>, <a class="el" href="classtvm_1_1script_1_1printer_1_1CallDocNode.html#afd99b131a9accf85284b528203e71413">tvm::script::printer::CallDocNode</a></li>
<li>caller : <a class="el" href="classtvm_1_1CallSiteLocNode.html#af6317bd3ebd9e9c2a8d9e39d91cfafe9">tvm::CallSiteLocNode</a></li>
<li>canonical_name : <a class="el" href="classtvm_1_1script_1_1printer_1_1NamespaceDocNode.html#aff1146b3556123ae0384c7ff0976aac6">tvm::script::printer::NamespaceDocNode</a></li>
<li>canonical_simplify : <a class="el" href="classtvm_1_1sym_1_1AnalyzerObj.html#a999515b92f3ff3a5e4b0a18580c590ae">tvm::sym::AnalyzerObj</a></li>
@@ -90,7 +90,7 @@ $(function() {
<li>comment : <a class="el" href="classtvm_1_1script_1_1printer_1_1StmtDocNode.html#a99434a755a816459b365afd7caf52b78">tvm::script::printer::StmtDocNode</a></li>
<li>cond : <a class="el" href="classtvm_1_1relax_1_1IfExprNode.html#a6fe48357f17d2a412839db1e72308139">tvm::relax::IfExprNode</a>, <a class="el" href="structtvm_1_1runtime_1_1vm_1_1Instruction.html#a0a9bcefef97c5a7fd11a1dc5103669a2">tvm::runtime::vm::Instruction</a></li>
<li>condition : <a class="el" href="classtvm_1_1AssertStmtNode.html#a42219a8d7a570a32b37fb4c1dd705a03">tvm::AssertStmtNode</a>, <a class="el" href="classtvm_1_1IfNode.html#a4e77795d3f6677cf272cbedac0fd70cd">tvm::IfNode</a>, <a class="el" href="classtvm_1_1prim_1_1SelectNode.html#a7be5da5d136256b91131ace2e5c55cb9">tvm::prim::SelectNode</a>, <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1ir_1_1AssertFrameNode.html#ae23a7e2026a82b0707302f4e3b2babcd">tvm::script::ir_build [...]
-<li>config : <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ab587d4e63b73fc2411792cba3517b5ae">tvm::script::printer::OpCallDocNode</a>, <a class="el" href="classtvm_1_1transform_1_1PassContextNode.html#a3eefdea0d7b623abd48b2fb3341631a5">tvm::transform::PassContextNode</a></li>
+<li>config : <a class="el" href="classtvm_1_1transform_1_1PassContextNode.html#a3eefdea0d7b623abd48b2fb3341631a5">tvm::transform::PassContextNode</a></li>
<li>const_int_bound : <a class="el" href="classtvm_1_1sym_1_1AnalyzerObj.html#abb9f2170a0b1cd7ccf173f393c1a2faf">tvm::sym::AnalyzerObj</a></li>
<li>constants : <a class="el" href="classtvm_1_1runtime_1_1vm_1_1VMExecutable.html#a8db062d10acf0ed58cd2d00426a6106f">tvm::runtime::vm::VMExecutable</a></li>
<li>coord_start : <a class="el" href="structtvm_1_1relax_1_1NonMaximumSuppressionAttrs.html#ae7348ffbe5e56d404d819c33b0b1ee17">tvm::relax::NonMaximumSuppressionAttrs</a></li>
diff --git a/docs/reference/api/doxygen/functions_vars_d.html b/docs/reference/api/doxygen/functions_vars_d.html
index 8e40852f316..232507b9e10 100644
--- a/docs/reference/api/doxygen/functions_vars_d.html
+++ b/docs/reference/api/doxygen/functions_vars_d.html
@@ -104,7 +104,6 @@ $(function() {
<li>dilation : <a class="el" href="structtvm_1_1relax_1_1Conv1DAttrs.html#a33a201ca45d510928b740718bed6d95c">tvm::relax::Conv1DAttrs</a>, <a class="el" href="structtvm_1_1relax_1_1Conv1DTransposeAttrs.html#a47ef9b1660a2b90cca2429344d5b82ec">tvm::relax::Conv1DTransposeAttrs</a>, <a class="el" href="structtvm_1_1relax_1_1Conv2DAttrs.html#a450ce3662daf2272d34d3ce216690529">tvm::relax::Conv2DAttrs</a>, <a class="el" href="structtvm_1_1relax_1_1Conv2DTransposeAttrs.html#a48841fafbd3 [...]
<li>dim_specs : <a class="el" href="classtvm_1_1relax_1_1distributed_1_1PlacementNode.html#a2e0c364bf39e9b43c2765b4181b7be97">tvm::relax::distributed::PlacementNode</a></li>
<li>disabled_pass : <a class="el" href="classtvm_1_1transform_1_1PassContextNode.html#a7b3e5ef0dc09987887390887b19d60ea">tvm::transform::PassContextNode</a></li>
-<li>dispatch : <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#a9463aa1e349fdaa77ee00318eda01047">tvm::script::printer::OpCallDocNode</a></li>
<li>dispatched : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1ExtractedTaskNode.html#a8be137581a62630c9b30e5e1d88acaf2">tvm::s_tir::meta_schedule::ExtractedTaskNode</a></li>
<li>doc : <a class="el" href="classtvm_1_1ArgumentInfoNode.html#ac6e758834aeaa009febaf8996e797dc1">tvm::ArgumentInfoNode</a>, <a class="el" href="classtvm_1_1OpNode.html#a581785b139323c424e7980367e597d1f">tvm::OpNode</a></li>
<li>doc_scopes_ : <a class="el" href="classtvm_1_1script_1_1printer_1_1DocTranslatorObj.html#a479c72c58a8e22da05cfbc8084abdb2a">tvm::script::printer::DocTranslatorObj</a></li>
diff --git a/docs/reference/api/doxygen/functions_vars_w.html b/docs/reference/api/doxygen/functions_vars_w.html
index 6c57b298a78..9dadfd7f58b 100644
--- a/docs/reference/api/doxygen/functions_vars_w.html
+++ b/docs/reference/api/doxygen/functions_vars_w.html
@@ -78,7 +78,6 @@ $(function() {
<li>worker_id : <a class="el" href="classtvm_1_1runtime_1_1cuda__ipc_1_1CUDAIPCMemoryObj.html#aee159316a5612aa8dbe42b9941e788b3">tvm::runtime::cuda_ipc::CUDAIPCMemoryObj</a>, <a class="el" href="classtvm_1_1runtime_1_1DiscoWorker.html#a5a6414e30855435fa0e6c0e226867edd">tvm::runtime::DiscoWorker</a></li>
<li>worker_zero_data : <a class="el" href="classtvm_1_1runtime_1_1DiscoWorker.html#ac4a5ec8d54ff321dbb960d442106773f">tvm::runtime::DiscoWorker</a></li>
<li>workload : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1TuningRecordNode.html#a950857678405bdfbedda2632aab850d1">tvm::s_tir::meta_schedule::TuningRecordNode</a></li>
-<li>workspace : <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ac5eaf7f682b39836acebf055f7c843ed">tvm::script::printer::OpCallDocNode</a></li>
<li>writes : <a class="el" href="classtvm_1_1s__tir_1_1SBlockNode.html#a0dd25645eb5121832e4f8ad55603d10d">tvm::s_tir::SBlockNode</a>, <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1s__tir_1_1SBlockFrameNode.html#aa62d5bcaffc983e9cd032351884c8298">tvm::script::ir_builder::s_tir::SBlockFrameNode</a></li>
</ul>
</div><!-- contents -->
diff --git a/docs/reference/api/doxygen/functions_w.html b/docs/reference/api/doxygen/functions_w.html
index 0e36d5b09ac..f82898d97cb 100644
--- a/docs/reference/api/doxygen/functions_w.html
+++ b/docs/reference/api/doxygen/functions_w.html
@@ -93,7 +93,7 @@ $(function() {
<li>WithDecision() : <a class="el" href="classtvm_1_1s__tir_1_1TraceNode.html#af5463d12f1e2024136e82421daa9bb11">tvm::s_tir::TraceNode</a></li>
<li>WithDocScope() : <a class="el" href="classtvm_1_1script_1_1printer_1_1DocTranslatorObj.html#a87b934fc34525e7855f4a2f4e9f2b5c7">tvm::script::printer::DocTranslatorObj</a></li>
<li>WithFilter() : <a class="el" href="structtvm_1_1tirx_1_1ExecContext.html#abedc4e591b93385635f69bcc4428d840">tvm::tirx::ExecContext</a></li>
-<li>WithGroup() : <a class="el" href="classtvm_1_1WithGroup.html#a506a5212abf0f5d2854f903a599587aa">tvm::WithGroup< ContextType ></a></li>
+<li>WithGroup() : <a class="el" href="classtvm_1_1WithGroup.html#a2b06930fa490149e771d9d16c31743b4">tvm::WithGroup< ContextType ></a></li>
<li>WithHost() : <a class="el" href="classtvm_1_1Target.html#a509ce63995f082c80742ea5ca6ac112f">tvm::Target</a></li>
<li>WithLanes() : <a class="el" href="classtvm_1_1PrimType.html#a47021aa229034baedd51cb5bd78a0b6c">tvm::PrimType</a></li>
<li>WithNewScope() : <a class="el" href="classtvm_1_1ScopeStack.html#a428e28b37398a250ea20ea660ef49fad">tvm::ScopeStack< T ></a></li>
@@ -104,11 +104,10 @@ $(function() {
<li>worker_id : <a class="el" href="classtvm_1_1runtime_1_1cuda__ipc_1_1CUDAIPCMemoryObj.html#aee159316a5612aa8dbe42b9941e788b3">tvm::runtime::cuda_ipc::CUDAIPCMemoryObj</a>, <a class="el" href="classtvm_1_1runtime_1_1DiscoWorker.html#a5a6414e30855435fa0e6c0e226867edd">tvm::runtime::DiscoWorker</a></li>
<li>worker_zero_data : <a class="el" href="classtvm_1_1runtime_1_1DiscoWorker.html#ac4a5ec8d54ff321dbb960d442106773f">tvm::runtime::DiscoWorker</a></li>
<li>workload : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1TuningRecordNode.html#a950857678405bdfbedda2632aab850d1">tvm::s_tir::meta_schedule::TuningRecordNode</a></li>
-<li>Workload() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1Workload.html#ac58e502d27bb29071ceb6455724392d2">tvm::s_tir::meta_schedule::Workload</a></li>
+<li>Workload() : <a class="el" href="classtvm_1_1s__tir_1_1meta__schedule_1_1Workload.html#a21acf51a06ad0dbbad3661afc2206953">tvm::s_tir::meta_schedule::Workload</a></li>
<li>WorkloadEqual() : <a class="el" href="structtvm_1_1s__tir_1_1meta__schedule_1_1WorkloadEqual.html#aecd57490b4085910fa0f34d958df11c9">tvm::s_tir::meta_schedule::WorkloadEqual</a></li>
<li>WorkOn() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#a98c7166dccb89aec6fefe6652ad7cd3f">tvm::s_tir::ScheduleNode</a></li>
-<li>workspace : <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html#ac5eaf7f682b39836acebf055f7c843ed">tvm::script::printer::OpCallDocNode</a></li>
-<li>Write() : <a class="el" href="structtvm_1_1support_1_1Serializer_3_01DLDataType_01_4.html#a90e6d264b6b4024fd82eb3ed22b101a8">tvm::support::Serializer< DLDataType ></a>, <a class="el" href="structtvm_1_1support_1_1Serializer_3_01DLDevice_01_4.html#a86809d7b22cf4bdff8ba2cc9d7f34c50">tvm::support::Serializer< DLDevice ></a>, <a class="el" href="structtvm_1_1support_1_1Serializer_3_01ffi_1_1Array_3_01T_01_4_01_4.html#a9464e988515dd37308280cd4901cad43">tvm::support:: [...]
