You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2020/07/12 00:08:01 UTC
[GitHub] [incubator-tvm] zhiics commented on a change in pull request #5235: [Fix] i64 indices
zhiics commented on a change in pull request #5235:
URL: https://github.com/apache/incubator-tvm/pull/5235#discussion_r453248169
##########
File path: tests/python/relay/test_pass_fuse_ops.py
##########
@@ -621,6 +621,81 @@ def expected():
after = run_opt_pass(expected(), transform.InferType())
assert tvm.ir.structural_equal(zz, after)
+
+def test_fuse_take():
Review comment:
I may miss something, but could you elaborate a bit why fusion is related to this change?
##########
File path: tests/python/relay/test_pass_fuse_ops.py
##########
@@ -621,6 +621,81 @@ def expected():
after = run_opt_pass(expected(), transform.InferType())
assert tvm.ir.structural_equal(zz, after)
+
+def test_fuse_take():
+ """Test fusion case involving concat and take"""
+
+ def before():
+ shape = (tvm.tir.const(10, "int64"),
+ tvm.tir.const(1, "int64"))
+ x = relay.var("x", shape=shape)
+ concat = relay.concatenate([x,x], axis=-1)
+ out = relay.op.take(concat, indices=relay.const([0], dtype="int64"))
+ return relay.Function(relay.analysis.free_vars(out), out)
+
+ def expected():
+ shape1 = (tvm.tir.const(10, "int64"),
+ tvm.tir.const(1, "int64"))
+ shape2 = (tvm.tir.const(1, "int64"),)
+ x = relay.var("x", shape=shape1)
+ p0 = relay.var("p0", shape=shape1)
+ p1 = relay.var("p1", shape=shape2,
+ dtype="int64")
+ c = relay.const([0], dtype="int64")
+ concat = relay.concatenate([p0,p0], axis=-1)
+ out = relay.op.take(concat, indices=p1)
+
+ f0 = relay.Function([p0, p1], out)
+ f0 = f0.with_attr("Primitive", tvm.tir.IntImm("int32", 1))
+
+ y = relay.Call(f0, [x, c])
+ return relay.Function([x], y)
+
+ orig = before()
+ fuse0(tvm.IRModule.from_expr(orig))
Review comment:
no used?
##########
File path: tests/python/relay/test_pass_fuse_ops.py
##########
@@ -621,6 +621,81 @@ def expected():
after = run_opt_pass(expected(), transform.InferType())
assert tvm.ir.structural_equal(zz, after)
+
+def test_fuse_take():
+ """Test fusion case involving concat and take"""
+
+ def before():
+ shape = (tvm.tir.const(10, "int64"),
+ tvm.tir.const(1, "int64"))
+ x = relay.var("x", shape=shape)
+ concat = relay.concatenate([x,x], axis=-1)
+ out = relay.op.take(concat, indices=relay.const([0], dtype="int64"))
+ return relay.Function(relay.analysis.free_vars(out), out)
+
+ def expected():
+ shape1 = (tvm.tir.const(10, "int64"),
+ tvm.tir.const(1, "int64"))
+ shape2 = (tvm.tir.const(1, "int64"),)
+ x = relay.var("x", shape=shape1)
+ p0 = relay.var("p0", shape=shape1)
+ p1 = relay.var("p1", shape=shape2,
+ dtype="int64")
+ c = relay.const([0], dtype="int64")
+ concat = relay.concatenate([p0,p0], axis=-1)
+ out = relay.op.take(concat, indices=p1)
+
+ f0 = relay.Function([p0, p1], out)
+ f0 = f0.with_attr("Primitive", tvm.tir.IntImm("int32", 1))
+
+ y = relay.Call(f0, [x, c])
+ return relay.Function([x], y)
+
+ orig = before()
+ fuse0(tvm.IRModule.from_expr(orig))
+ m = fuse2(tvm.IRModule.from_expr(orig))
+ relay.build(m, 'llvm')
+ after = run_opt_pass(expected(), transform.InferType())
+ assert tvm.ir.structural_equal(m["main"], after)
+
+
+def test_fuse_gather_nd():
+ """Test fusion case involving concat and gather_nd"""
+
+ def before():
+ shape = (tvm.tir.const(10, "int64"),
+ tvm.tir.const(1, "int64"))
+ x = relay.var("x", shape=shape)
+ concat = relay.concatenate([x,x], axis=-1)
+ out = relay.gather_nd(concat, indices=relay.expr.const([[0,1],[1,0]], dtype="int64"))
+ return relay.Function(relay.analysis.free_vars(out), out)
+
+ def expected():
+ shape1 = (tvm.tir.const(10, "int64"),
+ tvm.tir.const(1, "int64"))
+ shape2 = (tvm.tir.const(2, "int64"),
+ tvm.tir.const(2, "int64"))
+ x = relay.var("x", shape=shape1)
+ p0 = relay.var("p0", shape=shape1)
+ p1 = relay.var("p1", shape=shape2, dtype="int64")
+ c = relay.const([[0,1],[1,0]], dtype="int64")
+ concat = relay.concatenate([p0,p0], axis=-1)
+ out = relay.gather_nd(concat, indices=p1)
+
+ f0 = relay.Function([p0, p1], out)
+ f0 = f0.with_attr("Primitive", tvm.tir.IntImm("int32", 1))
+
+ y = relay.Call(f0, [x, c])
+ return relay.Function([x], y)
+
+ orig = before()
+ fuse0(tvm.IRModule.from_expr(orig))
Review comment:
not used?
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org