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125 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
zeshengzong
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1cc5f6b623 |
Optimize MaxPool1d param ceil_mode description (#148869)
Fixes #148123
Add output shape formula based on `ceil_mode` value, according to
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cyy
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d87aad6877 |
[5/N] Apply Ruff fixes and pyupgrade to Python 3.9 (#144205)
Fixes #ISSUE_NUMBER Pull Request resolved: https://github.com/pytorch/pytorch/pull/144205 Approved by: https://github.com/albanD |
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Lei Ding
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da320214e6 |
Format tensor (#127992)
Align tensor display Pull Request resolved: https://github.com/pytorch/pytorch/pull/127992 Approved by: https://github.com/janeyx99 |
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Xuehai Pan
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62ccf6d7cd |
[BE] enable UFMT for torch/nn/modules (#128594)
Part of #123062 - #123062 Pull Request resolved: https://github.com/pytorch/pytorch/pull/128594 Approved by: https://github.com/mikaylagawarecki |
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PyTorch MergeBot
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d4022b4658 |
Revert "[BE] enable UFMT for torch/nn/modules (#128594)"
This reverts commit
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Xuehai Pan
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95ac2d6482 |
[BE] enable UFMT for torch/nn/modules (#128594)
Part of #123062 - #123062 Pull Request resolved: https://github.com/pytorch/pytorch/pull/128594 Approved by: https://github.com/mikaylagawarecki ghstack dependencies: #128596 |
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Xuehai Pan
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a7c596870d |
[BE][Eazy] remove torch.torch.xxx usages (#127800)
NB: `torch` is exposed in `torch/__init__.py`. So there can be `torch.torch.torch.xxx`. Pull Request resolved: https://github.com/pytorch/pytorch/pull/127800 Approved by: https://github.com/peterbell10, https://github.com/kit1980, https://github.com/malfet |
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Dmovic
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6c07e2c930 |
fix redundant tensor (#127850)
As title. Pull Request resolved: https://github.com/pytorch/pytorch/pull/127850 Approved by: https://github.com/mikaylagawarecki |
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jmarin
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d9db9e62e3 |
Describe special case in avgpool (#120335)
Fixes #116420 AvgPool1d, AvgPool2d and AvgPool3d include now in their descriptions the special case when `ceil_mode` is True and the last window starts outside the tensor. Co-authored-by: mikaylagawarecki <mikaylagawarecki@gmail.com> Pull Request resolved: https://github.com/pytorch/pytorch/pull/120335 Approved by: https://github.com/mikaylagawarecki |
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zjgarvey
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6978c3ddf3 |
Removes an Incorrect Type Specification from AdaptiveMaxPool1d (#118162)
The return type for the forward pass of nn.AdaptiveMaxPool1d is specified to be Tensor, but if self.return_indices, then the result type should be tuple[Tensor,Tensor]. For users trying to trace/script this function with indices, the incorrect typing is problematic. Pull Request resolved: https://github.com/pytorch/pytorch/pull/118162 Approved by: https://github.com/albanD |
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feifan
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80c07df659 |
Update doc for the constraints of FractionalMaxPool2d (#116261)
Fixes [#115531 ](https://github.com/pytorch/pytorch/issues/115531) Update doc for the constraints of FractionalMaxPool2d. Pull Request resolved: https://github.com/pytorch/pytorch/pull/116261 Approved by: https://github.com/mikaylagawarecki |
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Wongboo
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68f74dd162 |
Add python and C++ support for LPPool3d (#114199)
Add python and C++ support for LPPool3d to Fixes #114114 Pull Request resolved: https://github.com/pytorch/pytorch/pull/114199 Approved by: https://github.com/mikaylagawarecki |
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zabboud
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53e7de4b65 |
Issue 112599 - fix pydocstyle errors (#113177)
Fixes #112599 Fixed errors relating to pydocstyle in the following files. The remaining errors are related to docstrings at the module level and at methods within each module, `forward()`, `reset_parameters`, `__init__` ..etc pydocstyle torch/nn/modules/pooling.py --count before: 49 after: 29 **remaining errors:** ``` torch/nn/modules/pooling.py:1 at module level: D100: Missing docstring in public module torch/nn/modules/pooling.py:90 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:163 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:240 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:315 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/pooling.py:321 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:402 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/pooling.py:408 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:472 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/pooling.py:478 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:541 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/pooling.py:550 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:620 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/pooling.py:630 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:706 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/pooling.py:716 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:720 in public method `__setstate__`: D105: Missing docstring in magic method torch/nn/modules/pooling.py:774 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/pooling.py:792 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:845 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/pooling.py:863 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:925 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:979 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:1026 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:1068 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:1111 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:1150 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:1189 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pooling.py:1228 in public method `forward`: D102: Missing docstring in public method ``` pydocstyle torch/nn/modules/upsampling.py --count before: 14 after: 7 **remaining:** ``` torch/nn/modules/upsampling.py:1 at module level: D100: Missing docstring in public module torch/nn/modules/upsampling.py:142 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/upsampling.py:156 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/upsampling.py:160 in public method `__setstate__`: D105: Missing docstring in magic method torch/nn/modules/upsampling.py:166 in public method `extra_repr`: D102: Missing docstring in public method torch/nn/modules/upsampling.py:216 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/upsampling.py:263 in public method `__init__`: D107: Missing docstring in __init__ ``` pydocstyle torch/nn/modules/rnn.py --count before: 47 after: 40 **remaining** ``` torch/nn/modules/rnn.py:1 at module level: D100: Missing docstring in public module torch/nn/modules/rnn.py:59 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:160 in public method `__setattr__`: D105: Missing docstring in magic method torch/nn/modules/rnn.py:225 in public method `reset_parameters`: D102: Missing docstring in public method torch/nn/modules/rnn.py:230 in public method `check_input`: D102: Missing docstring in public method torch/nn/modules/rnn.py:242 in public method `get_expected_hidden_size`: D102: Missing docstring in public method torch/nn/modules/rnn.py:256 in public method `check_hidden_size`: D102: Missing docstring in public method torch/nn/modules/rnn.py:272 in public method `check_forward_args`: D102: Missing docstring in public method torch/nn/modules/rnn.py:278 in public method `permute_hidden`: D102: Missing docstring in public method torch/nn/modules/rnn.py:284 in public method `extra_repr`: D102: Missing docstring in public method torch/nn/modules/rnn.py:305 in public method `__getstate__`: D105: Missing docstring in magic method torch/nn/modules/rnn.py:313 in public method `__setstate__`: D105: Missing docstring in magic method torch/nn/modules/rnn.py:355 in public method `all_weights`: D102: Missing docstring in public method torch/nn/modules/rnn.py:471 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:478 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:481 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:503 in public method `forward` (skipping F811): D102: Missing docstring in public method torch/nn/modules/rnn.py:762 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:768 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:771 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:774 in public method `get_expected_cell_size`: D102: Missing docstring in public method torch/nn/modules/rnn.py:786 in public method `check_forward_args`: D102: Missing docstring in public method torch/nn/modules/rnn.py:798 in public method `permute_hidden`: D102: Missing docstring in public method torch/nn/modules/rnn.py:809 in public method `forward` (skipping F811): D102: Missing docstring in public method torch/nn/modules/rnn.py:820 in public method `forward` (skipping F811): D102: Missing docstring in public method torch/nn/modules/rnn.py:1030 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:1036 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:1039 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:1046 in public method `forward` (skipping F811): D102: Missing docstring in public method torch/nn/modules/rnn.py:1054 in public method `forward` (skipping F811): D102: Missing docstring in public method torch/nn/modules/rnn.py:1123 in public class `RNNCellBase`: D101: Missing docstring in public class torch/nn/modules/rnn.py:1134 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:1152 in public method `extra_repr`: D102: Missing docstring in public method torch/nn/modules/rnn.py:1160 in public