+<li>Write() : <a class="el" href="structtvm_1_1support_1_1Serializer_3_01DLDataType_01_4.html#a90e6d264b6b4024fd82eb3ed22b101a8">tvm::support::Serializer< DLDataType ></a>, <a class="el" href="structtvm_1_1support_1_1Serializer_3_01DLDevice_01_4.html#a86809d7b22cf4bdff8ba2cc9d7f34c50">tvm::support::Serializer< DLDevice ></a>, <a class="el" href="structtvm_1_1support_1_1Serializer_3_01ffi_1_1Array_3_01T_01_4_01_4.html#a9464e988515dd37308280cd4901cad43">tvm::support:: [...]
<li>WriteArray() : <a class="el" href="classtvm_1_1support_1_1Stream.html#a2960a1a4127a1a31819df7e13cce553d">tvm::support::Stream</a></li>
<li>WriteAt() : <a class="el" href="classtvm_1_1s__tir_1_1ScheduleNode.html#ac8a6ba36b9a2b94906c9ba2b769953db">tvm::s_tir::ScheduleNode</a></li>
<li>writes : <a class="el" href="classtvm_1_1s__tir_1_1SBlockNode.html#a0dd25645eb5121832e4f8ad55603d10d">tvm::s_tir::SBlockNode</a>, <a class="el" href="classtvm_1_1script_1_1ir__builder_1_1s__tir_1_1SBlockFrameNode.html#aa62d5bcaffc983e9cd032351884c8298">tvm::script::ir_builder::s_tir::SBlockFrameNode</a></li>
diff --git a/docs/reference/api/doxygen/hierarchy.html b/docs/reference/api/doxygen/hierarchy.html
index 5fd5a854d01..14c79571fee 100644
--- a/docs/reference/api/doxygen/hierarchy.html
+++ b/docs/reference/api/doxygen/hierarchy.html
@@ -505,10 +505,9 @@ This inheritance list is sorted roughly, but not completely, alphabetically:</di
<tr id="row_44_74_3_8_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ForDocNode.html" target="_self">tvm::script::printer::ForDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents for statement </td></tr>
<tr id="row_44_74_3_9_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1FunctionDocNode.html" target="_self">tvm::script::printer::FunctionDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents function definition </td></tr>
<tr id="row_44_74_3_10_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1IfDocNode.html" target="_self">tvm::script::printer::IfDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represent if-then-else statement </td></tr>
-<tr id="row_44_74_3_11_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html" target="_self">tvm::script::printer::OpCallDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents call to an TIRX operator </td></tr>
-<tr id="row_44_74_3_12_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ReturnDocNode.html" target="_self">tvm::script::printer::ReturnDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents return statement </td></tr>
-<tr id="row_44_74_3_13_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ScopeDocNode.html" target="_self">tvm::script::printer::ScopeDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents special scopes </td></tr>
-<tr id="row_44_74_3_14_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1WhileDocNode.html" target="_self">tvm::script::printer::WhileDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents while statement </td></tr>
+<tr id="row_44_74_3_11_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ReturnDocNode.html" target="_self">tvm::script::printer::ReturnDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents return statement </td></tr>
+<tr id="row_44_74_3_12_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ScopeDocNode.html" target="_self">tvm::script::printer::ScopeDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents special scopes </td></tr>
+<tr id="row_44_74_3_13_" class="odd" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1WhileDocNode.html" target="_self">tvm::script::printer::WhileDocNode</a></td><td class="desc"><a class="el" href="classtvm_1_1script_1_1printer_1_1Doc.html" title="Reference type of DocNode.">Doc</a> that represents while statement </td></tr>
<tr id="row_44_75_" class="odd" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1DocTranslatorObj.html" target="_self">tvm::script::printer::DocTranslatorObj</a></td><td class="desc">Eager translation context shared by registered hooks. Hooks construct Docs, use explicit lexical scopes, and attach origins when emitting </td></tr>
<tr id="row_44_76_" class="odd" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1sym_1_1AnalyzerObj.html" target="_self">tvm::sym::AnalyzerObj</a></td><td class="desc"><a class="el" href="classtvm_1_1sym_1_1Analyzer.html" title="Managed reference to AnalyzerObj.">Analyzer</a> that contains bunch of sub-analyzers </td></tr>
<tr id="row_44_77_" class="odd" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1sym_1_1ConstIntBoundNode.html" target="_self">tvm::sym::ConstIntBoundNode</a></td><td class="desc"><a class="el" href="classtvm_1_1Constant.html" title="Managed reference to a literal constant.">Constant</a> integer up and lower bound(inclusive). Useful for value bound anal [...]
@@ -798,10 +797,9 @@ This inheritance list is sorted roughly, but not completely, alphabetically:</di
<tr id="row_47_75_3_8_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ForDoc.html" target="_self">tvm::script::printer::ForDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1ForDocNode.html" title="Doc that represents for statement.">ForDocNode</a> </td></tr>
<tr id="row_47_75_3_9_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1FunctionDoc.html" target="_self">tvm::script::printer::FunctionDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1FunctionDocNode.html" title="Doc that represents function definition.">FunctionDocNod [...]
<tr id="row_47_75_3_10_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1IfDoc.html" target="_self">tvm::script::printer::IfDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1IfDocNode.html" title="Doc that represent if-then-else statement.">IfDocNode</a> </td></tr>
-<tr id="row_47_75_3_11_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDoc.html" target="_self">tvm::script::printer::OpCallDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1OpCallDocNode.html" title="Doc that represents call to an TIRX operator.">OpCallDocNode< [...]
-<tr id="row_47_75_3_12_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ReturnDoc.html" target="_self">tvm::script::printer::ReturnDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1ReturnDocNode.html" title="Doc that represents return statement.">ReturnDocNode</a> </td></tr>
-<tr id="row_47_75_3_13_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ScopeDoc.html" target="_self">tvm::script::printer::ScopeDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1ScopeDocNode.html" title="Doc that represents special scopes.">ScopeDocNode</a> </td></tr>
-<tr id="row_47_75_3_14_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1WhileDoc.html" target="_self">tvm::script::printer::WhileDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1WhileDocNode.html" title="Doc that represents while statement.">WhileDocNode</a> </td></tr>
+<tr id="row_47_75_3_11_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ReturnDoc.html" target="_self">tvm::script::printer::ReturnDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1ReturnDocNode.html" title="Doc that represents return statement.">ReturnDocNode</a> </td></tr>
+<tr id="row_47_75_3_12_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1ScopeDoc.html" target="_self">tvm::script::printer::ScopeDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1ScopeDocNode.html" title="Doc that represents special scopes.">ScopeDocNode</a> </td></tr>
+<tr id="row_47_75_3_13_" class="even" style="display:none;"><td class="entry"><span style="width:64px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1WhileDoc.html" target="_self">tvm::script::printer::WhileDoc</a></td><td class="desc">Reference type of <a class="el" href="classtvm_1_1script_1_1printer_1_1WhileDocNode.html" title="Doc that represents while statement.">WhileDocNode</a> </td></tr>
<tr id="row_47_76_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1script_1_1printer_1_1DocTranslator.html" target="_self">tvm::script::printer::DocTranslator</a></td><td class="desc">Owning reference to a hook translation context </td></tr>
<tr id="row_47_77_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1sym_1_1Analyzer.html" target="_self">tvm::sym::Analyzer</a></td><td class="desc">Managed reference to <a class="el" href="classtvm_1_1sym_1_1AnalyzerObj.html" title="Analyzer that contains bunch of sub-analyzers.">AnalyzerObj</a> </td></tr>
<tr id="row_47_78_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1sym_1_1ConstIntBound.html" target="_self">tvm::sym::ConstIntBound</a></td><td class="desc">Reference class to <a class="el" href="classtvm_1_1sym_1_1ConstIntBoundNode.html" title="Constant integer up and lower bound(inclusive). Useful for value bound analysis.">ConstIntBou [...]
