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[torchlib] Simplify squeeze #2047

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Merged
merged 3 commits into from
Jan 31, 2025
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[torchlib] Simplify squeeze #2047

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928af79
[torchlib] Simplify squeeze
justinchuby Jan 31, 2025
0b8ea93
Simplify Squeeze operation argument
justinchuby Jan 31, 2025
e4f7a7f
test
justinchuby Jan 31, 2025
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20 changes: 8 additions & 12 deletions onnxscript/function_libs/torch_lib/ops/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7861,25 +7861,18 @@ def aten_square(self: TensorType) -> TensorType:
raise NotImplementedError()


@torch_op("aten::squeeze")
@torch_op("aten::squeeze", trace_only=True)
def aten_squeeze(self: TTensor) -> TTensor:
"""squeeze(Tensor(a) self) -> Tensor(a)"""

return op.Squeeze(self)


@torch_op("aten::squeeze.dim")
@torch_op("aten::squeeze.dim", trace_only=True)
def aten_squeeze_dim(self: TTensor, dim: int) -> TTensor:
result = self
if Rank(self) > 0: # type: ignore[operator]
# check if specified dimension is 1, do squeeze
shape = op.Shape(self)
dim_size = op.Gather(shape, dim, axis=0)
if dim_size == 1:
dims = op.Reshape(dim, op.Constant(value_ints=[-1]))
result = op.Squeeze(self, dims)

return result
if len(self.shape) == 0:
return self
return op.Squeeze(self, [dim])


@torch_op("aten::squeeze.dim", complex=True, trace_only=True)
Expand All @@ -7888,6 +7881,9 @@ def aten_squeeze_dim_complex(self: TTensor, dim: int) -> TTensor:
# Account for the complex dimension in ONNX
dim = dim - 1

if len(self.shape) == 1:
# The single dimension is the complex dimension
return self
return aten_squeeze_dim(self, dim)


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16 changes: 14 additions & 2 deletions tests/function_libs/torch_lib/ops_test_data.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1443,17 +1443,29 @@ def _where_input_wrangler(
TorchLibOpInfo(
"squeeze_dim",
core_ops.aten_squeeze_dim,
).skip(
)
.skip(
matcher=lambda sample: not (len(sample.args) > 0 and isinstance(sample.args[0], int)),
reason="this Aten overload only support one tensor as input and one int as args by design",
)
.skip(
matcher=lambda sample: len(sample.input.shape) != 0
and sample.input.shape[sample.args[0]] != 1,
reason="this Aten overload only support squeeze dim with size 1",
),
TorchLibOpInfo(
"squeeze_dim",
core_ops.aten_squeeze_dim_complex,
complex=True,
).skip(
)
.skip(
matcher=lambda sample: not (len(sample.args) > 0 and isinstance(sample.args[0], int)),
reason="this Aten overload only support one tensor as input and one int as args by design",
)
.skip(
matcher=lambda sample: len(sample.input.shape) != 0
and sample.input.shape[sample.args[0]] != 1,
reason="this Aten overload only support squeeze dim with size 1",
),
TorchLibOpInfo(
"squeeze",
Expand Down
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