Will Feng b37c235d86 C++/Python API parity for Conv{1,2,3}d layers, and add F::conv{1,2,3}d functionals (#28917) ... Summary: This PR changes the implementation of C++ Conv{1,2,3}d layers to exactly match the Python version, and add F::conv{1,2,3}d functionals. For more thorough testing, I will rely on the parity test mechanism which uses values from `common_nn.py` to generate the inputs and options that we are interested in testing. This PR is BC-breaking in the following way: In `Conv{1,2,3}dOptions`: - `with_bias` is renamed to `bias`. - `input_channels` is renamed to `in_channels`. - `output_channels` is renamed to `out_channels`. Pull Request resolved: https://github.com/pytorch/pytorch/pull/28917 Differential Revision: D18471526 Pulled By: yf225 fbshipit-source-id: 7a33f60654ad93cc2e043245e7ff9e0ef9da15b3		2019-11-13 12:53:31 -08:00
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__init__.py	Improve C++ maxpool and avgpool (#26521)	2019-09-25 13:52:58 -07:00
parity-tracker.md	C++/Python API parity for Conv{1,2,3}d layers, and add F::conv{1,2,3}d functionals (#28917)	2019-11-13 12:53:31 -08:00
sample_module.py	Improve C++ maxpool and avgpool (#26521)	2019-09-25 13:52:58 -07:00
torch_nn_modules.py	Add torch.nn.GELU for GELU activation (#28944)	2019-11-03 21:55:05 -08:00