@@ -845,7 +843,8 @@ This inheritance list is sorted roughly, but not completely, alphabetically:</di
<tr id="row_49_4_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01PrimExpr_01_4.html" target="_self">tvm::ffi::TypeTraits< PrimExpr ></a></td><td class="desc"></td></tr>
<tr id="row_49_5_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01PrimType_01_4.html" target="_self">tvm::ffi::TypeTraits< PrimType ></a></td><td class="desc"></td></tr>
<tr id="row_49_6_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01SeqStmt_01_4.html" target="_self">tvm::ffi::TypeTraits< SeqStmt ></a></td><td class="desc"></td></tr>
-<tr id="row_49_7_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01tvm_1_1StringImm_01_4.html" target="_self">tvm::ffi::TypeTraits< tvm::StringImm ></a></td><td class="desc"></td></tr>
+<tr id="row_49_7_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01TensorRegion_01_4.html" target="_self">tvm::ffi::TypeTraits< TensorRegion ></a></td><td class="desc"></td></tr>
+<tr id="row_49_8_" class="even" style="display:none;"><td class="entry"><span style="width:32px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ffi_1_1TypeTraits_3_01tvm_1_1StringImm_01_4.html" target="_self">tvm::ffi::TypeTraits< tvm::StringImm ></a></td><td class="desc"></td></tr>
<tr id="row_50_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1OpAttrMap.html" target="_self">tvm::OpAttrMap< ValueType ></a></td><td class="desc">Typed live view of an <a class="el" href="classtvm_1_1Op.html" title="Reference-counted handle to a canonical named operator.">Op</a> attribute column </td></tr>
<tr id="row_51_" class="odd"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="classtvm_1_1OpDef.html" target="_self">tvm::OpDef</a></td><td class="desc">Noncopyable temporary builder for a canonical <a class="el" href="classtvm_1_1Op.html" title="Reference-counted handle to a canonical named operator.">Op</a>; see <a class="el" href="classtvm_1_1Op.html" title="Reference-counted handle [...]
<tr id="row_52_" class="even"><td class="entry"><span style="width:16px;display:inline-block;"> </span><span class="icona"><span class="icon">C</span></span><a class="el" href="structtvm_1_1ConfigSchema_1_1OptionEntry.html" target="_self">tvm::ConfigSchema::OptionEntry</a></td><td class="desc">Schema entry for one declared option </td></tr>
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<path fill="none" stroke="#63b8ff" d="M334.31,-15C342.92,-15 351.55,-15 359.88,-15"/>
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<g id="Node000002" class="node">
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+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.39,-2232.3 32.94,-2222.28 29.39,-2232.26 36.39,-2232.3"/>
</a>
</g>
</g>
@@ -93,8 +93,8 @@
<g id="Node000175" class="node">
<title>Node175</title>
<g id="a_Node000175"><a xlink:href="classtvm_1_1GlobalInfoNode.html" target="_top" xlink:title="GlobalInfo are globally static object that are referred by the IR itself. Base node for all global in...">
-<polygon fill="white" stroke="#666666" points="257.5,-4860 139.5,-4860 139.5,-4841 257.5,-4841 257.5,-4860"/>
-<text text-anchor="middle" x="198.5" y="-4848" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::GlobalInfoNode</text>
+<polygon fill="white" stroke="#666666" points="257.5,-4812 139.5,-4812 139.5,-4793 257.5,-4793 257.5,-4812"/>
+<text text-anchor="middle" x="198.5" y="-4800" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::GlobalInfoNode</text>
</a>
</g>
</g>
@@ -102,8 +102,8 @@
<g id="edge179_Node000000_Node000175" class="edge">
<title>Node0->Node175</title>
<g id="a_edge179_Node000000_Node000175"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M33.07,-2280.28C33.89,-2509.14 43.1,-4648.54 100,-4767.5 116.59,-4802.19 155.29,-4827.9 178.63,-4840.92"/>
-<polygon fill="#63b8ff" stroke="#63b8ff" points="36.57,-2280.09 33.03,-2270.1 29.57,-2280.11 36.57,-2280.09"/>
+<path fill="none" stroke="#63b8ff" d="M33.07,-2232.28C33.89,-2461.14 43.1,-4600.54 100,-4719.5 116.59,-4754.19 155.29,-4779.9 178.63,-4792.92"/>
+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.57,-2232.09 33.03,-2222.1 29.57,-2232.11 36.57,-2232.09"/>
</a>
</g>
</g>
@@ -111,8 +111,8 @@
<g id="Node000179" class="node">
<title>Node179</title>
<g id="a_Node000179"><a xlink:href="classtvm_1_1IRModuleNode.html" target="_top" xlink:title="IRModule that holds functions and type definitions.">
-<polygon fill="white" stroke="#666666" points="255,-4758 142,-4758 142,-4739 255,-4739 255,-4758"/>
-<text text-anchor="middle" x="198.5" y="-4746" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::IRModuleNode</text>
+<polygon fill="white" stroke="#666666" points="255,-4710 142,-4710 142,-4691 255,-4691 255,-4710"/>
+<text text-anchor="middle" x="198.5" y="-4698" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::IRModuleNode</text>
</a>
</g>
</g>
@@ -120,8 +120,8 @@
<g id="edge183_Node000000_Node000179" class="edge">
<title>Node0->Node179</title>
<g id="a_edge183_Node000000_Node000179"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M33.19,-2280.58C35.46,-2512.74 57.77,-4681.14 100,-4730.5 110.41,-4742.66 126.12,-4748.37 141.91,-4750.7"/>
-<polygon fill="#63b8ff" stroke="#63b8ff" points="36.69,-2280.21 33.09,-2270.24 29.69,-2280.28 36.69,-2280.21"/>
+<path fill="none" stroke="#63b8ff" d="M33.19,-2232.58C35.46,-2464.74 57.77,-4633.14 100,-4682.5 110.41,-4694.66 126.12,-4700.37 141.91,-4702.7"/>
+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.69,-2232.21 33.09,-2222.24 29.69,-2232.28 36.69,-2232.21"/>
</a>
</g>
</g>
@@ -129,8 +129,8 @@
<g id="Node000180" class="node">
<title>Node180</title>
<g id="a_Node000180"><a xlink:href="classtvm_1_1LocationNode.html" target="_top" xlink:title="Base class for immutable source-location metadata.">
-<polygon fill="white" stroke="#666666" points="253,-4721 144,-4721 144,-4702 253,-4702 253,-4721"/>
-<text text-anchor="middle" x="198.5" y="-4709" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::LocationNode</text>
+<polygon fill="white" stroke="#666666" points="253,-4673 144,-4673 144,-4654 253,-4654 253,-4673"/>
+<text text-anchor="middle" x="198.5" y="-4661" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::LocationNode</text>
</a>
</g>
</g>
@@ -138,8 +138,8 @@
<g id="edge184_Node000000_Node000180" class="edge">
<title>Node0->Node180</title>
<g id="a_edge184_Node000000_Node000180"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M33.04,-2280.72C33.52,-2492.33 39.39,-4298.2 100,-4527.5 119.12,-4599.85 171.07,-4675.5 190.25,-4701.81"/>
-<polygon fill="#63b8ff" stroke="#63b8ff" points="36.54,-2280.44 33.02,-2270.45 29.54,-2280.46 36.54,-2280.44"/>
+<path fill="none" stroke="#63b8ff" d="M33.04,-2232.72C33.52,-2444.33 39.39,-4250.2 100,-4479.5 119.12,-4551.85 171.07,-4627.5 190.25,-4653.81"/>
+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.54,-2232.44 33.02,-2222.45 29.54,-2232.46 36.54,-2232.44"/>
</a>
</g>
</g>
@@ -147,8 +147,8 @@
<g id="Node000184" class="node">
<title>Node184</title>
<g id="a_Node000184"><a xlink:href="classtvm_1_1PrinterConfigNode.html" target="_top" xlink:title=" ">
-<polygon fill="white" stroke="#666666" points="264,-4518 133,-4518 133,-4499 264,-4499 264,-4518"/>
-<text text-anchor="middle" x="198.5" y="-4506" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::PrinterConfigNode</text>
+<polygon fill="white" stroke="#666666" points="264,-4470 133,-4470 133,-4451 264,-4451 264,-4470"/>
+<text text-anchor="middle" x="198.5" y="-4458" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::PrinterConfigNode</text>
</a>
</g>
</g>
@@ -156,8 +156,8 @@
<g id="edge188_Node000000_Node000184" class="edge">
<title>Node0->Node184</title>
<g id="a_edge188_Node000000_Node000184"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M32.89,-2280.15C31.75,-2495.03 23.84,-4401.74 100,-4490.5 108.41,-4500.3 120.26,-4505.9 132.81,-4508.92"/>
-<polygon fill="#63b8ff" stroke="#63b8ff" points="36.39,-2280.05 32.94,-2270.03 29.39,-2280.01 36.39,-2280.05"/>
+<path fill="none" stroke="#63b8ff" d="M32.89,-2232.15C31.75,-2447.03 23.84,-4353.74 100,-4442.5 108.41,-4452.3 120.26,-4457.9 132.81,-4460.92"/>
+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.39,-2232.05 32.94,-2222.03 29.39,-2232.01 36.39,-2232.05"/>
</a>
</g>
</g>
@@ -165,8 +165,8 @@
<g id="Node000185" class="node">
<title>Node185</title>
<g id="a_Node000185"><a xlink:href="classtvm_1_1RangeNode.html" target="_top" xlink:title="range over one dimension">
-<polygon fill="white" stroke="#666666" points="247.5,-4481 149.5,-4481 149.5,-4462 247.5,-4462 247.5,-4481"/>
-<text text-anchor="middle" x="198.5" y="-4469" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::RangeNode</text>
+<polygon fill="white" stroke="#666666" points="247.5,-4433 149.5,-4433 149.5,-4414 247.5,-4414 247.5,-4433"/>
+<text text-anchor="middle" x="198.5" y="-4421" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::RangeNode</text>
</a>
</g>
</g>
@@ -174,8 +174,8 @@
<g id="edge189_Node000000_Node000185" class="edge">
<title>Node0->Node185</title>
<g id="a_edge189_Node000000_Node000185"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M32.9,-2280.47C31.88,-2494.95 25.16,-4366.32 100,-4453.5 112.05,-4467.54 131.18,-4472.96 149.31,-4474.53"/>
-<polygon fill="#63b8ff" stroke="#63b8ff" points="36.4,-2280.36 32.95,-2270.34 29.4,-2280.32 36.4,-2280.36"/>
+<path fill="none" stroke="#63b8ff" d="M32.9,-2232.47C31.88,-2446.95 25.16,-4318.32 100,-4405.5 112.05,-4419.54 131.18,-4424.96 149.31,-4426.53"/>
+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.4,-2232.36 32.95,-2222.34 29.4,-2232.32 36.4,-2232.36"/>
</a>
</g>
</g>
@@ -183,8 +183,8 @@
<g id="Node000186" class="node">
<title>Node186</title>
<g id="a_Node000186"><a xlink:href="classtvm_1_1SourceMapObj.html" target="_top" xlink:title="Stores locations in frontend source that generated a node.">
-<polygon fill="white" stroke="#666666" points="255,-4444 142,-4444 142,-4425 255,-4425 255,-4444"/>
-<text text-anchor="middle" x="198.5" y="-4432" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::SourceMapObj</text>
