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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2020/09/07 14:39:39 UTC
[GitHub] [incubator-tvm] xqdan opened a new issue #6413: TIR Printer bugs
xqdan opened a new issue #6413:
URL: https://github.com/apache/incubator-tvm/issues/6413
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Hi，
I am trying to use tir printer to dump ir for each pass:
'''
__TRACE_COUNTER__ = 0
def dumpir(module, info, is_before):
global __TRACE_COUNTER__
if bool(is_before) == False:
__TRACE_COUNTER__ += 1
pname = str(__TRACE_COUNTER__).rjust(2,'0') + "_" + info.name + ".ir"
with open(pname, "a") as f:
f.write(str(module))
def tx_conv2d(input_shape, filter_shape, pad, stride):
fmap = te.placeholder(input_shape, name="feature_map", dtype="float16")
weight = te.placeholder(filter_shape, name="filter", dtype="float16")
conv_res = tx_conv_compute(fmap, weight, pad, stride)
sch = tx_conv2d_schedule(conv_res)
with tvm.transform.PassContext(opt_level=3, trace=dumpir):
(tvm.lower(sch, [fmap, weight, conv_res], simple_mode=True))
'''
1, check failed for local buffer
https://github.com/apache/incubator-tvm/blob/82d157f0b83ae17fde7bbfca14110aa2f2b80b61/src/printer/tir_text_printer.cc#L196
such as: buffer(result.shared_LLB, 0x11b7170), which is not in buffer_map
2, so I comment this, then I find ir dump for 01_tir.InjectPrefetch.ir, missing buffer for a store name, which looks werid:
```
attr [] "realize_scope" = "shared_LLB";
realize(, [0:1, 0:1, 0:16, 0:32], True {
attr [IterVar(ax0_1: int32, (nullptr), "DataPar", "")] "pragma_dma_copy" = 1;
for (ax2_1: int32, 0, 16) {
for (ax3_1: int32, 0, 32) {
[0, 0, ax2_1, ax3_1] = filter[0, 0, ax2_1, ax3_1]
}
}
```
3, is this an extra ')' here ?
https://github.com/apache/incubator-tvm/blob/82d157f0b83ae17fde7bbfca14110aa2f2b80b61/src/printer/tir_text_printer.cc#L304
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[GitHub] [incubator-tvm] spectrometerHBH commented on issue #6413: TIR Printer bugs
Posted by GitBox <gi...@apache.org>.
spectrometerHBH commented on issue #6413:
URL: https://github.com/apache/incubator-tvm/issues/6413#issuecomment-688565617
Thanks for your suggestion! @xqdan
Is your codebase up-to-date? It seems to me that the source file you referenced is different from that of mainline.
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[GitHub] [incubator-tvm] xqdan closed issue #6413: TIR Printer bugs
Posted by GitBox <gi...@apache.org>.
xqdan closed issue #6413:
URL: https://github.com/apache/incubator-tvm/issues/6413
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[GitHub] [incubator-tvm] xqdan commented on issue #6413: TIR Printer bugs
Posted by GitBox <gi...@apache.org>.
xqdan commented on issue #6413:
URL: https://github.com/apache/incubator-tvm/issues/6413#issuecomment-688585767
@spectrometerHBH thanks! I checkout latest version, looks good now, close this now.
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[GitHub] [incubator-tvm] xqdan commented on issue #6413: TIR Printer bugs
Posted by GitBox <gi...@apache.org>.
xqdan commented on issue #6413:
URL: https://github.com/apache/incubator-tvm/issues/6413#issuecomment-688547478
@spectrometerHBH you can reproduce with
```
diff --git a/tests/python/unittest/test_te_schedule_tensor_core.py b/tests/python/unittest/test_te_schedule_tensor_core.py
index ae2301caf..b832a0bce 100644
--- a/tests/python/unittest/test_te_schedule_tensor_core.py
+++ b/tests/python/unittest/test_te_schedule_tensor_core.py
@@ -103,14 +103,16 @@ def intrin_wmma_store_matrix(shape):
return te.decl_tensor_intrin(C.op, intrin_func, binds={A: BA, C: BC})
-def test_tensor_core_batch_matmal():
- if not tvm.gpu(0).exist or not tvm.runtime.enabled("cuda"):
- print("skip because cuda is not enabled..")
- return
- if not nvcc.have_tensorcore(tvm.gpu(0).compute_version):
- print("skip because gpu does not support tensor core")
- return
+__TRACE_COUNTER__ = 0
+def dumpir(module, info, is_before):
+ global __TRACE_COUNTER__
+ if bool(is_before) == False:
+ __TRACE_COUNTER__ += 1
+ pname = str(__TRACE_COUNTER__).rjust(2,'0') + "_" + info.name + ".ir"
+ with open(pname, "a") as f:
+ f.write(str(module))
+def test_tensor_core_batch_matmal():
batch_size = 4
n = 512
m, l = n, n
@@ -195,7 +197,8 @@ def test_tensor_core_batch_matmal():
s[C].tensorize(kernel_i, intrin_wmma_store_matrix((32, 8, 16)))
s[CF].tensorize(_i, intrin_wmma_gemm((32, 8, 16)))
- func = tvm.build(s, [A, B, C], 'cuda')
+ with tvm.transform.PassContext(opt_level=3, trace=dumpir):
+ func = tvm.build(s, [A, B, C], 'cuda')
ctx = tvm.gpu(0)
a_np = np.random.uniform(size=(batch_size, nn, ll, 32, 16)).astype(A.dtype)
@@ -384,4 +387,4 @@ def test_tensor_core_batch_conv():
if __name__ == '__main__':
test_tensor_core_batch_matmal()
- test_tensor_core_batch_conv()
+ #test_tensor_core_batch_conv()
```
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[GitHub] [incubator-tvm] spectrometerHBH commented on issue #6413: TIR Printer bugs
Posted by GitBox <gi...@apache.org>.
spectrometerHBH commented on issue #6413:
URL: https://github.com/apache/incubator-tvm/issues/6413#issuecomment-688566205
And #5965 #6147 are PRs related to the problems you encountered. You can try to sync your codebase and see if it works now.
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[GitHub] [incubator-tvm] tqchen commented on issue #6413: TIR Printer bugs
Posted by GitBox <gi...@apache.org>.
tqchen commented on issue #6413:
URL: https://github.com/apache/incubator-tvm/issues/6413#issuecomment-688463485
cc @spectrometerHBH
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