method `reset_parameters`: D102: Missing docstring in public method torch/nn/modules/rnn.py:1224 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:1230 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/rnn.py:1327 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:1332 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/rnn.py:1422 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/rnn.py:1427 in public method `forward`: D102: Missing docstring in public method ``` pydocstyle torch/nn/modules/pixelshuffle.py --count before: 13 after: 8 **remaining:** ``` torch/nn/modules/pixelshuffle.py:1 at module level: D100: Missing docstring in public module torch/nn/modules/pixelshuffle.py:52 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/pixelshuffle.py:56 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pixelshuffle.py:59 in public method `extra_repr`: D102: Missing docstring in public method torch/nn/modules/pixelshuffle.py:105 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/pixelshuffle.py:109 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/pixelshuffle.py:112 in public method `extra_repr`: D102: Missing docstring in public method ``` pydocstyle torch/nn/modules/sparse.py --count before: 14 after: 8 **remaining errors:** ``` torch/nn/modules/sparse.py:1 at module level: D100: Missing docstring in public module torch/nn/modules/sparse.py:124 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/sparse.py:153 in public method `reset_parameters`: D102: Missing docstring in public method torch/nn/modules/sparse.py:162 in public method `forward`: D102: Missing docstring in public method torch/nn/modules/sparse.py:167 in public method `extra_repr`: D102: Missing docstring in public method torch/nn/modules/sparse.py:320 in public method `__init__`: D107: Missing docstring in __init__ torch/nn/modules/sparse.py:350 in public method `reset_parameters`: D102: Missing docstring in public method torch/nn/modules/sparse.py:396 in public method `extra_repr`: D102: Missing docstring in public method ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/113177 Approved by: https://github.com/ezyang |
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Justin Chu
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4cc1745b13 |
[BE] f-stringify torch/ and scripts (#105538)
This PR is a follow up on the pyupgrade series to convert more strings to use f-strings using `flynt`. - https://docs.python.org/3/reference/lexical_analysis.html#f-strings - https://pypi.org/project/flynt/ Command used: ``` flynt torch/ -ll 120 flynt scripts/ -ll 120 flynt tools/ -ll 120 ``` and excluded `collect_env.py` Pull Request resolved: https://github.com/pytorch/pytorch/pull/105538 Approved by: https://github.com/ezyang, https://github.com/malfet |
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Justin Chu
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79c5e33349 |
[BE] Enable ruff's UP rules and autoformat nn/ mps/ and torch/ (#105436)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/105436 Approved by: https://github.com/malfet, https://github.com/albanD |
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Danni Li
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980fb94f9c |
[Doc] Specify output parameters for FractionalMaxPool2d and FractionalMaxPool3d (#104941)
Summary: Specify one of the output parameters must be set for FractionalMaxPool2d and FractionalMaxPool3d. Fix: #104861 Test Plan: Please see GitHub Actions Differential Revision: D47357240 Pull Request resolved: https://github.com/pytorch/pytorch/pull/104941 Approved by: https://github.com/mikaylagawarecki |
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Driss Guessous
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7f7f91e36f |
add reproducibility notes to nn.UnpoolND operations (#94629)
In response to some comments here: #80827 Pull Request resolved: https://github.com/pytorch/pytorch/pull/94629 Approved by: https://github.com/albanD |
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Xuehai Pan
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5b1cedacde |
[BE] [2/3] Rewrite super() calls in functorch and torch (#94588)
Rewrite Python built-in class `super()` calls. Only non-semantic changes should be applied. - #94587 - #94588 - #94592 Also, methods with only a `super()` call are removed: ```diff class MyModule(nn.Module): - def __init__(self): - super().__init__() - def forward(self, ...): ... ``` Some cases that change the semantics should be kept unchanged. E.g.: |
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joncrall
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ad782ff7df |
Enable xdoctest runner in CI for real this time (#83816)
Builds on #83317 and enables running the doctests. Just need to figure out what is causing the failures. Pull Request resolved: https://github.com/pytorch/pytorch/pull/83816 Approved by: https://github.com/ezyang, https://github.com/malfet |
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David
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67358ee124 |
MaxPool: correct pooling description (#86559)
In the documentation of `nn.MaxPool2d` and `nn.MaxPool3d`, the argument description of `padding` incorrectly states that zero padding is applied. The remainder of the documentation correctly states that negative infinity padding is applied. The documentation of `padding` in `nn.MaxPool1d`, `nn.functional.max_pool1d/2d/3d` is correct. Pull Request resolved: https://github.com/pytorch/pytorch/pull/86559 Approved by: https://github.com/albanD |
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joncrall
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b136f3f310 |
More doctest refinements. (#83317)
Follow up to #82797 Now that the doctests themselves are in a better state, we should be able to enable xdoctest on the CI so they stay that way. @ezyang @vadimkantorov Pull Request resolved: https://github.com/pytorch/pytorch/pull/83317 Approved by: https://github.com/ezyang |
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joncrall
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4618371da5 |
Integrate xdoctest - Rebased (#82797)
This is a new version of #15648 based on the latest master branch. Unlike the previous PR where I fixed a lot of the doctests in addition to integrating xdoctest, I'm going to reduce the scope here. I'm simply going to integrate xdoctest, and then I'm going to mark all of the failing tests as "SKIP". This will let xdoctest run on the dashboards, provide some value, and still let the dashboards pass. I'll leave fixing the doctests themselves to another PR. In my initial commit, I do the bare minimum to get something running with failing dashboards. The few tests that I marked as skip are causing segfaults. Running xdoctest results in 293 failed, 201 passed tests. The next commits will be to disable those tests. (unfortunately I don't have a tool that will insert the `#xdoctest: +SKIP` directive over every failing test, so I'm going to do this mostly manually.) Fixes https://github.com/pytorch/pytorch/issues/71105 @ezyang Pull Request resolved: https://github.com/pytorch/pytorch/pull/82797 Approved by: https://github.com/ezyang |
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PyTorch MergeBot
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9db3c517de |
Add __all__ for torch.nn.modules, torch.distributed.elastic, torch.nn.utils submodules (#80240)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80240 Approved by: https://github.com/rohan-varma |
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Kushashwa Ravi Shrimali
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452c26bbeb |
Fix functional.max_poolNd warning spam in the CI
Fixes https://github.com/pytorch/pytorch/issues/71257. Warnings have been removed, please see [this](https://github.com/pytorch/pytorch/pull/71258#issuecomment-1058503649) comment. cc: @Lezcano @jbschlosser @zou3519 Pull Request resolved: https://github.com/pytorch/pytorch/pull/71258 Approved by: https://github.com/Lezcano, https://github.com/jbschlosser |
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Joel Schlosser
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f670179c0a |
Fix doc regressions for various modules and functional forms (#73014)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73014
Fixes #72501
Fixes #72502
Fixes #72503
Fixes #72504
Fixes #72505
Fixes #72506
Fixes #72507
Fixes #72509
Fixes #72510
Test Plan: Imported from OSS
Reviewed By: albanD
Differential Revision: D34305640
Pulled By: jbschlosser
fbshipit-source-id: 62f341633fdb0316eaa346cf7247865290eb830a
(cherry picked from commit
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George Qi
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7c690ef1c2 |
FractionalMaxPool3d with no_batch_dim support (#69732)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/69732 Test Plan: Imported from OSS Reviewed By: jbschlosser Differential Revision: D33280090 Pulled By: george-qi fbshipit-source-id: aaf90a372b6d80da0554bad28d56436676f9cb89 |
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Kyle Matoba
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3bf4080fd9 |
Change misleading MaxUnpool2d example to better demonstrate output_size usage (#68936)
Summary: At https://github.com/pytorch/pytorch/issues/68873, jbschlosser states that maxunpool2d with the `output_size` argument only works for indices of the same size. This makes sense, but unfortunately it's not what's shown in the example! I've removed the wrong example and replaced it with one where specifying `output_size` is actually necessary -- the unpool call fails without it. Pull Request resolved: https://github.com/pytorch/pytorch/pull/68936 Reviewed By: H-Huang Differential Revision: D32759207 Pulled By: jbschlosser fbshipit-source-id: 658e1724150a95454a05a771ae7c6e2e736740a7 |
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Gary Miguel
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543b7fb942 |
[JIT] Fix type annotations of pooling modules (#65847)
Summary:
All of the pooling modules except MaxUnpool and LPPool return either a
Tensor or [Tensor, Tensor]. The current type annotations are inaccurate,
and prevent scripting the module if return_indices is set as True in the
module.
There's not a great way to make this agree with mypy because the
overload is dependent on the value of return_indices, an attribute.
I tried changing the annotations from `Tensor` to
`Union[Tensor, Tuple[Tensor, Tensor]]`, but that breaks a bunch of uses
that have return_indices=False.