+<polygon fill="white" stroke="#666666" points="255,-4396 142,-4396 142,-4377 255,-4377 255,-4396"/>
+<text text-anchor="middle" x="198.5" y="-4384" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::SourceMapObj</text>
</a>
</g>
</g>
@@ -192,8 +192,8 @@
<g id="edge190_Node000000_Node000186" class="edge">
<title>Node0->Node186</title>
<g id="a_edge190_Node000000_Node000186"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M32.91,-2280.45C32.02,-2492.83 26.44,-4330.85 100,-4416.5 110.43,-4428.64 126.15,-4434.34 141.94,-4436.67"/>
-<polygon fill="#63b8ff" stroke="#63b8ff" points="36.41,-2280.19 32.95,-2270.17 29.41,-2280.16 36.41,-2280.19"/>
+<path fill="none" stroke="#63b8ff" d="M32.91,-2232.45C32.02,-2444.83 26.44,-4282.85 100,-4368.5 110.43,-4380.64 126.15,-4386.34 141.94,-4388.67"/>
+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.41,-2232.19 32.95,-2222.17 29.41,-2232.16 36.41,-2232.19"/>
</a>
</g>
</g>
@@ -201,8 +201,8 @@
<g id="Node000187" class="node">
<title>Node187</title>
<g id="a_Node000187"><a xlink:href="classtvm_1_1SourceNameNode.html" target="_top" xlink:title="The name of a source fragment.">
-<polygon fill="white" stroke="#666666" points="263.5,-4407 133.5,-4407 133.5,-4388 263.5,-4388 263.5,-4407"/>
-<text text-anchor="middle" x="198.5" y="-4395" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::SourceNameNode</text>
+<polygon fill="white" stroke="#666666" points="263.5,-4359 133.5,-4359 133.5,-4340 263.5,-4340 263.5,-4359"/>
+<text text-anchor="middle" x="198.5" y="-4347" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::SourceNameNode</text>
</a>
</g>
</g>
@@ -210,8 +210,8 @@
<g id="edge191_Node000000_Node000187" class="edge">
<title>Node0->Node187</title>
<g id="a_edge191_Node000000_Node000187"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M32.92,-2280.11C32.16,-2488.84 27.67,-4295.34 100,-4379.5 108.53,-4389.42 120.58,-4395.04 133.32,-4398.03"/>
-<polygon fill="#63b8ff" stroke="#63b8ff" points="36.42,-2280.02 32.96,-2270.01 29.42,-2279.99 36.42,-2280.02"/>
+<path fill="none" stroke="#63b8ff" d="M32.92,-2232.11C32.16,-2440.84 27.67,-4247.34 100,-4331.5 108.53,-4341.42 120.58,-4347.04 133.32,-4350.03"/>
+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.42,-2232.02 32.96,-2222.01 29.42,-2231.99 36.42,-2232.02"/>
</a>
</g>
</g>
@@ -219,8 +219,8 @@
<g id="Node000188" class="node">
<title>Node188</title>
<g id="a_Node000188"><a xlink:href="classtvm_1_1SourceNode.html" target="_top" xlink:title=" ">
-<polygon fill="white" stroke="#666666" points="249,-4370 148,-4370 148,-4351 249,-4351 249,-4370"/>
-<text text-anchor="middle" x="198.5" y="-4358" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::SourceNode</text>
+<polygon fill="white" stroke="#666666" points="249,-4322 148,-4322 148,-4303 249,-4303 249,-4322"/>
+<text text-anchor="middle" x="198.5" y="-4310" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::SourceNode</text>
</a>
</g>
</g>
@@ -228,8 +228,8 @@
<g id="edge192_Node000000_Node000188" class="edge">
<title>Node0->Node188</title>
<g id="a_edge192_Node000000_Node000188"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M32.93,-2280.4C32.3,-2488.47 28.99,-4259.91 100,-4342.5 111.73,-4356.14 130.13,-4361.64 147.8,-4363.38"/>
-<polygon fill="#63b8ff" stroke="#63b8ff" points="36.43,-2280.31 32.96,-2270.3 29.43,-2280.28 36.43,-2280.31"/>
+<path fill="none" stroke="#63b8ff" d="M32.93,-2232.4C32.3,-2440.47 28.99,-4211.91 100,-4294.5 111.73,-4308.14 130.13,-4313.64 147.8,-4315.38"/>
+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.43,-2232.31 32.96,-2222.3 29.43,-2232.28 36.43,-2232.31"/>
</a>
</g>
</g>
@@ -237,8 +237,8 @@
<g id="Node000189" class="node">
<title>Node189</title>
<g id="a_Node000189"><a xlink:href="classtvm_1_1StmtNode.html" target="_top" xlink:title="Base node of all statements.">
-<polygon fill="white" stroke="#666666" points="244,-4333 153,-4333 153,-4314 244,-4314 244,-4333"/>
-<text text-anchor="middle" x="198.5" y="-4321" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::StmtNode</text>
+<polygon fill="white" stroke="#666666" points="244,-4285 153,-4285 153,-4266 244,-4266 244,-4285"/>
+<text text-anchor="middle" x="198.5" y="-4273" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::StmtNode</text>
</a>
</g>
</g>
@@ -246,8 +246,8 @@
<g id="edge193_Node000000_Node000189" class="edge">
<title>Node0->Node189</title>
<g id="a_edge193_Node000000_Node000189"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M33.27,-2280.29C35.58,-2444.15 53.11,-3578.33 100,-3916.5 122.4,-4078.07 180.5,-4269.26 194.45,-4313.87"/>
-<polygon fill="#63b8ff" stroke="#63b8ff" points="36.77,-2280.15 33.13,-2270.2 29.77,-2280.25 36.77,-2280.15"/>
+<path fill="none" stroke="#63b8ff" d="M33.27,-2232.29C35.58,-2396.15 53.11,-3530.33 100,-3868.5 122.4,-4030.07 180.5,-4221.26 194.45,-4265.87"/>
+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.77,-2232.15 33.13,-2222.2 29.77,-2232.25 36.77,-2232.15"/>
</a>
</g>
</g>
@@ -255,8 +255,8 @@
<g id="Node000204" class="node">
<title>Node204</title>
<g id="a_Node000204"><a xlink:href="classtvm_1_1TargetKindNode.html" target="_top" xlink:title="Target kind, specifies the kind of the target.">
-<polygon fill="white" stroke="#666666" points="258,-3907 139,-3907 139,-3888 258,-3888 258,-3907"/>
-<text text-anchor="middle" x="198.5" y="-3895" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::TargetKindNode</text>
+<polygon fill="white" stroke="#666666" points="258,-3859 139,-3859 139,-3840 258,-3840 258,-3859"/>
+<text text-anchor="middle" x="198.5" y="-3847" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::TargetKindNode</text>
</a>
</g>
</g>
@@ -264,8 +264,8 @@
<g id="edge208_Node000000_Node000204" class="edge">
<title>Node0->Node204</title>
<g id="a_edge208_Node000000_Node000204"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M33.12,-2280.12C34.29,-2459.93 44.91,-3816.03 100,-3879.5 109.82,-3890.81 124.22,-3896.51 138.96,-3899.11"/>
-<polygon fill="#63b8ff" stroke="#63b8ff" points="36.62,-2279.99 33.05,-2270.01 29.62,-2280.03 36.62,-2279.99"/>
+<path fill="none" stroke="#63b8ff" d="M33.12,-2232.12C34.29,-2411.93 44.91,-3768.03 100,-3831.5 109.82,-3842.81 124.22,-3848.51 138.96,-3851.11"/>
+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.62,-2231.99 33.05,-2222.01 29.62,-2232.03 36.62,-2231.99"/>
</a>
</g>
</g>
@@ -273,8 +273,8 @@
<g id="Node000205" class="node">
<title>Node205</title>
<g id="a_Node000205"><a xlink:href="classtvm_1_1TargetNode.html" target="_top" xlink:title="Compilation target.">
-<polygon fill="white" stroke="#666666" points="247.5,-3870 149.5,-3870 149.5,-3851 247.5,-3851 247.5,-3870"/>
-<text text-anchor="middle" x="198.5" y="-3858" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::TargetNode</text>
+<polygon fill="white" stroke="#666666" points="247.5,-3822 149.5,-3822 149.5,-3803 247.5,-3803 247.5,-3822"/>
+<text text-anchor="middle" x="198.5" y="-3810" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::TargetNode</text>
</a>
</g>
</g>
@@ -282,8 +282,8 @@
<g id="edge209_Node000000_Node000205" class="edge">
<title>Node0->Node205</title>
<g id="a_edge209_Node000000_Node000205"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M33.14,-2280.22C34.47,-2458.08 46.19,-3780.57 100,-3842.5 112.14,-3856.47 131.27,-3861.88 149.39,-3863.46"/>
-<polygon fill="#63b8ff" stroke="#63b8ff" points="36.64,-2280.16 33.07,-2270.19 29.64,-2280.21 36.64,-2280.16"/>
+<path fill="none" stroke="#63b8ff" d="M33.14,-2232.22C34.47,-2410.08 46.19,-3732.57 100,-3794.5 112.14,-3808.47 131.27,-3813.88 149.39,-3815.46"/>
+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.64,-2232.16 33.07,-2222.19 29.64,-2232.21 36.64,-2232.16"/>
</a>
</g>
</g>
@@ -291,8 +291,8 @@
<g id="Node000206" class="node">
<title>Node206</title>
<g id="a_Node000206"><a xlink:href="classtvm_1_1TypeNode.html" target="_top" xlink:title="Type is the base type of all types.">
-<polygon fill="white" stroke="#666666" points="243.5,-3833 153.5,-3833 153.5,-3814 243.5,-3814 243.5,-3833"/>
-<text text-anchor="middle" x="198.5" y="-3821" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::TypeNode</text>
+<polygon fill="white" stroke="#666666" points="243.5,-3785 153.5,-3785 153.5,-3766 243.5,-3766 243.5,-3785"/>
+<text text-anchor="middle" x="198.5" y="-3773" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::TypeNode</text>
</a>
</g>
</g>
@@ -300,8 +300,8 @@
<g id="edge210_Node000000_Node000206" class="edge">
<title>Node0->Node206</title>
<g id="a_edge210_Node000000_Node000206"><a xlink:title=" ">
-<path fill="none" stroke="#63b8ff" d="M32.97,-2280.12C32.9,-2425.77 35.07,-3340.49 100,-3608.5 120.36,-3692.55 173.39,-3784.11 191.41,-3813.7"/>
-<polygon fill="#63b8ff" stroke="#63b8ff" points="36.47,-2280.01 32.98,-2270.01 29.47,-2280 36.47,-2280.01"/>
+<path fill="none" stroke="#63b8ff" d="M32.97,-2232.12C32.9,-2377.77 35.07,-3292.49 100,-3560.5 120.36,-3644.55 173.39,-3736.11 191.41,-3765.7"/>
+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.47,-2232.01 32.98,-2222.01 29.47,-2232 36.47,-2232.01"/>
</a>
</g>
</g>
@@ -309,8 +309,8 @@
<g id="Node000223" class="node">
<title>Node223</title>
<g id="a_Node000223"><a xlink:href="classtvm_1_1UniqueNameSupplyNode.html" target="_top" xlink:title="UniqueNameSupply can be used to generate unique names.">
-<polygon fill="white" stroke="#666666" points="280.5,-3599 116.5,-3599 116.5,-3580 280.5,-3580 280.5,-3599"/>
-<text text-anchor="middle" x="198.5" y="-3587" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::UniqueNameSupplyNode</text>
+<polygon fill="white" stroke="#666666" points="280.5,-3551 116.5,-3551 116.5,-3532 280.5,-3532 280.5,-3551"/>
+<text text-anchor="middle" x="198.5" y="-3539" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::UniqueNameSupplyNode</text>
</a>
</g>
</g>
@@ -318,8 +318,8 @@
<g id="edge227_Node000000_Node000223" class="edge">
<title>Node0->Node223</title>
<g id="a_edge227_Node000000_Node000223"><a xlink:title=" ">
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<g id="Node000224" class="node">
<title>Node224</title>
