tlopex commented on code in PR #18633:
URL: https://github.com/apache/tvm/pull/18633#discussion_r2661585587
##########
tests/python/relax/test_transform_to_mixed_precision.py:
##########
@@ -1064,5 +1064,58 @@ def tir_identity(
tvm.ir.assert_structural_equal(Expected, After)
+def test_dynamic_strided_slice():
+ @I.ir_module
+ class Input:
+ @R.function
+ def main(
+ x: R.Tensor((2, 3, 28, 28), "float32"),
+ w: R.Tensor((4, 3, 3, 3), "float32"),
+ begin: R.Tensor((4,), "int64"),
+ end: R.Tensor((4,), "int64"),
+ strides: R.Tensor((4,), "int64"),
+ ) -> R.Tensor(None, "float32", ndim=4):
+ with R.dataflow():
+ lv: R.Tensor((2, 4, 26, 26), "float32") = R.nn.conv2d(x, w,
out_dtype="float32")
+ gv = R.dynamic_strided_slice(lv, begin, end, strides)
+ R.output(gv)
+ return gv
+
+ @I.ir_module
+ class Expected:
+ @R.function
+ def main(
+ x: R.Tensor((2, 3, 28, 28), dtype="float32"),
+ w: R.Tensor((4, 3, 3, 3), dtype="float32"),
+ begin: R.Tensor((4,), dtype="int64"),
+ end: R.Tensor((4,), dtype="int64"),
+ strides: R.Tensor((4,), dtype="int64"),
+ ) -> R.Tensor(None, dtype="float32", ndim=4):
+ with R.dataflow():
+ lv: R.Tensor((2, 3, 28, 28), dtype="float16") = R.astype(x,
dtype="float16")
+ lv1: R.Tensor((4, 3, 3, 3), dtype="float16") = R.astype(w,
dtype="float16")
+ lv2: R.Tensor((2, 4, 26, 26), dtype="float32") = R.nn.conv2d(
+ lv,
+ lv1,
+ strides=[1, 1],
+ padding=[0, 0, 0, 0],
+ dilation=[1, 1],
+ groups=1,
+ data_layout="NCHW",
+ kernel_layout="OIHW",
+ out_layout="NCHW",
+ out_dtype="float32",
+ )
+ lv3: R.Tensor((2, 4, 26, 26), dtype="float16") = R.astype(lv2,
dtype="float16")
+ lv4: R.Tensor((2, 4, 26, 26), dtype="float32") = R.astype(lv3,
dtype="float32")
+ gv: R.Tensor(None, dtype="float32", ndim=4) =
R.dynamic_strided_slice(
+ lv4, begin, end, strides
+ )
+ R.output(gv)
+ return gv
+
+ _assert_test(Input, Expected)
Review Comment:
Why we don't use `tvm.ir.assert_structural_equal` here?
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