pytorch

0c705855 - fix #49064 (invalid escape) by using raw strings (#49065)

fix #49064 (invalid escape) by using raw strings (#49065) Summary: Fixes https://github.com/pytorch/pytorch/issues/49064 by using raw strings I removed `# noqa: W605` because that's the "invalid escape sequence" check: https://www.flake8rules.com/rules/W605.html I wrote a quick test to make sure the strings are the same before and after this PR. This block should print `True` (it does for me). ``` convolution_notes1 = \ {"groups_note": r"""* :attr:`groups` controls the connections between inputs and outputs. :attr:`in_channels` and :attr:`out_channels` must both be divisible by :attr:`groups`. For example, * At groups=1, all inputs are convolved to all outputs. * At groups=2, the operation becomes equivalent to having two conv layers side by side, each seeing half the input channels and producing half the output channels, and both subsequently concatenated. * At groups= :attr:`in_channels`, each input channel is convolved with its own set of filters (of size :math:`\frac{\text{out\_channels}}{\text{in\_channels}}`).""", "depthwise_separable_note": r"""When `groups == in_channels` and `out_channels == K * in_channels`, where `K` is a positive integer, this operation is also known as a "depthwise convolution". In other words, for an input of size :math:`(N, C_{in}, L_{in})`, a depthwise convolution with a depthwise multiplier `K` can be performed with the arguments :math:`(C_\text{in}=C_\text{in}, C_\text{out}=C_\text{in} \times \text{K}, ..., \text{groups}=C_\text{in})`."""} # noqa: B950 convolution_notes2 = \ {"groups_note": """* :attr:`groups` controls the connections between inputs and outputs. :attr:`in_channels` and :attr:`out_channels` must both be divisible by :attr:`groups`. For example, * At groups=1, all inputs are convolved to all outputs. * At groups=2, the operation becomes equivalent to having two conv layers side by side, each seeing half the input channels and producing half the output channels, and both subsequently concatenated. * At groups= :attr:`in_channels`, each input channel is convolved with its own set of filters (of size :math:`\\frac{\\text{out\_channels}}{\\text{in\_channels}}`).""", # noqa: W605 "depthwise_separable_note": """When `groups == in_channels` and `out_channels == K * in_channels`, where `K` is a positive integer, this operation is also known as a "depthwise convolution". In other words, for an input of size :math:`(N, C_{in}, L_{in})`, a depthwise convolution with a depthwise multiplier `K` can be performed with the arguments :math:`(C_\\text{in}=C_\\text{in}, C_\\text{out}=C_\\text{in} \\times \\text{K}, ..., \\text{groups}=C_\\text{in})`."""} # noqa: W605,B950 print(convolution_notes1 == convolution_notes2) ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/49065 Reviewed By: agolynski Differential Revision: D25464507 Pulled By: H-Huang fbshipit-source-id: 88a65a24e3cc29774af25e09823257b2136550fe