<g id="a_Node000224"><a xlink:href="classtvm_1_1relax_1_1BindingBlockNode.html" target="_top" xlink:title=" ">
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-<text text-anchor="middle" x="198.5" y="-3550" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::BindingBlockNode</text>
+<polygon fill="white" stroke="#666666" points="279.5,-3514 117.5,-3514 117.5,-3495 279.5,-3495 279.5,-3514"/>
+<text text-anchor="middle" x="198.5" y="-3502" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::BindingBlockNode</text>
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<g id="edge228_Node000000_Node000224" class="edge">
<title>Node0->Node224</title>
<g id="a_edge228_Node000000_Node000224"><a xlink:title=" ">
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<g id="Node000226" class="node">
<title>Node226</title>
<g id="a_Node000226"><a xlink:href="classtvm_1_1relax_1_1BindingNode.html" target="_top" xlink:title="The base class of a variable binding in Relax.">
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-<text text-anchor="middle" x="198.5" y="-3513" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::BindingNode</text>
+<polygon fill="white" stroke="#666666" points="266,-3477 131,-3477 131,-3458 266,-3458 266,-3477"/>
+<text text-anchor="middle" x="198.5" y="-3465" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::BindingNode</text>
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<g id="edge230_Node000000_Node000226" class="edge">
<title>Node0->Node226</title>
<g id="a_edge230_Node000000_Node000226"><a xlink:title=" ">
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<g id="Node000229" class="node">
<title>Node229</title>
<g id="a_Node000229"><a xlink:href="classtvm_1_1relax_1_1BlockBuilderNode.html" target="_top" xlink:title="A builder to build Relax binding blocks.">
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-<text text-anchor="middle" x="198.5" y="-3476" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::BlockBuilderNode</text>
+<polygon fill="white" stroke="#666666" points="278.5,-3440 118.5,-3440 118.5,-3421 278.5,-3421 278.5,-3440"/>
+<text text-anchor="middle" x="198.5" y="-3428" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::BlockBuilderNode</text>
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<g id="edge233_Node000000_Node000229" class="edge">
<title>Node0->Node229</title>
<g id="a_edge233_Node000000_Node000229"><a xlink:title=" ">
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+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.91,-2232.03 33.2,-2222.1 29.91,-2232.18 36.91,-2232.03"/>
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@@ -381,8 +381,8 @@
<g id="Node000230" class="node">
<title>Node230</title>
<g id="a_Node000230"><a xlink:href="classtvm_1_1relax_1_1DFConstraintNode.html" target="_top" xlink:title="Additional constraints on the graph.">
-<polygon fill="white" stroke="#666666" points="279.5,-3451 117.5,-3451 117.5,-3432 279.5,-3432 279.5,-3451"/>
-<text text-anchor="middle" x="198.5" y="-3439" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::DFConstraintNode</text>
+<polygon fill="white" stroke="#666666" points="279.5,-3403 117.5,-3403 117.5,-3384 279.5,-3384 279.5,-3403"/>
+<text text-anchor="middle" x="198.5" y="-3391" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::DFConstraintNode</text>
</a>
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@@ -390,8 +390,8 @@
<g id="edge234_Node000000_Node000230" class="edge">
<title>Node0->Node230</title>
<g id="a_edge234_Node000000_Node000230"><a xlink:title=" ">
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+<polygon fill="#63b8ff" stroke="#63b8ff" points="36.95,-2232.06 33.22,-2222.14 29.95,-2232.22 36.95,-2232.06"/>
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@@ -399,8 +399,8 @@
<g id="Node000232" class="node">
<title>Node232</title>
<g id="a_Node000232"><a xlink:href="classtvm_1_1relax_1_1DFPatternNode.html" target="_top" xlink:title="Base type of all dataflow patterns.">
-<polygon fill="white" stroke="#666666" points="271.5,-3414 125.5,-3414 125.5,-3395 271.5,-3395 271.5,-3414"/>
-<text text-anchor="middle" x="198.5" y="-3402" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::DFPatternNode</text>
+<polygon fill="white" stroke="#666666" points="271.5,-3366 125.5,-3366 125.5,-3347 271.5,-3347 271.5,-3366"/>
+<text text-anchor="middle" x="198.5" y="-3354" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::DFPatternNode</text>
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@@ -408,8 +408,8 @@
<g id="edge236_Node000000_Node000232" class="edge">
<title>Node0->Node232</title>
<g id="a_edge236_Node000000_Node000232"><a xlink:title=" ">
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@@ -417,9 +417,9 @@
<g id="Node000253" class="node">
<title>Node253</title>
<g id="a_Node000253"><a xlink:href="classtvm_1_1relax_1_1DataflowBlockRewriteNode.html" target="_top" xlink:title="Statement rewriter for relax.DataflowBlock.">
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-<text text-anchor="start" x="135" y="-3364.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::DataflowBlock</text>
-<text text-anchor="middle" x="198.5" y="-3353.5" font-family="Helvetica,sans-Serif" font-size="10.00">RewriteNode</text>
+<polygon fill="white" stroke="#666666" points="270,-3328.5 127,-3328.5 127,-3298.5 270,-3298.5 270,-3328.5"/>
+<text text-anchor="start" x="135" y="-3316.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::DataflowBlock</text>
+<text text-anchor="middle" x="198.5" y="-3305.5" font-family="Helvetica,sans-Serif" font-size="10.00">RewriteNode</text>
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<g id="edge257_Node000000_Node000253" class="edge">
<title>Node0->Node253</title>
<g id="a_edge257_Node000000_Node000253"><a xlink:title=" ">
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@@ -436,8 +436,8 @@
<g id="Node000254" class="node">
<title>Node254</title>
<g id="a_Node000254"><a xlink:href="classtvm_1_1relax_1_1ExecBuilderNode.html" target="_top" xlink:title="A builder provides api to build VM executable with instructions.">
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-<text text-anchor="middle" x="198.5" y="-3316" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::ExecBuilderNode</text>
+<polygon fill="white" stroke="#666666" points="276,-3280 121,-3280 121,-3261 276,-3261 276,-3280"/>
+<text text-anchor="middle" x="198.5" y="-3268" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::ExecBuilderNode</text>
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@@ -445,8 +445,8 @@
<g id="edge258_Node000000_Node000254" class="edge">
<title>Node0->Node254</title>
<g id="a_edge258_Node000000_Node000254"><a xlink:title=" ">
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@@ -454,8 +454,8 @@
<g id="Node000255" class="node">
<title>Node255</title>
<g id="a_Node000255"><a xlink:href="classtvm_1_1relax_1_1MatchResultNode.html" target="_top" xlink:title=" ">
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-<text text-anchor="middle" x="198.5" y="-3279" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::MatchResultNode</text>
+<polygon fill="white" stroke="#666666" points="278,-3243 119,-3243 119,-3224 278,-3224 278,-3243"/>
+<text text-anchor="middle" x="198.5" y="-3231" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::MatchResultNode</text>
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<g id="edge259_Node000000_Node000255" class="edge">
<title>Node0->Node255</title>
<g id="a_edge259_Node000000_Node000255"><a xlink:title=" ">
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@@ -472,8 +472,8 @@
<g id="Node000256" class="node">
<title>Node256</title>
<g id="a_Node000256"><a xlink:href="classtvm_1_1relax_1_1PatternContextNode.html" target="_top" xlink:title="A context to manage the graph-level pattern matching.">
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-<text text-anchor="middle" x="198.5" y="-3242" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::PatternContextNode</text>
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+<text text-anchor="middle" x="198.5" y="-3194" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::PatternContextNode</text>
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<g id="edge260_Node000000_Node000256" class="edge">
<title>Node0->Node256</title>
<g id="a_edge260_Node000000_Node000256"><a xlink:title=" ">
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@@ -490,8 +490,8 @@
<g id="Node000257" class="node">
<title>Node257</title>
<g id="a_Node000257"><a xlink:href="classtvm_1_1relax_1_1PatternSeqNode.html" target="_top" xlink:title="A sequence of DFPatterns that the previous DFPattern is connected to the next one.">
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-<text text-anchor="middle" x="198.5" y="-3205" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::PatternSeqNode</text>
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+<text text-anchor="middle" x="198.5" y="-3157" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::PatternSeqNode</text>
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<g id="edge261_Node000000_Node000257" class="edge">
<title>Node0->Node257</title>
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@@ -508,9 +508,9 @@
<g id="Node000258" class="node">
<title>Node258</title>
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+<text text-anchor="start" x="144" y="-3119.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::distributed</text>
+<text text-anchor="middle" x="198.5" y="-3108.5" font-family="Helvetica,sans-Serif" font-size="10.00">::PlacementNode</text>
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@@ -518,8 +518,8 @@
<g id="edge262_Node000000_Node000258" class="edge">
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@@ -527,9 +527,9 @@
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+<text text-anchor="start" x="144" y="-3071.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::distributed</text>
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@@ -537,8 +537,8 @@
