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Remove padding_mode from torch.nn.functional.conv{1,2,3}d's docstr #20891

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Remove padding_mode from torch.nn.functional.conv{1,2,3}d's docstr #20891

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2 changes: 1 addition & 1 deletion third_party/onnx
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Submodule onnx updated 8 files
+1 −1 onnx/common/ir.h
+16 −16 onnx/defs/nn/defs.cc
+0 −7 onnx/test/shape_inference_test.py
+0 −402 onnx/test/version_converter_test.py
+0 −31 onnx/version_converter/adapters/batch_normalization_8_9.h
+0 −57 onnx/version_converter/adapters/scan_8_9.h
+0 −39 onnx/version_converter/adapters/upsample_8_9.h
+0 −29 onnx/version_converter/convert.h
9 changes: 3 additions & 6 deletions torch/nn/functional.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,7 @@


conv1d = _add_docstr(torch.conv1d, r"""
conv1d(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1, padding_mode='zeros') -> Tensor
conv1d(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1) -> Tensor

Applies a 1D convolution over an input signal composed of several input
planes.
Expand All @@ -37,7 +37,6 @@
a one-element tuple `(dW,)`. Default: 1
groups: split input into groups, :math:`\text{in\_channels}` should be divisible by
the number of groups. Default: 1
padding_mode: the type of paddings applied to both sided can be: `zeros` or `circular`. Default: `zeros`

Examples::

Expand All @@ -47,7 +46,7 @@
""")

conv2d = _add_docstr(torch.conv2d, r"""
conv2d(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1, padding_mode='zeros') -> Tensor
conv2d(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1) -> Tensor

Applies a 2D convolution over an input image composed of several input
planes.
Expand All @@ -68,7 +67,6 @@
a tuple `(dH, dW)`. Default: 1
groups: split input into groups, :math:`\text{in\_channels}` should be divisible by the
number of groups. Default: 1
padding_mode: the type of paddings applied to both sided can be: `zeros` or `circular`. Default: `zeros`

Examples::

Expand All @@ -79,7 +77,7 @@
""") # noqa: E501

conv3d = _add_docstr(torch.conv3d, r"""
conv3d(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1, padding_mode='zeros') -> Tensor
conv3d(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1) -> Tensor

Applies a 3D convolution over an input image composed of several input
planes.
Expand All @@ -100,7 +98,6 @@
a tuple `(dT, dH, dW)`. Default: 1
groups: split input into groups, :math:`\text{in\_channels}` should be divisible by
the number of groups. Default: 1
padding_mode: the type of paddings applied to both sided can be: `zeros` or `circular`. Default: `zeros`

Examples::

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