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[Fix][Relax][Frontend][Torch] Emit int64 indices for sort and argsort #20254

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[Fix][Relax][Frontend][Torch] Emit int64 indices for sort and argsort #20254

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4 changes: 2 additions & 2 deletions python/tvm/relax/frontend/torch/base_fx_graph_translator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1851,7 +1851,7 @@ def _argsort(self, node: fx.Node) -> relax.Var:
x = self.env[node.args[0]]
dim = node.args[1] if len(node.args) > 1 else node.kwargs.get("dim", -1)
descending = node.args[2] if len(node.args) > 2 else node.kwargs.get("descending", False)
return self.block_builder.emit(relax.op.argsort(x, dim, descending))
return self.block_builder.emit(relax.op.argsort(x, dim, descending, dtype="int64"))

def _broadcast_to(self, node: fx.Node) -> relax.Var:
args = self.retrieve_args(node)
Expand Down Expand Up @@ -2316,7 +2316,7 @@ def _sort(self, node: fx.Node) -> relax.Var:
dim = node.args[1] if len(node.args) > 1 else node.kwargs.get("dim", -1)
descending = node.args[2] if len(node.args) > 2 else node.kwargs.get("descending", False)

indices = self.block_builder.emit(relax.op.argsort(x, dim, descending))
indices = self.block_builder.emit(relax.op.argsort(x, dim, descending, dtype="int64"))
values = self.block_builder.emit(relax.op.gather_elements(x, indices, axis=dim))
return self.block_builder.emit(relax.Tuple([values, indices]))

Expand Down
45 changes: 39 additions & 6 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 @@ -7784,25 +7784,58 @@ def forward(self, x):
@tvm.script.ir_module
class Expected:
@R.function
def main(x: R.Tensor((5, 3), dtype="float32")) -> R.Tuple(R.Tensor((5, 3), dtype="int32")):
def main(x: R.Tensor((5, 3), dtype="float32")) -> R.Tuple(R.Tensor((5, 3), dtype="int64")):
with R.dataflow():
lv: R.Tensor((5, 3), dtype="int32") = R.argsort(
x, axis=1, descending=True, dtype="int32"
lv: R.Tensor((5, 3), dtype="int64") = R.argsort(
x, axis=1, descending=True, dtype="int64"
)
lv1: R.Tensor((5, 3), dtype="float32") = R.gather_elements(x, lv, axis=1)
lv2: R.Tuple(R.Tensor((5, 3), dtype="float32"), R.Tensor((5, 3), dtype="int32")) = (
lv2: R.Tuple(R.Tensor((5, 3), dtype="float32"), R.Tensor((5, 3), dtype="int64")) = (
lv1,
lv,
)
lv3: R.Tensor((5, 3), dtype="int32") = lv2[1]
gv: R.Tuple(R.Tensor((5, 3), dtype="int32")) = (lv3,)
lv3: R.Tensor((5, 3), dtype="int64") = lv2[1]
gv: R.Tuple(R.Tensor((5, 3), dtype="int64")) = (lv3,)
R.output(gv)
return gv

example_args = (torch.randn(5, 3, dtype=torch.float32),)
verify_model(Argsort(), example_args, {}, Expected)


def test_sort():
class Sort(Module):
def forward(self, x):
return torch.sort(x, dim=1, descending=True)

@tvm.script.ir_module
class Expected:
@R.function
def main(x: R.Tensor((5, 3), dtype="float32")) -> R.Tuple(
R.Tensor((5, 3), dtype="float32"), R.Tensor((5, 3), dtype="int64")
):
with R.dataflow():
lv: R.Tensor((5, 3), dtype="int64") = R.argsort(
x, axis=1, descending=True, dtype="int64"
)
lv1: R.Tensor((5, 3), dtype="float32") = R.gather_elements(x, lv, axis=1)
lv2: R.Tuple(R.Tensor((5, 3), dtype="float32"), R.Tensor((5, 3), dtype="int64")) = (
lv1,
lv,
)
lv3: R.Tensor((5, 3), dtype="float32") = lv2[0]
lv4: R.Tensor((5, 3), dtype="int64") = lv2[1]
gv: R.Tuple(R.Tensor((5, 3), dtype="float32"), R.Tensor((5, 3), dtype="int64")) = (
lv3,
lv4,
)
R.output(gv)
return gv

example_args = (torch.randn(5, 3, dtype=torch.float32),)
verify_model(Sort(), example_args, {}, Expected)


def test_topk():
class Topk(Module):
def forward(self, x):
Expand Down
18 changes: 10 additions & 8 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 @@ -6067,10 +6067,12 @@ class Expected:
@R.function
def main(
inp_0: R.Tensor((5, 3), dtype="float32"),
) -> R.Tensor((5, 3), dtype="int32"):
) -> R.Tensor((5, 3), dtype="int64"):
with R.dataflow():
lv: R.Tensor((5, 3), dtype="int32") = R.argsort(inp_0, axis=1, descending=True)
gv: R.Tensor((5, 3), dtype="int32") = lv
lv: R.Tensor((5, 3), dtype="int64") = R.argsort(
inp_0, axis=1, descending=True, dtype="int64"
)
gv: R.Tensor((5, 3), dtype="int64") = lv
R.output(gv)
return gv

Expand All @@ -6086,18 +6088,18 @@ def forward(self, x):
class Expected:
@R.function
def main(inp_0: R.Tensor((5, 3), dtype="float32")) -> R.Tuple(
R.Tensor((5, 3), dtype="float32"), R.Tensor((5, 3), dtype="int32")
R.Tensor((5, 3), dtype="float32"), R.Tensor((5, 3), dtype="int64")
):
with R.dataflow():
lv: R.Tensor((5, 3), dtype="int32") = R.argsort(
inp_0, axis=1, descending=True, dtype="int32"
lv: R.Tensor((5, 3), dtype="int64") = R.argsort(
inp_0, axis=1, descending=True, dtype="int64"
)
lv1: R.Tensor((5, 3), dtype="float32") = R.gather_elements(inp_0, lv, axis=1)
lv2: R.Tuple(R.Tensor((5, 3), dtype="float32"), R.Tensor((5, 3), dtype="int32")) = (
lv2: R.Tuple(R.Tensor((5, 3), dtype="float32"), R.Tensor((5, 3), dtype="int64")) = (
lv1,
lv,
)
gv: R.Tuple(R.Tensor((5, 3), dtype="float32"), R.Tensor((5, 3), dtype="int32")) = (
gv: R.Tuple(R.Tensor((5, 3), dtype="float32"), R.Tensor((5, 3), dtype="int64")) = (
lv2
)
R.output(gv)
Expand Down