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+<text text-anchor="start" x="135" y="-2071.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
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+<text text-anchor="start" x="135" y="-2023.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
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-<text text-anchor="middle" x="198.5" y="-2012.5" font-family="Helvetica,sans-Serif" font-size="10.00">::FeatureExtractorNode</text>
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+<text text-anchor="start" x="135" y="-1975.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
+<text text-anchor="middle" x="198.5" y="-1964.5" font-family="Helvetica,sans-Serif" font-size="10.00">::FeatureExtractorNode</text>
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<g id="a_Node000292"><a xlink:href="classtvm_1_1s__tir_1_1meta__schedule_1_1MeasureCallbackNode.html" target="_top" xlink:title="Rules to apply after measure results is available.">
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-<text text-anchor="start" x="135" y="-1975.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
-<text text-anchor="middle" x="198.5" y="-1964.5" font-family="Helvetica,sans-Serif" font-size="10.00">::MeasureCallbackNode</text>
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+<text text-anchor="start" x="135" y="-1927.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
+<text text-anchor="middle" x="198.5" y="-1916.5" font-family="Helvetica,sans-Serif" font-size="10.00">::MeasureCallbackNode</text>
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-<text text-anchor="start" x="135" y="-1927.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
-<text text-anchor="middle" x="198.5" y="-1916.5" font-family="Helvetica,sans-Serif" font-size="10.00">::MeasureCandidateNode</text>
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+<text text-anchor="start" x="135" y="-1879.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
+<text text-anchor="middle" x="198.5" y="-1868.5" font-family="Helvetica,sans-Serif" font-size="10.00">::MeasureCandidateNode</text>
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+<text text-anchor="start" x="135" y="-1831.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
+<text text-anchor="middle" x="198.5" y="-1820.5" font-family="Helvetica,sans-Serif" font-size="10.00">::MutatorNode</text>
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+<text text-anchor="start" x="135" y="-1783.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
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-<text text-anchor="start" x="135" y="-1783.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
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+<text text-anchor="start" x="135" y="-1735.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
+<text text-anchor="middle" x="198.5" y="-1724.5" font-family="Helvetica,sans-Serif" font-size="10.00">::ProfilerNode</text>
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+<text text-anchor="start" x="135" y="-1687.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
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+<text text-anchor="start" x="135" y="-1495.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
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+<text text-anchor="start" x="135" y="-1447.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
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+<text text-anchor="start" x="135" y="-1351.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::s_tir::meta_schedule</text>
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<g id="Node000339" class="node">
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-<text text-anchor="middle" x="198.5" y="-1100.5" font-family="Helvetica,sans-Serif" font-size="10.00">::IRBuilderNode</text>
+<polygon fill="white" stroke="#666666" points="259,-1075.5 138,-1075.5 138,-1045.5 259,-1045.5 259,-1075.5"/>
+<text text-anchor="start" x="146" y="-1063.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::ir_builder</text>
+<text text-anchor="middle" x="198.5" y="-1052.5" font-family="Helvetica,sans-Serif" font-size="10.00">::IRBuilderNode</text>
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<title>Node340</title>
<g id="a_Node000340"><a xlink:href="classtvm_1_1script_1_1printer_1_1DocNode.html" target="_top" xlink:title="The base class of all Doc.">
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-<text text-anchor="start" x="153" y="-1063.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
-<text text-anchor="middle" x="198.5" y="-1052.5" font-family="Helvetica,sans-Serif" font-size="10.00">::DocNode</text>
+<polygon fill="white" stroke="#666666" points="252,-1027.5 145,-1027.5 145,-997.5 252,-997.5 252,-1027.5"/>
+<text text-anchor="start" x="153" y="-1015.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
+<text text-anchor="middle" x="198.5" y="-1004.5" font-family="Helvetica,sans-Serif" font-size="10.00">::DocNode</text>
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+</g>
+</g>
+<!-- Node371 -->
+<g id="Node000371" class="node">
+<title>Node371</title>
+<g id="a_Node000371"><a xlink:href="classtvm_1_1script_1_1printer_1_1DocTranslatorObj.html" target="_top" xlink:title="Eager translation context shared by registered hooks. Hooks construct Docs, use explicit lexical scop...">
+<polygon fill="white" stroke="#666666" points="252,-979.5 145,-979.5 145,-949.5 252,-949.5 252,-979.5"/>
+<text text-anchor="start" x="153" y="-967.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
+<text text-anchor="middle" x="198.5" y="-956.5" font-family="Helvetica,sans-Serif" font-size="10.00">::DocTranslatorObj</text>
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+<!-- Node0->Node371 -->
+<g id="edge375_Node000000_Node000371" class="edge">
+<title>Node0->Node371</title>
+<g id="a_edge375_Node000000_Node000371"><a xlink:title=" ">
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<g id="Node000372" class="node">
<title>Node372</title>
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-<text text-anchor="start" x="153" y="-1015.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::script::printer</text>
-<text text-anchor="middle" x="198.5" y="-1004.5" font-family="Helvetica,sans-Serif" font-size="10.00">::DocTranslatorObj</text>
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+<polygon fill="white" stroke="#666666" points="262.5,-931 134.5,-931 134.5,-912 262.5,-912 262.5,-931"/>
+<text text-anchor="middle" x="198.5" y="-919" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::sym::AnalyzerObj</text>
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<g id="edge376_Node000000_Node000372" class="edge">
<title>Node0->Node372</title>
<g id="a_edge376_Node000000_Node000372"><a xlink:title=" ">
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<g id="Node000373" class="node">
<title>Node373</title>
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-<text text-anchor="middle" x="198.5" y="-967" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::sym::AnalyzerObj</text>
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+<text text-anchor="middle" x="198.5" y="-882" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::sym::ConstIntBoundNode</text>
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<title>Node0->Node373</title>
<g id="a_edge377_Node000000_Node000373"><a xlink:title=" ">
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<g id="Node000374" class="node">
<title>Node374</title>
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-<text text-anchor="middle" x="198.5" y="-930" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::sym::ConstIntBoundNode</text>
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<g id="Node000375" class="node">
<title>Node375</title>
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-<text text-anchor="middle" x="198.5" y="-893" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::sym::IntSetNode</text>
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+<text text-anchor="middle" x="198.5" y="-808" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::sym::IterMapResultNode</text>
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<title>Node0->Node375</title>
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<g id="Node000376" class="node">
<title>Node376</title>
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<g id="edge380_Node000000_Node000376" class="edge">
<title>Node0->Node376</title>
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<g id="Node000377" class="node">
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-<text text-anchor="middle" x="198.5" y="-708" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::te::OperationNode</text>
+<!-- Node385 -->
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+<title>Node385</title>
+<g id="a_Node000385"><a xlink:href="classtvm_1_1tirx_1_1DependencyNode.html" target="_top" xlink:title="A tuple (src, dst, kind) representing certain types of dependency. For example, (A,...">
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+<!-- Node0->Node385 -->
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+<title>Node0->Node385</title>
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<g id="Node000386" class="node">
<title>Node386</title>
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-<text text-anchor="middle" x="198.5" y="-671" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::DependencyNode</text>
+<g id="a_Node000386"><a xlink:href="classtvm_1_1tirx_1_1DispatchContextNode.html" target="_top" xlink:title="The context information of the kernel required by op dispatch.">
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+<text text-anchor="middle" x="198.5" y="-586" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::DispatchContextNode</text>
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<g id="edge390_Node000000_Node000386" class="edge">
<title>Node0->Node386</title>
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<g id="Node000387" class="node">
