mirror of
https://github.com/zebrajr/pytorch.git
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b7bda236d1
Summary:
xref gh-38010 and gh-38011.
After this PR, there should be only two warnings:
```
pytorch/docs/source/index.rst:65: WARNING: toctree contains reference to nonexisting \
document 'torchvision/index'
WARNING: autodoc: failed to import class 'tensorboard.writer.SummaryWriter' from module \
'torch.utils'; the following exception was raised:
No module named 'tensorboard'
```
If tensorboard and torchvision are prerequisites to building docs, they should be added to the `requirements.txt`.
As for breaking up quantization into smaller pieces: I split out the list of supported operations and the list of modules to separate documents. I think this makes the page flow better, makes it much "lighter" in terms of page cost, and also removes some warnings since the same class names appear in multiple sub-modules.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/41321
Reviewed By: ngimel
Differential Revision: D22753099
Pulled By: mruberry
fbshipit-source-id: d504787fcf1104a0b6e3d1c12747ec53450841da
124 lines
1.9 KiB
ReStructuredText
124 lines
1.9 KiB
ReStructuredText
torch.nn.quantized
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------------------
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This module implements the quantized versions of the nn layers such as
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~`torch.nn.Conv2d` and `torch.nn.ReLU`.
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Functional interface
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~~~~~~~~~~~~~~~~~~~~
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.. automodule:: torch.nn.quantized.functional
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.. autofunction:: relu
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.. autofunction:: linear
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.. autofunction:: conv1d
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.. autofunction:: conv2d
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.. autofunction:: conv3d
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.. autofunction:: max_pool2d
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.. autofunction:: adaptive_avg_pool2d
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.. autofunction:: avg_pool2d
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.. autofunction:: interpolate
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.. autofunction:: hardswish
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.. autofunction:: upsample
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.. autofunction:: upsample_bilinear
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.. autofunction:: upsample_nearest
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.. automodule:: torch.nn.quantized
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ReLU
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~~~~~~~~~~~~~~~
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.. autoclass:: ReLU
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:members:
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ReLU6
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~~~~~~~~~~~~~~~
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.. autoclass:: ReLU6
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:members:
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ELU
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~~~~~~~~~~~~~~~
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.. autoclass:: ELU
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:members:
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Hardswish
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~~~~~~~~~~~~~~~
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.. autoclass:: Hardswish
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:members:
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Conv1d
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~~~~~~~~~~~~~~~
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.. autoclass:: Conv1d
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:members:
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Conv2d
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~~~~~~~~~~~~~~~
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.. autoclass:: Conv2d
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:members:
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Conv3d
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~~~~~~~~~~~~~~~
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.. autoclass:: Conv3d
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:members:
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FloatFunctional
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~~~~~~~~~~~~~~~
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.. autoclass:: FloatFunctional
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:members:
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QFunctional
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~~~~~~~~~~~~~~~
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.. autoclass:: QFunctional
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:members:
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Quantize
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~~~~~~~~~~~~~~~
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.. autoclass:: Quantize
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:members:
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DeQuantize
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~~~~~~~~~~~~~~~
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.. autoclass:: DeQuantize
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:members:
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Linear
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~~~~~~~~~~~~~~~
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.. autoclass:: Linear
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:members:
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BatchNorm2d
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~~~~~~~~~~~~~~~
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.. autoclass:: BatchNorm2d
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:members:
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BatchNorm3d
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~~~~~~~~~~~~~~~
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.. autoclass:: BatchNorm3d
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:members:
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LayerNorm
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~~~~~~~~~~~~~~~
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.. autoclass:: LayerNorm
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:members:
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GroupNorm
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~~~~~~~~~~~~~~~
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.. autoclass:: GroupNorm
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:members:
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InstanceNorm1d
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~~~~~~~~~~~~~~~
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.. autoclass:: InstanceNorm1d
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:members:
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InstanceNorm2d
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~~~~~~~~~~~~~~~
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.. autoclass:: InstanceNorm2d
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:members:
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InstanceNorm3d
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~~~~~~~~~~~~~~~
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.. autoclass:: InstanceNorm3d
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:members:
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