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[Relax][PyTorch] Add tests for all the dtypes supported in the PyTorch frontend #17926

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Merged
Hzfengsy merged 1 commit into from
May 8, 2025
Merged

[Relax][PyTorch] Add tests for all the dtypes supported in the PyTorch frontend #17926

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34 changes: 22 additions & 12 deletions tests/python/relax/test_frontend_from_exported_program.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5051,31 +5051,41 @@ def main(
verify_model(Linspace(), example_args, {}, Expected)


def test_bfloat16():
# TODO(mshr-h): Add tests for all the dtypes supported in fx frontend
@pytest.mark.parametrize(
"torch_dtype, relax_dtype",
[
(torch.float32, "float32"),
(torch.float16, "float16"),
(torch.bfloat16, "bfloat16"),
(torch.int64, "int64"),
(torch.int32, "int32"),
(torch.bool, "bool"),
],
)
def test_dtypes(torch_dtype, relax_dtype):
example_args = (
torch.randn(10, 10, dtype=torch.bfloat16),
torch.randn(10, 10, dtype=torch.bfloat16),
torch.randint(0, 10, (10, 10)).to(torch_dtype),
torch.randint(0, 10, (10, 10)).to(torch_dtype),
)

class BFloat16Model(Module):
class Model(Module):
def forward(self, lhs: torch.Tensor, rhs: torch.Tensor):
return torch.ops.aten.add(lhs, rhs)

@tvm.script.ir_module
class expected:
class Expected:
@R.function
def main(
lhs: R.Tensor((10, 10), dtype="bfloat16"),
rhs: R.Tensor((10, 10), dtype="bfloat16"),
) -> R.Tuple(R.Tensor((10, 10), dtype="bfloat16")):
lhs: R.Tensor((10, 10), dtype=relax_dtype),
rhs: R.Tensor((10, 10), dtype=relax_dtype),
) -> R.Tuple(R.Tensor((10, 10), dtype=relax_dtype)):
with R.dataflow():
lv: R.Tensor((10, 10), dtype="bfloat16") = relax.op.add(lhs, rhs)
gv: R.Tuple(R.Tensor((10, 10), dtype="bfloat16")) = (lv,)
lv: R.Tensor((10, 10), dtype=relax_dtype) = relax.op.add(lhs, rhs)
gv: R.Tuple(R.Tensor((10, 10), dtype=relax_dtype)) = (lv,)
R.output(gv)
return gv

verify_model(BFloat16Model(), example_args, {}, expected)
verify_model(Model(), example_args, {}, Expected)


if __name__ == "__main__":
Expand Down
28 changes: 19 additions & 9 deletions tests/python/relax/test_frontend_from_fx.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5416,26 +5416,36 @@ def main(
verify_model(Norm(p, dim=dim, keepdim=keepdim), input_info, {}, expected)


def test_bfloat16():
# TODO(mshr-h): Add tests for all the dtypes supported in EP frontend
class BFloat16Model(Module):
@pytest.mark.parametrize(
"torch_dtype, relax_dtype",
[
(torch.float32, "float32"),
(torch.float16, "float16"),
(torch.bfloat16, "bfloat16"),
(torch.int64, "int64"),
(torch.int32, "int32"),
(torch.bool, "bool"),
],
)
def test_dtypes(torch_dtype, relax_dtype):
class Model(Module):
def forward(self, lhs: torch.Tensor, rhs: torch.Tensor):
return torch.ops.aten.add(lhs, rhs)

@tvm.script.ir_module
class Expected:
@R.function
def main(
lhs: R.Tensor((10, 10), dtype="bfloat16"),
rhs: R.Tensor((10, 10), dtype="bfloat16"),
) -> R.Tensor((10, 10), dtype="bfloat16"):
lhs: R.Tensor((10, 10), dtype=relax_dtype),
rhs: R.Tensor((10, 10), dtype=relax_dtype),
) -> R.Tensor((10, 10), dtype=relax_dtype):
with R.dataflow():
lv: R.Tensor((10, 10), dtype="bfloat16") = relax.op.add(lhs, rhs)
gv: R.Tensor((10, 10), dtype="bfloat16") = lv
lv: R.Tensor((10, 10), dtype=relax_dtype) = relax.op.add(lhs, rhs)
gv: R.Tensor((10, 10), dtype=relax_dtype) = lv
R.output(gv)
return gv

verify_model(BFloat16Model(), [([10, 10], "bfloat16"), ([10, 10], "bfloat16")], {}, Expected)
verify_model(Model(), [([10, 10], torch_dtype), ([10, 10], torch_dtype)], {}, Expected)


def test_eye():
Expand Down
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