<title>Node387</title>
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-<text text-anchor="middle" x="198.5" y="-634" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::DispatchContextNode</text>
+<g id="a_Node000387"><a xlink:href="classtvm_1_1tirx_1_1ExecScopeNode.html" target="_top" xlink:title=" ">
+<polygon fill="white" stroke="#666666" points="269.5,-561 127.5,-561 127.5,-542 269.5,-542 269.5,-561"/>
+<text text-anchor="middle" x="198.5" y="-549" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::ExecScopeNode</text>
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<g id="edge391_Node000000_Node000387" class="edge">
<title>Node0->Node387</title>
<g id="a_edge391_Node000000_Node000387"><a xlink:title=" ">
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<g id="Node000388" class="node">
<title>Node388</title>
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-<text text-anchor="middle" x="198.5" y="-597" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::ExecScopeNode</text>
+<g id="a_Node000388"><a xlink:href="classtvm_1_1tirx_1_1IndexMapNode.html" target="_top" xlink:title="Defines a mapping between two representations of indices into a buffer.">
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+<text text-anchor="middle" x="198.5" y="-512" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::IndexMapNode</text>
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<g id="edge392_Node000000_Node000388" class="edge">
<title>Node0->Node388</title>
<g id="a_edge392_Node000000_Node000388"><a xlink:title=" ">
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<g id="Node000389" class="node">
<title>Node389</title>
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-<text text-anchor="middle" x="198.5" y="-560" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::IndexMapNode</text>
+<g id="a_Node000389"><a xlink:href="classtvm_1_1tirx_1_1IterNode.html" target="_top" xlink:title=" ">
+<polygon fill="white" stroke="#666666" points="252,-487 145,-487 145,-468 252,-468 252,-487"/>
+<text text-anchor="middle" x="198.5" y="-475" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::IterNode</text>
</a>
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<g id="edge393_Node000000_Node000389" class="edge">
<title>Node0->Node389</title>
<g id="a_edge393_Node000000_Node000389"><a xlink:title=" ">
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<g id="Node000390" class="node">
<title>Node390</title>
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-<polygon fill="white" stroke="#666666" points="252,-535 145,-535 145,-516 252,-516 252,-535"/>
-<text text-anchor="middle" x="198.5" y="-523" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::IterNode</text>
+<g id="a_Node000390"><a xlink:href="classtvm_1_1tirx_1_1LayoutNode.html" target="_top" xlink:title=" ">
+<polygon fill="white" stroke="#666666" points="260,-450 137,-450 137,-431 260,-431 260,-450"/>
+<text text-anchor="middle" x="198.5" y="-438" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::LayoutNode</text>
</a>
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<g id="edge394_Node000000_Node000390" class="edge">
<title>Node0->Node390</title>
<g id="a_edge394_Node000000_Node000390"><a xlink:title=" ">
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-<g id="Node000391" class="node">
-<title>Node391</title>
-<g id="a_Node000391"><a xlink:href="classtvm_1_1tirx_1_1LayoutNode.html" target="_top" xlink:title=" ">
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-<text text-anchor="middle" x="198.5" y="-486" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::LayoutNode</text>
+<!-- Node393 -->
+<g id="Node000393" class="node">
+<title>Node393</title>
+<g id="a_Node000393"><a xlink:href="classtvm_1_1tirx_1_1SBijectiveLayoutNode.html" target="_top" xlink:title=" ">
+<polygon fill="white" stroke="#666666" points="284.5,-413 112.5,-413 112.5,-394 284.5,-394 284.5,-413"/>
+<text text-anchor="middle" x="198.5" y="-401" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::SBijectiveLayoutNode</text>
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-<title>Node0->Node391</title>
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+<title>Node0->Node393</title>
+<g id="a_edge397_Node000000_Node000393"><a xlink:title=" ">
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<g id="Node000394" class="node">
<title>Node394</title>
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-<text text-anchor="middle" x="198.5" y="-449" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::SBijectiveLayoutNode</text>
+<g id="a_Node000394"><a xlink:href="classtvm_1_1tirx_1_1SBlockDependenceInfoNode.html" target="_top" xlink:title="An object that helps build and query block level dependences using the 2 core objects SBlockScope and...">
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+<text text-anchor="start" x="127.5" y="-363.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::SBlockDependence</text>
+<text text-anchor="middle" x="198.5" y="-352.5" font-family="Helvetica,sans-Serif" font-size="10.00">InfoNode</text>
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<g id="edge398_Node000000_Node000394" class="edge">
<title>Node0->Node394</title>
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<g id="Node000395" class="node">
<title>Node395</title>
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-<text text-anchor="start" x="127.5" y="-411.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::SBlockDependence</text>
-<text text-anchor="middle" x="198.5" y="-400.5" font-family="Helvetica,sans-Serif" font-size="10.00">InfoNode</text>
+<g id="a_Node000395"><a xlink:href="classtvm_1_1tirx_1_1SBlockScopeNode.html" target="_top" xlink:title="An object with 1-to-1 correspondence with each block reference in the sref tree. This data structure ...">
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+<text text-anchor="middle" x="198.5" y="-315" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::tirx::SBlockScopeNode</text>
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<g id="Node000396" class="node">
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<g id="a_Node000009"><a xlink:href="structtvm_1_1relax_1_1AdaptivePool3DAttrs.html" target="_top" xlink:title="Attributes for 3d adaptive pool operator.">
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-<text text-anchor="start" x="372.5" y="-10194.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AdaptivePool3</text>
-<text text-anchor="middle" x="436" y="-10183.5" font-family="Helvetica,sans-Serif" font-size="10.00">DAttrs</text>
+<polygon fill="white" stroke="#666666" points="507.5,-10158.5 364.5,-10158.5 364.5,-10128.5 507.5,-10128.5 507.5,-10158.5"/>
+<text text-anchor="start" x="372.5" y="-10146.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AdaptivePool3</text>
+<text text-anchor="middle" x="436" y="-10135.5" font-family="Helvetica,sans-Serif" font-size="10.00">DAttrs</text>
</a>
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<g id="edge13_Node000002_Node000009" class="edge">
<title>Node2->Node9</title>
<g id="a_edge13_Node000002_Node000009"><a xlink:title=" ">
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@@ -1973,8 +1973,8 @@
<g id="Node000010" class="node">
<title>Node10</title>
<g id="a_Node000010"><a xlink:href="structtvm_1_1relax_1_1AffineGridAttrs.html" target="_top" xlink:title="Attributes used in image affine_grid operator.">
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-<text text-anchor="middle" x="436" y="-10146" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AffineGridAttrs</text>
+<polygon fill="white" stroke="#666666" points="508.5,-10110 363.5,-10110 363.5,-10091 508.5,-10091 508.5,-10110"/>
+<text text-anchor="middle" x="436" y="-10098" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AffineGridAttrs</text>
</a>
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<g id="edge14_Node000002_Node000010" class="edge">
<title>Node2->Node10</title>
<g id="a_edge14_Node000002_Node000010"><a xlink:title=" ">
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<g id="Node000011" class="node">
<title>Node11</title>
<g id="a_Node000011"><a xlink:href="structtvm_1_1relax_1_1AllClassNonMaximumSuppressionAttrs.html" target="_top" xlink:title="Attributes used in AllClassNonMaximumSuppression operator.">
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-<text text-anchor="start" x="353.5" y="-10108.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AllClassNonMaximum</text>
-<text text-anchor="middle" x="436" y="-10097.5" font-family="Helvetica,sans-Serif" font-size="10.00">SuppressionAttrs</text>
+<polygon fill="white" stroke="#666666" points="526.5,-10072.5 345.5,-10072.5 345.5,-10042.5 526.5,-10042.5 526.5,-10072.5"/>
+<text text-anchor="start" x="353.5" y="-10060.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AllClassNonMaximum</text>
+<text text-anchor="middle" x="436" y="-10049.5" font-family="Helvetica,sans-Serif" font-size="10.00">SuppressionAttrs</text>
</a>
</g>
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<g id="edge15_Node000002_Node000011" class="edge">
<title>Node2->Node11</title>
<g id="a_edge15_Node000002_Node000011"><a xlink:title=" ">
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-<polygon fill="#63b8ff" stroke="#63b8ff" points="254.32,-8609.24 244,-8611.66 253.57,-8616.2 254.32,-8609.24"/>
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</a>
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</g>
@@ -2010,8 +2010,8 @@
<g id="Node000012" class="node">
<title>Node12</title>
<g id="a_Node000012"><a xlink:href="structtvm_1_1relax_1_1AllGatherAttrs.html" target="_top" xlink:title="Attributes used in allgather operators.">
-<polygon fill="white" stroke="#666666" points="507,-10072 365,-10072 365,-10053 507,-10053 507,-10072"/>
-<text text-anchor="middle" x="436" y="-10060" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AllGatherAttrs</text>
+<polygon fill="white" stroke="#666666" points="507,-10024 365,-10024 365,-10005 507,-10005 507,-10024"/>