For example, this breaks:
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Thomas J. Fan
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9914fb6615 |
ENH Adds no_batch_dim tests/docs for LPPool1d and Identity (#62190)
Summary: Fixes https://github.com/pytorch/pytorch/issues/60585 Pull Request resolved: https://github.com/pytorch/pytorch/pull/62190 Reviewed By: ejguan Differential Revision: D29942385 Pulled By: jbschlosser fbshipit-source-id: 00df6f6f01ad039631bb8679f8de94863aac7650 |
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Thomas J. Fan
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c5f3ab6982 |
ENH Adds no_batch_dim to FractionalMaxPool2d (#62490)
Summary: Towards https://github.com/pytorch/pytorch/issues/60585 Pull Request resolved: https://github.com/pytorch/pytorch/pull/62490 Reviewed By: bdhirsh Differential Revision: D30287143 Pulled By: jbschlosser fbshipit-source-id: 1b9dd932157f571adf3aa2c98c3c6b56ece8fa6e |
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Kyle Matoba
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de94034328 |
Fixes #62636 (#62670)
Summary: Fixes https://github.com/pytorch/pytorch/issues/62636. Pull Request resolved: https://github.com/pytorch/pytorch/pull/62670 Reviewed By: ezyang Differential Revision: D30102179 Pulled By: soulitzer fbshipit-source-id: 38480463ef354f2c12ed83e6678aed26b0b96efe |
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Thomas J. Fan
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71a6ef17a5 |
ENH Adds no_batch_dim tests/docs for Maxpool1d & MaxUnpool1d (#62206)
Summary: Towards https://github.com/pytorch/pytorch/issues/60585 Pull Request resolved: https://github.com/pytorch/pytorch/pull/62206 Reviewed By: ejguan Differential Revision: D29942341 Pulled By: jbschlosser fbshipit-source-id: a3fad774cee30478f7d6cdd49d2eec31be3fc518 |
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Thomas J. Fan
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89ca638c18 |
ENH Adds no batch dim support for AdativeMaxPool*D (#61847)
Summary: Towards https://github.com/pytorch/pytorch/issues/60585 Pull Request resolved: https://github.com/pytorch/pytorch/pull/61847 Reviewed By: suo Differential Revision: D29883887 Pulled By: jbschlosser fbshipit-source-id: de3fcf1cc3878b138ab766d2a50cc59c52ec5a60 |
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Thomas J. Fan
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1ec6205bd0 |
ENH Adds no_batch_dim support for maxpool and unpool for 2d and 3d (#61984)
Summary: Towards https://github.com/pytorch/pytorch/issues/60585 (Interesting how the maxpool tests are currently in `test/test_nn.py`) Pull Request resolved: https://github.com/pytorch/pytorch/pull/61984 Reviewed By: suo Differential Revision: D29883846 Pulled By: jbschlosser fbshipit-source-id: 1e0637c96f8fa442b4784a9865310c164cbf61c8 |
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Thomas J. Fan
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0309c5780d |
ENH Adds no batch dim support for AvgPool1d (#61860)
Summary: Towards https://github.com/pytorch/pytorch/issues/60585 Pull Request resolved: https://github.com/pytorch/pytorch/pull/61860 Reviewed By: albanD Differential Revision: D29826382 Pulled By: jbschlosser fbshipit-source-id: 47e12073d866f0604310fc1ff270cde9907e516d |
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Zeina Migeed
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243c7079a1 |
add 3d input and output shapes to maxpool documentation (#61310)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/61310 Test Plan: Imported from OSS Reviewed By: jbschlosser Differential Revision: D29737516 Pulled By: migeed-z fbshipit-source-id: eb6964f6808b8ae05d4d3852a5162dc66930cd64 |
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Thomas J. Fan
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24a6eb3fda |
ENH Adds tests and docs for 2d & 3d modules that already support no batch (#61262)
Summary: Toward https://github.com/pytorch/pytorch/issues/60585 Pull Request resolved: https://github.com/pytorch/pytorch/pull/61262 Reviewed By: mrshenli Differential Revision: D29660554 Pulled By: jbschlosser fbshipit-source-id: d5e3dc7096fcf8621bce4a1063d521b84092e0ca |
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Thomas J. Fan
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25a705610f |
ENH Adds support for no-batch dim in AdaptiveAvgPool1d (#61264)
Summary: Towards https://github.com/pytorch/pytorch/issues/60585 Pull Request resolved: https://github.com/pytorch/pytorch/pull/61264 Reviewed By: iramazanli Differential Revision: D29615292 Pulled By: jbschlosser fbshipit-source-id: 826d1c87d67261a7211270e90e3a1022bbbe37bd |
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Victor Quach
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c769300301 |
Fix MaxPool default pad documentation (#59404)
Summary: Fixes https://github.com/pytorch/pytorch/issues/33384 Pull Request resolved: https://github.com/pytorch/pytorch/pull/59404 Reviewed By: albanD Differential Revision: D28879049 Pulled By: Varal7 fbshipit-source-id: 03a86cd347d53ac2d06028b3f213c5b5d5ab7e91 |
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Loi Ly
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74c055b240 |
Fix mypy type hint for AdaptiveAvgPool2,3d, AdaptiveMaxPool2,3d (#49963)
Summary: Fixes https://github.com/pytorch/pytorch/issues/49918 Pull Request resolved: https://github.com/pytorch/pytorch/pull/49963 Reviewed By: mrshenli, heitorschueroff Differential Revision: D25760110 Pulled By: ezyang fbshipit-source-id: aeb655b784689544000ea3b948f7d6d025aee441 |
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Xianguang Zhou
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736e8965e5 |
Change the type hints of "pooling.py". (#48412)
Summary: Change the type hints of "AvgPool2d" and "AvgPool3d". Pull Request resolved: https://github.com/pytorch/pytorch/pull/48412 Reviewed By: ejguan Differential Revision: D25221087 Pulled By: ezyang fbshipit-source-id: 5fba2a8051a7b3d5508e97763bacfd2140a777bf |
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Heitor Schueroff
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2643800881 |
Fix max_pool2d with ceil_mode bug (#46558)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/46558 This PR fixes a bug with how pooling output shape was computed. ## BC Breaking Notes Previously, a bug in the pooling code allowed a sliding window to be entirely off bounds. Now, sliding windows must start inside the input or left padding (not right padding, see https://github.com/pytorch/pytorch/issues/46929) and may only go off-bounds if ceil_mode=True. fixes #45357 TODO - [x] Ensure existing tests are checking for the correct output size Test Plan: Imported from OSS Reviewed By: albanD Differential Revision: D24633372 Pulled By: heitorschueroff fbshipit-source-id: 55925243a53df5d6131a1983076f11cab7516d6b |
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Xiang Gao
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20ac736200 |
Remove py2 compatible future imports (#44735)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/44735 Reviewed By: mruberry Differential Revision: D23731306 Pulled By: ezyang fbshipit-source-id: 0ba009a99e475ddbe22981be8ac636f8a1c8b02f |
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Heitor Schueroff de Souza
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13a48ac1f3 |
MaxPool1d without indices optimization (#43745)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/43745 This is part of a larger effort to refactor and optimize the pooling code. Previously I started working on MaxPool2d here https://github.com/pytorch/pytorch/pull/43267 but since it uses MaxPool1d as a subroutine, it made more sense to work on 1D first and get it tested and optimized and then move up to 2D and then 3D. Below are some benchmarking results, the python script I used is under the results. ## Benchmarking ``` Name (time in us) Min Max Mean StdDev Median IQR Outliers OPS (Kops/s) Rounds Iterations --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- test_googlenet[(3, 2, 0, 1, 0)-new] 79.7659 (1.03) 1,059.6327 (5.32) 90.6280 (1.01) 19.1196 (1.41) 84.2176 (1.01) 2.4289 (1.0) 1079;2818 11.0341 (0.99) 9055 1 test_googlenet[(3, 2, 0, 1, 0)-old] 505.1531 (6.55) 830.8962 (4.17) 563.4763 (6.29) 65.3974 (4.81) 538.3361 (6.43) 80.5371 (33.16) 242;99 1.7747 (0.16) 1742 1 test_googlenet[(3, 2, 0, 1, 1)-new] 80.2949 (1.04) 233.0020 (1.17) 97.6498 (1.09) 19.1228 (1.41) 89.2282 (1.07) 18.5743 (7.65) 1858;741 10.2407 (0.92) 9587 1 test_googlenet[(3, 2, 0, 1, 1)-old] 513.5350 (6.66) 977.4677 (4.91) 594.4559 (6.63) 69.9372 (5.15) 577.9080 (6.90) 79.8218 (32.86) 503;84 1.6822 (0.15) 1675 1 test_googlenet[(3, 2, 1, 1, 0)-new] 77.1061 (1.0) 199.1168 (1.0) 89.6529 (1.0) 13.5864 (1.0) 83.7557 (1.0) 7.5139 (3.09) 1419;1556 11.1541 (1.0) 7434 1 test_googlenet[(3, 2, 1, 1, 0)-old] 543.6055 (7.05) 964.5708 (4.84) 636.9867 (7.11) 84.0732 (6.19) 616.7777 (7.36) 100.4562 (41.36) 434;65 1.5699 (0.14) 1552 1 --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- test_inception[(3, 2, 0, 1, 0)-new] 84.5827 (1.00) 184.2827 (1.0) 90.5438 (1.01) 9.6324 (1.0) 89.3027 (1.05) 4.5672 (1.03) 637;759 11.0444 (0.99) 6274 1 test_inception[(3, 2, 0, 1, 0)-old] 641.2268 (7.59) 1,704.8977 (9.25) 686.9383 (7.65) 57.2499 (5.94) 682.5905 (8.01) 58.3753 (13.17) 86;21 1.4557 (0.13) 802 1 test_inception[(3, 2, 0, 1, 1)-new] 84.5008 (1.0) 1,093.6335 (5.93) 89.8233 (1.0) 14.0443 (1.46) 85.2682 (1.0) 4.4331 (1.0) 802;1106 11.1330 (1.0) 9190 1 test_inception[(3, 2, 0, 1, 1)-old] 643.7078 (7.62) 851.4188 (4.62) 687.4905 (7.65) 41.1116 (4.27) 685.1386 (8.04) 60.2733 (13.60) 286;14 1.4546 (0.13) 1300 1 test_inception[(3, 2, 1, 1, 0)-new] 106.0739 (1.26) 258.5649 (1.40) 115.3597 (1.28) 17.5436 (1.82) 106.9643 (1.25) 5.5470 (1.25) 894;1402 8.6685 (0.78) 7635 1 test_inception[(3, 2, 1, 1, 0)-old] 651.0504 (7.70) 955.2278 (5.18) 698.0295 (7.77) 45.5097 (4.72) 692.8109 (8.13) 64.6794 (14.59) 145;15 1.4326 (0.13) 909 1 -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- test_large_batch_size[new] 2.9608 (1.0) 5.1127 (1.0) 3.3096 (1.0) 0.1936 (1.0) 3.3131 (1.0) 0.2093 (1.0) 71;6 302.1515 (1.0) 297 1 test_large_batch_size[old] 130.6583 (44.13) 152.9521 (29.92) 137.1385 (41.44) 7.4352 (38.40) 135.1784 (40.80) 5.1358 (24.53) 1;1 7.2919 (0.02) 7 1 --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- test_large_channel_size[new] 2.9696 (1.0) 5.5595 (1.0) 3.5997 (1.0) 0.5836 (1.0) 3.3497 (1.0) 0.3445 (1.0) 58;54 277.8014 (1.0) 277 1 test_large_channel_size[old] 19.6838 (6.63) 22.6637 (4.08) 21.1775 (5.88) 0.8610 (1.48) 21.3739 (6.38) 1.4930 (4.33) 13;0 47.2199 (0.17) 36 1 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- test_large_width[new] 1.7714 (1.0) 2.4104 (1.0) 1.8988 (1.0) 0.0767 (1.0) 1.8911 (1.0) 0.0885 (1.0) 86;13 526.6454 (1.0) 373 1 test_large_width[old] 19.5708 (11.05) 22.8755 (9.49) 20.7987 (10.95) 0.7009 (9.14) 20.6623 (10.93) 0.8584 (9.70) 14;1 48.0799 (0.09) 46 1 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ test_multithreaded[new] 15.0560 (1.0) 24.2891 (1.0) 16.1627 (1.0) 1.5657 (1.0) 15.7182 (1.0) 0.7598 (1.0) 4;6 61.8709 (1.0) 65 1 test_multithreaded[old] 115.7614 (7.69) 120.9670 (4.98) 118.3004 (7.32) 1.6259 (1.04) 118.4164 (7.53) 1.9613 (2.58) 2;0 8.4531 (0.14) 8 1 ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Legend: Outliers: 1 Standard Deviation from Mean; 1.5 IQR (InterQuartile Range) from 1st Quartile and 3rd Quartile. OPS: Operations Per Second, computed as 1 / Mean ``` ### Benchmarking script To run the benchmark make sure you have pytest-benchmark installed with `pip install pytest-benchmark` and use the following command: `pytest benchmark.py --benchmark-sort='name'` ``` import torch import pytest def _test_speedup(benchmark, batches=1, channels=32, width=32, kernel_size=2, stride=None, padding=0, dilation=1, ceil_mode=False, return_indices=False): torch.set_num_threads(1) x = torch.randn((batches, channels, width)) model = torch.nn.MaxPool1d(kernel_size, stride, padding, dilation, return_indices, ceil_mode) benchmark(model, x) pytest.mark.benchmark(group="inception") pytest.mark.parametrize("return_indices", [True, False], ids=["old", "new"]) pytest.mark.parametrize("params", [(3, 2), (3, 2, 0, 1, True), (3, 2, 1)], ids=["(3, 2, 0, 1, 0)", "(3, 2, 0, 1, 1)", "(3, 2, 1, 1, 0)"]) def test_inception(benchmark, params, return_indices): _test_speedup(benchmark, 10, 64, 147, *params, return_indices=return_indices) pytest.mark.benchmark(group="googlenet") pytest.mark.parametrize("return_indices", [True, False], ids=["old", "new"]) pytest.mark.parametrize("params", [(3, 2), (3, 2, 0, 1, True), (3, 2, 1)], ids=["(3, 2, 0, 1, 0)", "(3, 2, 0, 1, 1)", "(3, 2, 1, 1, 0)"]) def test_googlenet(benchmark, params, return_indices): _test_speedup(benchmark, 10, 64, 112, *params, return_indices=return_indices) pytest.mark.benchmark(group="large batch size") pytest.mark.parametrize("return_indices", [True, False], ids=["old", "new"]) def test_large_batch_size(benchmark, return_indices): _test_speedup(benchmark, 100000, 1, 32, return_indices=return_indices) pytest.mark.benchmark(group="large channel size") pytest.mark.parametrize("return_indices", [True, False], ids=["old", "new"]) def test_large_channel_size(benchmark, return_indices): _test_speedup(benchmark, 1, 100000, 32, return_indices=return_indices) pytest.mark.benchmark(group="large width") pytest.mark.parametrize("return_indices", [True, False], ids=["old", "new"]) def test_large_width(benchmark, return_indices): _test_speedup(benchmark, 1, 32, 100000, return_indices=return_indices) pytest.mark.benchmark(group="multithreading") pytest.mark.parametrize("return_indices", [True, False], ids=["old", "new"]) def test_multithreaded(benchmark, return_indices): x = torch.randn((40, 10000, 32)) model = torch.nn.MaxPool1d(2, return_indices=return_indices) benchmark(model, x) ``` ## Discussion The new algorithm is on average 7x faster than the old one. But because the old algorithm had many issues with how it parallelized the code and made use of the cache, one can come up with input parameters (like large batch size) that will make the new algorithm much faster than the original one. Test Plan: Imported from OSS Reviewed By: glaringlee Differential Revision: D23425348 Pulled By: heitorschueroff fbshipit-source-id: 3fa3f9b8e71200da48424a95510124a83f50d7b2 |
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X Wang
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b0424a895c |
Raise RuntimeError for zero stride pooling (#41819)
Summary: Close https://github.com/pytorch/pytorch/issues/41767 Pull Request resolved: https://github.com/pytorch/pytorch/pull/41819 Reviewed By: mrshenli Differential Revision: D22780634 Pulled By: ngimel fbshipit-source-id: 376ce5229ad5bd60804d839340d2c6505cf3288d |
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Edward Leardi
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6b50874cb7 |
Fix HTTP links in documentation to HTTPS (#40878)
Summary: I ran `make linkcheck` using `sphinx.builders.linkcheck` on the documentation and noticed a few links weren't using HTTPS so I quickly updated them all. Pull Request resolved: https://github.com/pytorch/pytorch/pull/40878 Differential Revision: D22404647 Pulled By: ngimel fbshipit-source-id: 9c9756db59197304023fddc28f252314f6cf4af3 |
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Alexander
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e439cf738a |
Fix examples Adaptive avg pooling typo (#40217)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/40217 Reviewed By: ezyang Differential Revision: D22193711 Pulled By: zou3519 fbshipit-source-id: f96f71e025aa1c81b232e78b1d5b3a3bbd8f331f |
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Edward Yang
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eace053398 |
Move all torch.nn.modules type annotations inline (#38211)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/38211 Just because the annotations are inline doesn't mean the files type check; most of the newly annotated files have type errors and I added exclusions for them in mypy.ini. The payoff of moving all of these modules inline is I can delete the relevant code generation logic for the pyi files (which was added ignore annotations that weren't actually relevant anymore.) For the most part the translation was completely mechanical, but there were two hairy issues. First, I needed to work around a Python 3.6 and earlier bug where Generic has a nontrivial metaclass. This fix is in torch/jit/__init__.py. Second, module.py, we need to apply the same fix for avoiding contravariance checks that the pyi file used to have; this is done by declaring forward as a variable (rather than a function), which appears to be sufficient enough to get mypy to not contravariantly check input arguments. Because we aren't actually typechecking these modules in most cases, it is inevitable that some of these type annotations are wrong. I slavishly copied the old annotations from the pyi files unless there was an obvious correction I could make. These annotations will probably need fixing up later. Signed-off-by: Edward Z. Yang <ezyang@fb.com> Test Plan: Imported from OSS Differential Revision: D21497397 Pulled By: ezyang fbshipit-source-id: 2b08bacc152c48f074e7edc4ee5dce1b77d83702 |
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Alban Desmaison
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3799d1d74a |
Fix many doc issues (#37099)
Summary: Fix https://github.com/pytorch/pytorch/issues/35643 https://github.com/pytorch/pytorch/issues/37063 https://github.com/pytorch/pytorch/issues/36307 https://github.com/pytorch/pytorch/issues/35861 https://github.com/pytorch/pytorch/issues/35299 https://github.com/pytorch/pytorch/issues/23108 https://github.com/pytorch/pytorch/issues/4661 Just a bunch of small updates on the doc. Pull Request resolved: https://github.com/pytorch/pytorch/pull/37099 Differential Revision: D21185713 Pulled By: albanD fbshipit-source-id: 4ac06d6709dc0da6109a6ad3daae75667ee5863e |
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Ralf Gommers
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78d5707041 |
Fix type annotations and make MyPy run on torch/ (#36584)
Summary: This PR fixes a couple of syntax errors in `torch/` that prevent MyPy from running, fixes simple type annotation errors (e.g. missing `from typing import List, Tuple, Optional`), and adds granular ignores for errors in particular modules as well as for missing typing in third party packages. As a result, running `mypy` in the root dir of the repo now runs on: - `torch/` - `aten/src/ATen/function_wrapper.py` (the only file already covered in CI) In CI this runs on GitHub Actions, job Lint, sub-job "quick-checks", task "MyPy typecheck". It should give (right now): `Success: no issues found in 329 source files`. Here are the details of the original 855 errors when running `mypy torch` on current master (after fixing the couple of syntax errors that prevent `mypy` from running through): <details> ``` torch/utils/tensorboard/_proto_graph.py:1: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.node_def_pb2' torch/utils/tensorboard/_proto_graph.py:2: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.attr_value_pb2' torch/utils/tensorboard/_proto_graph.py:3: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.tensor_shape_pb2' torch/utils/backcompat/__init__.py:1: error: Cannot find implementation or library stub for module named 'torch._C' torch/for_onnx/__init__.py:1: error: Cannot find implementation or library stub for module named 'torch.for_onnx.onnx' torch/cuda/nvtx.py:2: error: Cannot find implementation or library stub for module named 'torch._C' torch/utils/show_pickle.py:59: error: Name 'pickle._Unpickler' is not defined torch/utils/show_pickle.py:113: error: "Type[PrettyPrinter]" has no attribute "_dispatch" torch/utils/tensorboard/_onnx_graph.py:1: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.graph_pb2' torch/utils/tensorboard/_onnx_graph.py:2: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.node_def_pb2' torch/utils/tensorboard/_onnx_graph.py:3: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.versions_pb2' torch/utils/tensorboard/_onnx_graph.py:4: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.attr_value_pb2' torch/utils/tensorboard/_onnx_graph.py:5: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.tensor_shape_pb2' torch/utils/tensorboard/_onnx_graph.py:9: error: Cannot find implementation or library stub for module named 'onnx' torch/contrib/_tensorboard_vis.py:10: error: Cannot find implementation or library stub for module named 'tensorflow.core.util' torch/contrib/_tensorboard_vis.py:11: error: Cannot find implementation or library stub for module named 'tensorflow.core.framework' torch/contrib/_tensorboard_vis.py:12: error: Cannot find implementation or library stub for module named 'tensorflow.python.summary.writer.writer' torch/utils/hipify/hipify_python.py:43: error: Need type annotation for 'CAFFE2_TEMPLATE_MAP' (hint: "CAFFE2_TEMPLATE_MAP: Dict[<type>, <type>] = ...") torch/utils/hipify/hipify_python.py:636: error: "object" has no attribute "items" torch/nn/_reduction.py:27: error: Name 'Optional' is not defined torch/nn/_reduction.py:27: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/nn/_reduction.py:47: error: Name 'Optional' is not defined torch/nn/_reduction.py:47: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/utils/tensorboard/_utils.py:17: error: Skipping analyzing 'matplotlib.pyplot': found module but no type hints or library stubs torch/utils/tensorboard/_utils.py:17: error: Skipping analyzing 'matplotlib': found module but no type hints or library stubs torch/utils/tensorboard/_utils.py:18: error: Skipping analyzing 'matplotlib.backends.backend_agg': found module but no type hints or library stubs torch/utils/tensorboard/_utils.py:18: error: Skipping analyzing 'matplotlib.backends': found module but no type hints or library stubs torch/nn/modules/utils.py:27: error: Name 'List' is not defined torch/nn/modules/utils.py:27: note: Did you forget to import it from "typing"? (Suggestion: "from typing import List") caffe2/proto/caffe2_pb2.py:17: error: Unexpected keyword argument "serialized_options" for "FileDescriptor"; did you mean "serialized_pb"? caffe2/proto/caffe2_pb2.py:25: error: Unexpected keyword argument "serialized_options" for "EnumDescriptor" caffe2/proto/caffe2_pb2.py:31: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:35: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:39: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:43: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:47: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:51: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:55: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:59: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:63: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:67: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:71: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:75: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:102: error: Unexpected keyword argument "serialized_options" for "EnumDescriptor" caffe2/proto/caffe2_pb2.py:108: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:112: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:124: error: Unexpected keyword argument "serialized_options" for "EnumDescriptor" caffe2/proto/caffe2_pb2.py:130: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:134: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:138: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:142: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:146: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:150: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:154: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:158: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:162: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:166: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:170: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:174: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:178: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:182: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:194: error: Unexpected keyword argument "serialized_options" for "EnumDescriptor" caffe2/proto/caffe2_pb2.py:200: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:204: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:208: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:212: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:224: error: Unexpected keyword argument "serialized_options" for "EnumDescriptor" caffe2/proto/caffe2_pb2.py:230: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:234: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:238: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:242: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:246: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:250: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:254: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:267: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:274: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:281: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:288: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:295: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:302: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:327: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:334: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:341: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:364: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:371: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:378: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:385: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:392: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:399: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:406: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:413: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:420: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:427: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:434: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:441: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:448: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:455: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:462: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:488: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:495: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:502: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:509: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:516: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:523: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:530: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:537: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:544: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:551: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:558: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:565: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:572: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:596: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:603: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:627: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:634: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:641: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:648: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:655: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:662: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:686: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:693: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:717: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:724: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:731: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:738: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:763: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:770: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:777: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:784: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:808: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:815: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:822: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:829: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:836: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:843: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:850: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:857: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:864: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:871: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:878: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:885: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:892: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:916: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:923: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:930: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:937: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:944: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:951: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:958: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:982: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:989: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:996: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1003: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1010: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1017: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1024: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1031: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1038: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1045: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1052: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1059: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1066: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1090: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1097: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1104: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1128: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1135: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1142: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1166: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1173: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1180: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1187: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1194: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1218: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1225: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1232: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1239: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1246: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1253: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1260: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1267: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1274: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1281: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1305: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1312: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1319: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1326: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1333: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1340: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1347: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1354: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1361: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1368: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1375: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1382: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1389: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1396: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1420: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1427: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1434: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1441: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1465: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1472: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1479: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1486: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1493: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1500: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1507: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1514: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1538: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1545: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1552: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1559: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1566: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1667: error: "GeneratedProtocolMessageType" has no attribute "Segment" torch/multiprocessing/queue.py:4: error: No library stub file for standard library module 'multiprocessing.reduction' caffe2/proto/torch_pb2.py:18: error: Unexpected keyword argument "serialized_options" for "FileDescriptor"; did you mean "serialized_pb"? caffe2/proto/torch_pb2.py:27: error: Unexpected keyword argument "serialized_options" for "EnumDescriptor" caffe2/proto/torch_pb2.py:33: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/torch_pb2.py:50: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:57: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:81: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:88: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:95: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:102: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:109: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:116: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:123: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:130: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:137: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:144: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:151: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:175: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:182: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:189: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:196: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:220: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:227: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:234: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:241: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:265: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:272: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:279: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:286: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:293: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:300: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:307: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:314: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:321: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:328: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:335: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:342: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:366: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:373: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:397: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:404: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:411: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:418: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:425: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:432: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:17: error: Unexpected keyword argument "serialized_options" for "FileDescriptor"; did you mean "serialized_pb"? caffe2/proto/metanet_pb2.py:29: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/metanet_pb2.py:36: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:43: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:50: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:57: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:64: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:88: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/metanet_pb2.py:95: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:102: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:126: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/metanet_pb2.py:133: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:140: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:164: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/metanet_pb2.py:171: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:178: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:202: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/metanet_pb2.py:209: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:216: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:240: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/metanet_pb2.py:247: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:254: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:261: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:268: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:275: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:282: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:289: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:296: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/__init__.py:13: error: Skipping analyzing 'caffe2.caffe2.fb.session.proto': found module but no type hints or library stubs torch/multiprocessing/pool.py:3: error: No library stub file for standard library module 'multiprocessing.util' torch/multiprocessing/pool.py:3: note: (Stub files are from https://github.com/python/typeshed) caffe2/python/scope.py:10: error: Skipping analyzing 'past.builtins': found module but no type hints or library stubs caffe2/python/__init__.py:7: error: Module has no attribute "CPU" caffe2/python/__init__.py:8: error: Module has no attribute "CUDA" caffe2/python/__init__.py:9: error: Module has no attribute "MKLDNN" caffe2/python/__init__.py:10: error: Module has no attribute "OPENGL" caffe2/python/__init__.py:11: error: Module has no attribute "OPENCL" caffe2/python/__init__.py:12: error: Module has no attribute "IDEEP" caffe2/python/__init__.py:13: error: Module has no attribute "HIP" caffe2/python/__init__.py:14: error: Module has no attribute "COMPILE_TIME_MAX_DEVICE_TYPES"; maybe "PROTO_COMPILE_TIME_MAX_DEVICE_TYPES"? caffe2/python/__init__.py:15: error: Module has no attribute "ONLY_FOR_TEST"; maybe "PROTO_ONLY_FOR_TEST"? caffe2/python/__init__.py:34: error: Item "_Loader" of "Optional[_Loader]" has no attribute "exec_module" caffe2/python/__init__.py:34: error: Item "None" of "Optional[_Loader]" has no attribute "exec_module" caffe2/python/__init__.py:35: error: Module has no attribute "cuda" caffe2/python/__init__.py:37: error: Module has no attribute "cuda" caffe2/python/__init__.py:49: error: Module has no attribute "add_dll_directory" torch/random.py:4: error: Cannot find implementation or library stub for module named 'torch._C' torch/_classes.py:2: error: Cannot find implementation or library stub for module named 'torch._C' torch/onnx/__init__.py:1: error: Cannot find implementation or library stub for module named 'torch._C' torch/hub.py:21: error: Skipping analyzing 'tqdm.auto': found module but no type hints or library stubs torch/hub.py:24: error: Skipping analyzing 'tqdm': found module but no type hints or library stubs torch/hub.py:27: error: Name 'tqdm' already defined (possibly by an import) torch/_tensor_str.py:164: error: Not all arguments converted during string formatting torch/_ops.py:1: error: Cannot find implementation or library stub for module named 'torch._C' torch/_linalg_utils.py:26: error: Name 'Optional' is not defined torch/_linalg_utils.py:26: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_linalg_utils.py:26: error: Name 'Tensor' is not defined torch/_linalg_utils.py:63: error: Name 'Tensor' is not defined torch/_linalg_utils.py:63: error: Name 'Optional' is not defined torch/_linalg_utils.py:63: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_linalg_utils.py:70: error: Name 'Optional' is not defined torch/_linalg_utils.py:70: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_linalg_utils.py:70: error: Name 'Tensor' is not defined torch/_linalg_utils.py:88: error: Name 'Tensor' is not defined torch/_linalg_utils.py:88: error: Name 'Optional' is not defined torch/_linalg_utils.py:88: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_linalg_utils.py:88: error: Name 'Tuple' is not defined torch/_linalg_utils.py:88: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/_jit_internal.py:17: error: Need type annotation for 'boolean_dispatched' torch/_jit_internal.py:474: error: Need type annotation for '_overloaded_fns' (hint: "_overloaded_fns: Dict[<type>, <type>] = ...") torch/_jit_internal.py:512: error: Need type annotation for '_overloaded_methods' (hint: "_overloaded_methods: Dict[<type>, <type>] = ...") torch/_jit_internal.py:648: error: Incompatible types in assignment (expression has type "FinalCls", variable has type "_SpecialForm") torch/sparse/__init__.py:11: error: Name 'Tensor' is not defined torch/sparse/__init__.py:71: error: Name 'Tensor' is not defined torch/sparse/__init__.py:71: error: Name 'Optional' is not defined torch/sparse/__init__.py:71: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/sparse/__init__.py:71: error: Name 'Tuple' is not defined torch/sparse/__init__.py:71: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/nn/init.py:109: error: Name 'Tensor' is not defined torch/nn/init.py:126: error: Name 'Tensor' is not defined torch/nn/init.py:142: error: Name 'Tensor' is not defined torch/nn/init.py:165: error: Name 'Tensor' is not defined torch/nn/init.py:180: error: Name 'Tensor' is not defined torch/nn/init.py:194: error: Name 'Tensor' is not defined torch/nn/init.py:287: error: Name 'Tensor' is not defined torch/nn/init.py:315: error: Name 'Tensor' is not defined torch/multiprocessing/reductions.py:8: error: No library stub file for standard library module 'multiprocessing.util' torch/multiprocessing/reductions.py:9: error: No library stub file for standard library module 'multiprocessing.reduction' torch/multiprocessing/reductions.py:17: error: No library stub file for standard library module 'multiprocessing.resource_sharer' torch/jit/_builtins.py:72: error: Module has no attribute "_no_grad_embedding_renorm_" torch/jit/_builtins.py:80: error: Module has no attribute "stft" torch/jit/_builtins.py:81: error: Module has no attribute "cdist" torch/jit/_builtins.py:82: error: Module has no attribute "norm" torch/jit/_builtins.py:83: error: Module has no attribute "nuclear_norm" torch/jit/_builtins.py:84: error: Module has no attribute "frobenius_norm" torch/backends/cudnn/__init__.py:8: error: Cannot find implementation or library stub for module named 'torch._C' torch/backends/cudnn/__init__.py:86: error: Need type annotation for '_handles' (hint: "_handles: Dict[<type>, <type>] = ...") torch/autograd/profiler.py:13: error: Name 'ContextDecorator' already defined (possibly by an import) torch/autograd/function.py:2: error: Cannot find implementation or library stub for module named 'torch._C' torch/autograd/function.py:2: note: See https://mypy.readthedocs.io/en/latest/running_mypy.html#missing-imports torch/autograd/function.py:109: error: Unsupported dynamic base class "with_metaclass" torch/serialization.py:609: error: "Callable[[Any], Any]" has no attribute "cache" torch/_lowrank.py:11: error: Name 'Tensor' is not defined torch/_lowrank.py:13: error: Name 'Optional' is not defined torch/_lowrank.py:13: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_lowrank.py:14: error: Name 'Optional' is not defined torch/_lowrank.py:14: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_lowrank.py:14: error: Name 'Tensor' is not defined torch/_lowrank.py:82: error: Name 'Tensor' is not defined torch/_lowrank.py:82: error: Name 'Optional' is not defined torch/_lowrank.py:82: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_lowrank.py:82: error: Name 'Tuple' is not defined torch/_lowrank.py:82: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/_lowrank.py:130: error: Name 'Tensor' is not defined torch/_lowrank.py:130: error: Name 'Optional' is not defined torch/_lowrank.py:130: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_lowrank.py:130: error: Name 'Tuple' is not defined torch/_lowrank.py:130: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/_lowrank.py:167: error: Name 'Tensor' is not defined torch/_lowrank.py:167: error: Name 'Optional' is not defined torch/_lowrank.py:167: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_lowrank.py:167: error: Name 'Tuple' is not defined torch/_lowrank.py:167: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/quantization/observer.py:45: error: Variable "torch.quantization.observer.ABC" is not valid as a type torch/quantization/observer.py:45: note: See https://mypy.readthedocs.io/en/latest/common_issues.html#variables-vs-type-aliases torch/quantization/observer.py:45: error: Invalid base class "ABC" torch/quantization/observer.py:127: error: Name 'Tensor' is not defined torch/quantization/observer.py:127: error: Name 'Tuple' is not defined torch/quantization/observer.py:127: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/quantization/observer.py:172: error: Module has no attribute "per_tensor_symmetric" torch/quantization/observer.py:172: error: Module has no attribute "per_channel_symmetric" torch/quantization/observer.py:192: error: Name 'Tensor' is not defined torch/quantization/observer.py:192: error: Name 'Tuple' is not defined torch/quantization/observer.py:192: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/quantization/observer.py:233: error: Module has no attribute "per_tensor_symmetric" torch/quantization/observer.py:233: error: Module has no attribute "per_channel_symmetric" torch/quantization/observer.py:534: error: Name 'Tensor' is not defined torch/quantization/observer.py:885: error: Name 'Tensor' is not defined torch/quantization/observer.py:885: error: Name 'Tuple' is not defined torch/quantization/observer.py:885: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/quantization/observer.py:894: error: Cannot determine type of 'max_val' torch/quantization/observer.py:894: error: Cannot determine type of 'min_val' torch/quantization/observer.py:899: error: Cannot determine type of 'min_val' torch/quantization/observer.py:902: error: Name 'Tensor' is not defined torch/quantization/observer.py:925: error: Name 'Tensor' is not defined torch/quantization/observer.py:928: error: Cannot determine type of 'min_val' torch/quantization/observer.py:929: error: Cannot determine type of 'max_val' torch/quantization/observer.py:946: error: Argument "min" to "histc" has incompatible type "Tuple[Tensor, Tensor]"; expected "Union[int, float, bool]" torch/quantization/observer.py:946: error: Argument "max" to "histc" has incompatible type "Tuple[Tensor, Tensor]"; expected "Union[int, float, bool]" torch/quantization/observer.py:1056: error: Module has no attribute "per_tensor_symmetric" torch/quantization/observer.py:1058: error: Module has no attribute "per_channel_symmetric" torch/nn/quantized/functional.py:76: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:76: error: Name 'BroadcastingList2' is not defined torch/nn/quantized/functional.py:259: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:259: error: Name 'Optional' is not defined torch/nn/quantized/functional.py:259: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/nn/quantized/functional.py:289: error: Module has no attribute "ops" torch/nn/quantized/functional.py:290: error: Module has no attribute "ops" torch/nn/quantized/functional.py:308: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:326: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:356: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:371: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:400: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:400: error: Name 'Optional' is not defined torch/nn/quantized/functional.py:400: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/nn/quantized/functional.py:430: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:448: error: Name 'Tensor' is not defined torch/nn/quantized/modules/linear.py:26: error: Module has no attribute "ops" torch/nn/quantized/modules/linear.py:28: error: Module has no attribute "ops" torch/nn/quantized/modules/functional_modules.py:40: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:47: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:54: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:61: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:68: error: Name 'List' is not defined torch/nn/quantized/modules/functional_modules.py:68: note: Did you forget to import it from "typing"? (Suggestion: "from typing import List") torch/nn/quantized/modules/functional_modules.py:68: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:75: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:140: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:146: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:151: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:157: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:162: error: Name 'List' is not defined torch/nn/quantized/modules/functional_modules.py:162: note: Did you forget to import it from "typing"? (Suggestion: "from typing import List") torch/nn/quantized/modules/functional_modules.py:162: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:168: error: Name 'Tensor' is not defined torch/multiprocessing/spawn.py:9: error: Module 'torch.multiprocessing' has no attribute '_prctl_pr_set_pdeathsig' torch/multiprocessing/__init__.py:28: error: Module has no attribute "__all__" torch/jit/frontend.py:9: error: Cannot find implementation or library stub for module named 'torch._C._jit_tree_views' torch/jit/annotations.py:6: error: Module 'torch._jit_internal' has no attribute 'BroadcastingList2'; maybe "BroadcastingList1" or "BroadcastingListCls"? torch/jit/annotations.py:6: error: Module 'torch._jit_internal' has no attribute 'BroadcastingList3'; maybe "BroadcastingList1" or "BroadcastingListCls"? torch/jit/annotations.py:9: error: Cannot find implementation or library stub for module named 'torch._C' torch/distributions/distribution.py:16: error: Need type annotation for 'arg_constraints' (hint: "arg_constraints: Dict[<type>, <type>] = ...") torch/distributions/distribution.py:74: error: Name 'arg_constraints' already defined on line 16 torch/distributions/distribution.py:84: error: Name 'support' already defined on line 15 torch/functional.py:114: error: Name 'Tuple' is not defined torch/functional.py:114: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/functional.py:114: error: Name 'Optional' is not defined torch/functional.py:114: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:189: error: Incompatible types in assignment (expression has type "None", variable has type "Tensor") torch/functional.py:200: error: Argument 1 to "_indices_product" has incompatible type "Tuple[int, ...]"; expected "List[int]" torch/functional.py:204: error: No overload variant of "__setitem__" of "list" matches argument types "Tensor", "int" torch/functional.py:204: note: Possible overload variants: torch/functional.py:204: note: def __setitem__(self, int, int) -> None torch/functional.py:204: note: def __setitem__(self, slice, Iterable[int]) -> None torch/functional.py:204: error: No overload variant of "__getitem__" of "list" matches argument type "Tensor" torch/functional.py:204: note: def __getitem__(self, int) -> int torch/functional.py:204: note: def __getitem__(self, slice) -> List[int] torch/functional.py:207: error: "Tensor" has no attribute "copy_" torch/functional.py:212: error: No overload variant of "__setitem__" of "list" matches argument types "Tensor", "int" torch/functional.py:212: note: Possible overload variants: torch/functional.py:212: note: def __setitem__(self, int, int) -> None torch/functional.py:212: note: def __setitem__(self, slice, Iterable[int]) -> None torch/functional.py:212: error: No overload variant of "__getitem__" of "list" matches argument type "Tensor" torch/functional.py:212: note: def __getitem__(self, int) -> int torch/functional.py:212: note: def __getitem__(self, slice) -> List[int] torch/functional.py:215: error: Incompatible types in assignment (expression has type "None", variable has type "Tensor") torch/functional.py:334: error: Name 'Optional' is not defined torch/functional.py:334: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:429: error: Argument 2 to "pad" has incompatible type "Tuple[int, int]"; expected "List[int]" torch/functional.py:431: error: Module has no attribute "stft" torch/functional.py:766: error: Module has no attribute "cdist" torch/functional.py:768: error: Module has no attribute "cdist" torch/functional.py:770: error: Module has no attribute "cdist" torch/functional.py:775: error: Name 'Optional' is not defined torch/functional.py:775: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:780: error: Name 'Optional' is not defined torch/functional.py:780: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:780: error: Name 'number' is not defined torch/functional.py:780: error: Name 'norm' already defined on line 775 torch/functional.py:785: error: Name 'Optional' is not defined torch/functional.py:785: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:785: error: Name 'number' is not defined torch/functional.py:785: error: Name 'norm' already defined on line 775 torch/functional.py:790: error: Name 'Optional' is not defined torch/functional.py:790: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:790: error: Name 'norm' already defined on line 775 torch/functional.py:795: error: Name 'norm' already defined on line 775 torch/functional.py:960: error: Name 'Any' is not defined torch/functional.py:960: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Any") torch/functional.py:960: error: Name 'Tuple' is not defined torch/functional.py:960: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/functional.py:1036: error: Argument 1 to "len" has incompatible type "int"; expected "Sized" torch/functional.py:1041: error: Name 'Optional' is not defined torch/functional.py:1041: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:1041: error: Name 'Tuple' is not defined torch/functional.py:1041: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/functional.py:1056: error: Name 'Optional' is not defined torch/functional.py:1056: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:1056: error: Name 'Tuple' is not defined torch/functional.py:1056: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/distributions/von_mises.py:87: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/negative_binomial.py:25: error: Incompatible types in assignment (expression has type "_IntegerGreaterThan", base class "Distribution" defined the type as "None") torch/distributions/multivariate_normal.py:116: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/laplace.py:23: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/independent.py:34: error: Need type annotation for 'arg_constraints' (hint: "arg_constraints: Dict[<type>, <type>] = ...") torch/distributions/cauchy.py:28: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/poisson.py:28: error: Incompatible types in assignment (expression has type "_IntegerGreaterThan", base class "Distribution" defined the type as "None") torch/distributions/one_hot_categorical.py:32: error: Incompatible types in assignment (expression has type "_Simplex", base class "Distribution" defined the type as "None") torch/distributions/normal.py:27: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/lowrank_multivariate_normal.py:79: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/gamma.py:30: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/exponential.py:23: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/fishersnedecor.py:25: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/dirichlet.py:44: error: Incompatible types in assignment (expression has type "_Simplex", base class "Distribution" defined the type as "None") torch/nn/quantized/dynamic/modules/rnn.py:230: error: Incompatible types in assignment (expression has type "int", variable has type "Tensor") torch/nn/quantized/dynamic/modules/rnn.py:232: error: Incompatible types in assignment (expression has type "int", variable has type "Tensor") torch/nn/quantized/dynamic/modules/rnn.py:236: error: Incompatible return value type (got "Tuple[Any, Tensor, Any]", expected "Tuple[int, int, int]") torch/nn/quantized/dynamic/modules/rnn.py:351: error: Incompatible types in assignment (expression has type "Type[LSTM]", base class "RNNBase" defined the type as "Type[RNNBase]") torch/nn/quantized/dynamic/modules/rnn.py:381: error: Module has no attribute "quantized_lstm" torch/nn/quantized/dynamic/modules/rnn.py:385: error: Module has no attribute "quantized_lstm" torch/nn/quantized/dynamic/modules/rnn.py:414: error: Argument 1 to "forward_impl" of "LSTM" has incompatible type "PackedSequence"; expected "Tensor" torch/nn/quantized/dynamic/modules/rnn.py:416: error: Incompatible types in assignment (expression has type "PackedSequence", variable has type "Tensor") torch/nn/quantized/dynamic/modules/rnn.py:418: error: Incompatible return value type (got "Tuple[Tensor, Tuple[Tensor, Tensor]]", expected "Tuple[PackedSequence, Tuple[Tensor, Tensor]]") torch/nn/quantized/dynamic/modules/rnn.py:420: error: Argument 1 of "permute_hidden" is incompatible with supertype "RNNBase"; supertype defines the argument type as "Tensor" torch/nn/quantized/dynamic/modules/rnn.py:420: error: Return type "Tuple[Tensor, Tensor]" of "permute_hidden" incompatible with return type "Tensor" in supertype "RNNBase" torch/nn/quantized/dynamic/modules/rnn.py:426: error: Argument 2 of "check_forward_args" is incompatible with supertype "RNNBase"; supertype defines the argument type as "Tensor" torch/nn/intrinsic/qat/modules/conv_fused.py:232: error: Incompatible types in assignment (expression has type "Type[ConvBnReLU2d]", base class "ConvBn2d" defined the type as "Type[ConvBn2d]") torch/distributions/beta.py:27: error: Incompatible types in assignment (expression has type "_Interval", base class "Distribution" defined the type as "None") torch/distributions/geometric.py:31: error: Incompatible types in assignment (expression has type "_IntegerGreaterThan", base class "Distribution" defined the type as "None") torch/distributions/continuous_bernoulli.py:38: error: Incompatible types in assignment (expression has type "_Interval", base class "Distribution" defined the type as "None") torch/distributions/bernoulli.py:30: error: Incompatible types in assignment (expression has type "_Boolean", base class "Distribution" defined the type as "None") torch/quantization/fake_quantize.py:126: error: Module has no attribute "per_tensor_symmetric" torch/quantization/fake_quantize.py:132: error: Module has no attribute "per_channel_symmetric" torch/distributions/transformed_distribution.py:41: error: Need type annotation for 'arg_constraints' (hint: "arg_constraints: Dict[<type>, <type>] = ...") torch/jit/__init__.py:1: error: Cannot find implementation or library stub for module named 'torch._C' torch/jit/__init__.py:15: error: Module 'torch.utils' has no attribute 'set_module' torch/jit/__init__.py:70: error: Name 'Attribute' already defined on line 68 torch/jit/__init__.py:213: error: On Python 3 '{}'.format(b'abc') produces "b'abc'"; use !r if this is a desired behavior torch/jit/__init__.py:215: error: On Python 3 '{}'.format(b'abc') produces "b'abc'"; use !r if this is a desired behavior torch/jit/__init__.py:1524: error: Unsupported dynamic base class "with_metaclass" torch/jit/__init__.py:1869: error: Name 'ScriptModule' already defined on line 1524 torch/jit/__init__.py:1998: error: Need type annotation for '_jit_caching_layer' torch/jit/__init__.py:1999: error: Need type annotation for '_jit_function_overload_caching' torch/distributions/relaxed_categorical.py:34: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/relaxed_categorical.py:108: error: Incompatible types in assignment (expression has type "_Simplex", base class "Distribution" defined the type as "None") torch/distributions/relaxed_bernoulli.py:31: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/relaxed_bernoulli.py:114: error: Incompatible types in assignment (expression has type "_Interval", base class "Distribution" defined the type as "None") torch/distributions/logistic_normal.py:31: error: Incompatible types in assignment (expression has type "_Simplex", base class "Distribution" defined the type as "None") torch/distributions/log_normal.py:26: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/half_normal.py:27: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/half_cauchy.py:28: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/gumbel.py:28: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/nn/quantized/modules/conv.py:18: error: Module 'torch.nn.utils' has no attribute 'fuse_conv_bn_weights' torch/nn/quantized/modules/conv.py:209: error: Name 'Optional' is not defined torch/nn/quantized/modules/conv.py:209: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/nn/quantized/modules/conv.py:214: error: Module has no attribute "ops" torch/nn/quantized/modules/conv.py:321: error: Name 'Optional' is not defined torch/nn/quantized/modules/conv.py:321: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/nn/quantized/modules/conv.py:323: error: Module has no attribute "ops" torch/nn/quantized/modules/conv.py:447: error: Name 'Optional' is not defined torch/nn/quantized/modules/conv.py:447: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/nn/quantized/modules/conv.py:449: error: Module has no attribute "ops" torch/nn/quantized/modules/conv.py:513: error: Name 'nn.modules.conv._ConvTransposeNd' is not defined torch/nn/quantized/modules/conv.py:525: error: Name 'List' is not defined torch/nn/quantized/modules/conv.py:525: note: Did you forget to import it from "typing"? (Suggestion: "from typing import List") torch/nn/quantized/modules/conv.py:527: error: Name 'List' is not defined torch/nn/quantized/modules/conv.py:527: note: Did you forget to import it from "typing"? (Suggestion: "from typing import List") torch/nn/intrinsic/quantized/modules/conv_relu.py:8: error: Module 'torch.nn.utils' has no attribute 'fuse_conv_bn_weights' torch/nn/intrinsic/quantized/modules/conv_relu.py:21: error: Incompatible types in assignment (expression has type "Type[ConvReLU2d]", base class "Conv2d" defined the type as "Type[Conv2d]") torch/nn/intrinsic/quantized/modules/conv_relu.py:62: error: Incompatible types in assignment (expression has type "Type[ConvReLU3d]", base class "Conv3d" defined the type as "Type[Conv3d]") torch/distributions/weibull.py:25: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/kl.py:35: error: Need type annotation for '_KL_MEMOIZE' (hint: "_KL_MEMOIZE: Dict[<type>, <type>] = ...") torch/distributions/studentT.py:27: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/mixture_same_family.py:48: error: Need type annotation for 'arg_constraints' (hint: "arg_constraints: Dict[<type>, <type>] = ...") torch/distributions/__init__.py:158: error: Name 'transforms' is not defined torch/onnx/utils.py:21: error: Cannot find implementation or library stub for module named 'torch._C' torch/distributed/rendezvous.py:4: error: Cannot find implementation or library stub for module named 'urlparse' torch/distributed/rendezvous.py:4: error: Name 'urlparse' already defined (possibly by an import) torch/distributed/rendezvous.py:4: error: Name 'urlunparse' already defined (possibly by an import) torch/distributed/rendezvous.py:9: error: Module 'torch.distributed' has no attribute 'FileStore' torch/distributed/rendezvous.py:9: error: Module 'torch.distributed' has no attribute 'TCPStore' torch/distributed/rendezvous.py:65: error: On Python 3 '{}'.format(b'abc') produces "b'abc'"; use !r if this is a desired behavior torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'AllreduceOptions'; maybe "ReduceOptions" or "AllreduceCoalescedOptions"? torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'AllreduceCoalescedOptions'; maybe "AllreduceOptions"? torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'AllToAllOptions' torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'BroadcastOptions' torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'GatherOptions'; maybe "ScatterOptions"? torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'ReduceOptions'; maybe "AllreduceOptions", "ReduceScatterOptions", or "ReduceOp"? torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'ReduceScatterOptions'; maybe "ScatterOptions" or "ReduceOptions"? torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'ScatterOptions'; maybe "ReduceScatterOptions" or Pull Request resolved: https://github.com/pytorch/pytorch/pull/36584 Reviewed By: seemethere, ailzhang Differential Revision: D21155985 Pulled By: ezyang fbshipit-source-id: f628d4293992576207167e7c417998fad15898d1 |