+<text text-anchor="middle" x="436" y="-10012" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AllGatherAttrs</text>
</a>
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</g>
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<g id="edge16_Node000002_Node000012" class="edge">
<title>Node2->Node12</title>
<g id="a_edge16_Node000002_Node000012"><a xlink:title=" ">
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-<polygon fill="#63b8ff" stroke="#63b8ff" points="254.57,-8609.28 244.25,-8611.68 253.81,-8616.24 254.57,-8609.28"/>
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+<polygon fill="#63b8ff" stroke="#63b8ff" points="254.57,-8561.28 244.25,-8563.68 253.81,-8568.24 254.57,-8561.28"/>
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@@ -2028,8 +2028,8 @@
<g id="Node000013" class="node">
<title>Node13</title>
<g id="a_Node000013"><a xlink:href="structtvm_1_1relax_1_1AllReduceAttrs.html" target="_top" xlink:title="Attributes used in allreduce operators.">
-<polygon fill="white" stroke="#666666" points="508.5,-10035 363.5,-10035 363.5,-10016 508.5,-10016 508.5,-10035"/>
-<text text-anchor="middle" x="436" y="-10023" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AllReduceAttrs</text>
+<polygon fill="white" stroke="#666666" points="508.5,-9987 363.5,-9987 363.5,-9968 508.5,-9968 508.5,-9987"/>
+<text text-anchor="middle" x="436" y="-9975" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AllReduceAttrs</text>
</a>
</g>
</g>
@@ -2037,8 +2037,8 @@
<g id="edge17_Node000002_Node000013" class="edge">
<title>Node2->Node13</title>
<g id="a_edge17_Node000002_Node000013"><a xlink:title=" ">
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+<polygon fill="#63b8ff" stroke="#63b8ff" points="254.56,-8561.28 244.24,-8563.68 253.81,-8568.24 254.56,-8561.28"/>
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@@ -2046,9 +2046,9 @@
<g id="Node000014" class="node">
<title>Node14</title>
<g id="a_Node000014"><a xlink:href="structtvm_1_1relax_1_1ArgmaxArgminAttrs.html" target="_top" xlink:title="Attributes for search operators.">
-<polygon fill="white" stroke="#666666" points="509,-9997.5 363,-9997.5 363,-9967.5 509,-9967.5 509,-9997.5"/>
-<text text-anchor="start" x="371" y="-9985.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::ArgmaxArgmin</text>
-<text text-anchor="middle" x="436" y="-9974.5" font-family="Helvetica,sans-Serif" font-size="10.00">Attrs</text>
+<polygon fill="white" stroke="#666666" points="509,-9949.5 363,-9949.5 363,-9919.5 509,-9919.5 509,-9949.5"/>
+<text text-anchor="start" x="371" y="-9937.5" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::ArgmaxArgmin</text>
+<text text-anchor="middle" x="436" y="-9926.5" font-family="Helvetica,sans-Serif" font-size="10.00">Attrs</text>
</a>
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</g>
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<g id="edge18_Node000002_Node000014" class="edge">
<title>Node2->Node14</title>
<g id="a_edge18_Node000002_Node000014"><a xlink:title=" ">
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@@ -2065,8 +2065,8 @@
<g id="Node000015" class="node">
<title>Node15</title>
<g id="a_Node000015"><a xlink:href="structtvm_1_1relax_1_1ArgsortAttrs.html" target="_top" xlink:title="Attributes used in argsort operator.">
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-<text text-anchor="middle" x="436" y="-9937" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::ArgsortAttrs</text>
+<polygon fill="white" stroke="#666666" points="501.5,-9901 370.5,-9901 370.5,-9882 501.5,-9882 501.5,-9901"/>
+<text text-anchor="middle" x="436" y="-9889" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::ArgsortAttrs</text>
</a>
</g>
</g>
@@ -2074,8 +2074,8 @@
<g id="edge19_Node000002_Node000015" class="edge">
<title>Node2->Node15</title>
<g id="a_edge19_Node000002_Node000015"><a xlink:title=" ">
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@@ -2083,8 +2083,8 @@
<g id="Node000016" class="node">
<title>Node16</title>
<g id="a_Node000016"><a xlink:href="structtvm_1_1relax_1_1AstypeAttrs.html" target="_top" xlink:title="Attributes used in astype operator.">
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-<text text-anchor="middle" x="436" y="-9900" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AstypeAttrs</text>
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+<text text-anchor="middle" x="436" y="-9852" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AstypeAttrs</text>
</a>
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</g>
@@ -2092,8 +2092,8 @@
<g id="edge20_Node000002_Node000016" class="edge">
<title>Node2->Node16</title>
<g id="a_edge20_Node000002_Node000016"><a xlink:title=" ">
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@@ -2101,8 +2101,8 @@
<g id="Node000017" class="node">
<title>Node17</title>
<g id="a_Node000017"><a xlink:href="structtvm_1_1relax_1_1AttentionAttrs.html" target="_top" xlink:title="Attributes used in Attention operator.">
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-<text text-anchor="middle" x="436" y="-9863" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AttentionAttrs</text>
+<polygon fill="white" stroke="#666666" points="506.5,-9827 365.5,-9827 365.5,-9808 506.5,-9808 506.5,-9827"/>
+<text text-anchor="middle" x="436" y="-9815" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::AttentionAttrs</text>
</a>
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@@ -2110,8 +2110,8 @@
<g id="edge21_Node000002_Node000017" class="edge">
<title>Node2->Node17</title>
<g id="a_edge21_Node000002_Node000017"><a xlink:title=" ">
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@@ -2119,8 +2119,8 @@
<g id="Node000018" class="node">
<title>Node18</title>
<g id="a_Node000018"><a xlink:href="structtvm_1_1relax_1_1BatchNormAttrs.html" target="_top" xlink:title="Attributes used in batch_norm operator.">
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-<text text-anchor="middle" x="436" y="-9826" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::BatchNormAttrs</text>
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+<text text-anchor="middle" x="436" y="-9778" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::BatchNormAttrs</text>
</a>
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@@ -2128,8 +2128,8 @@
<g id="edge22_Node000002_Node000018" class="edge">
<title>Node2->Node18</title>
<g id="a_edge22_Node000002_Node000018"><a xlink:title=" ">
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@@ -2137,8 +2137,8 @@
<g id="Node000019" class="node">
<title>Node19</title>
<g id="a_Node000019"><a xlink:href="structtvm_1_1relax_1_1BucketizeAttrs.html" target="_top" xlink:title="Attributes for bucketize operator.">
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-<text text-anchor="middle" x="436" y="-9789" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::BucketizeAttrs</text>
+<polygon fill="white" stroke="#666666" points="507.5,-9753 364.5,-9753 364.5,-9734 507.5,-9734 507.5,-9753"/>
+<text text-anchor="middle" x="436" y="-9741" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::BucketizeAttrs</text>
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@@ -2146,8 +2146,8 @@
<g id="edge23_Node000002_Node000019" class="edge">
<title>Node2->Node19</title>
<g id="a_edge23_Node000002_Node000019"><a xlink:title=" ">
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@@ -2155,9 +2155,9 @@
<g id="Node000020" class="node">
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<g id="Node000031" class="node">
<title>Node31</title>
<g id="a_Node000031"><a xlink:href="structtvm_1_1relax_1_1DropoutAttrs.html" target="_top" xlink:title="Attributes used in dropout operator.">
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-<text text-anchor="middle" x="436" y="-9264" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::DropoutAttrs</text>
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+<text text-anchor="middle" x="436" y="-9216" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::DropoutAttrs</text>
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<g id="edge35_Node000002_Node000031" class="edge">
<title>Node2->Node31</title>
<g id="a_edge35_Node000002_Node000031"><a xlink:title=" ">
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<g id="Node000032" class="node">
<title>Node32</title>
<g id="a_Node000032"><a xlink:href="structtvm_1_1relax_1_1EinsumAttrs.html" target="_top" xlink:title="Attributes used in einsum operator.">
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-<text text-anchor="middle" x="436" y="-9227" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::EinsumAttrs</text>
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+<text text-anchor="middle" x="436" y="-9179" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::EinsumAttrs</text>
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<g id="edge36_Node000002_Node000032" class="edge">
<title>Node2->Node32</title>
<g id="a_edge36_Node000002_Node000032"><a xlink:title=" ">
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<g id="Node000033" class="node">
<title>Node33</title>
<g id="a_Node000033"><a xlink:href="structtvm_1_1relax_1_1ExpandDimsAttrs.html" target="_top" xlink:title="Attributes used in expand_dims operators.">
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-<text text-anchor="middle" x="436" y="-9190" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::ExpandDimsAttrs</text>
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+<text text-anchor="middle" x="436" y="-9142" font-family="Helvetica,sans-Serif" font-size="10.00">tvm::relax::ExpandDimsAttrs</text>
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<g id="edge37_Node000002_Node000033" class="edge">
<title>Node2->Node33</title>
<g id="a_edge37_Node000002_Node000033"><a xlink:title=" ">
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<g id="Node000034" class="node">
<title>Node34</title>
<g id="a_Node000034"><a xlink:href="structtvm_1_1relax_1_1FlipAttrs.html" target="_top" xlink:title="Attributes used in flip operators.">
... 17838 lines suppressed ...