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Author SHA1 Message Date
Yan Zhiwei
ae351d4d0e [Intel GPU] allow_tf32 for oneDNN backend - XPU part (#137570) 
# Motivation
Add context variable `torch.bachend.mkldnn.allow_tf32` to control tf32 computation in convolution kernels at XPU side.  The tf32 data type is beneficial to improve the performance of deep learning workloads during training/inference. Current PR uses the [oneDNN API fpmath_mode](https://oneapi-src.github.io/oneDNN/dev_guide_attributes_fpmath_mode.html#the-floating-point-math-mode-attribute) to trigger the tf32 acceleration in convolution kernels.

# Valiadation
* ut to test context variable
`python test/xpu/test_conv.py -k test_mkldnn_allow_tf32_get_set`

* Runtime exemplification
```
onednn_verbose,primitive,exec,gpu:0,convolution,jit:ir,forward_training,src_f32::blocked:abcd::f0 wei_f32::blocked:abcd::f0 bia_f32::blocked:a::f0 dst_f32::blocked:abcd::f0,attr-scratchpad:user attr-fpmath:tf32,alg:convolution_direct,mb20_ic16oc33_ih50oh24kh3sh2dh0ph0_iw100ow49kw3sw2dw0pw0,0.649902
onednn_verbose,primitive,exec,gpu:0,convolution,jit:ir,forward_training,src_f32::blocked:abcd::f0 wei_f32::blocked:abcd::f0 bia_f32::blocked:a::f0 dst_f32::blocked:abcd::f0,attr-scratchpad:user attr-fpmath:tf32,alg:convolution_direct,mb20_ic33oc33_ih24oh24kh3sh1dh0ph1_iw49ow49kw3sw1dw0pw1,0.151855
onednn_verbose,primitive,exec,gpu:0,convolution,jit:ir,backward_data,src_f32::blocked:abcd::f0 wei_f32::blocked:abcd::f0 bia_undef::undef::: dst_f32::blocked:abcd::f0,attr-scratchpad:user attr-fpmath:tf32,alg:convolution_direct,mb20_ic33oc33_ih24oh24kh3sh1dh0ph1_iw49ow49kw3sw1dw0pw1,0.167969
onednn_verbose,primitive,exec,gpu:0,convolution,jit:ir,backward_weights,src_f32::blocked:abcd::f0 wei_f32::blocked:abcd::f0 bia_f32::blocked:a::f0 dst_f32::blocked:abcd::f0,attr-scratchpad:user attr-fpmath:tf32,alg:convolution_direct,mb20_ic33oc33_ih24oh24kh3sh1dh0ph1_iw49ow49kw3sw1dw0pw1,0.26709
onednn_verbose,primitive,exec,gpu:0,convolution,jit:ir,backward_weights,src_f32::blocked:abcd::f0 wei_f32::blocked:abcd::f0 bia_f32::blocked:a::f0 dst_f32::blocked:abcd::f0,attr-scratchpad:user attr-fpmath:tf32,alg:convolution_direct,mb20_ic16oc33_ih50oh24kh3sh2dh0ph0_iw100ow49kw3sw2dw0pw0,0.219971

```
According to the field `fpmath:tf32` in verbose, we could see that, current context setting utils could successfully trigger tf32 computation in conv forward/backward_data/backward_weights kernels.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/137570
Approved by: https://github.com/guangyey, https://github.com/EikanWang, https://github.com/atalman, https://github.com/malfet

Co-authored-by: Yu, Guangye <guangye.yu@intel.com>
 2025-02-17 01:46:43 +00:00
Xuehai Pan
f3fce597e9 [BE][Easy][17/19] enforce style for empty lines in import segments in torch/[a-c]*/ and torch/[e-n]*/ (#129769) 
See https://github.com/pytorch/pytorch/pull/129751#issue-2380881501. Most changes are auto-generated by linter.

You can review these PRs via:

```bash
git diff --ignore-all-space --ignore-blank-lines HEAD~1
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129769
Approved by: https://github.com/ezyang
 2024-08-04 10:24:09 +00:00
Deng Weishi
b542825066 Enable deterministic support for oneDNN (#127277) 
This PR is a part of RFC https://github.com/pytorch/pytorch/issues/114848.
For the request for Torchbenchmark models, this PR enables the deterministic attribute for the oneDNN operators for XPU backends, like convolution, deconvolution and matmult.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/127277
Approved by: https://github.com/jgong5, https://github.com/EikanWang, https://github.com/desertfire, https://github.com/gujinghui
 2024-06-21 05:21:24 +00:00
Aaron Orenstein
62bcdc0ac9 Flip default value for mypy disallow_untyped_defs [4/11] (#127841) 
See #127836 for details.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/127841
Approved by: https://github.com/oulgen
 2024-06-08 18:36:48 +00:00
Colin Peppler
1f6aa4b336 [mypy] Enable follow_imports = normal for mypy-torch.backends.* (#116311) 
Summary:

Test Plan:

```
lintrunner --take MYPYINDUCTOR --all-files
ok No lint issues.

lintrunner -a
ok No lint issues.
Successfully applied all patches.
```

Reviewers:

Subscribers:

Tasks:

Tags:

Pull Request resolved: https://github.com/pytorch/pytorch/pull/116311
Approved by: https://github.com/int3
 2024-01-25 20:17:22 +00:00
NVS Abhilash
eb5487361d docs: fix docstring errors in quantized modules and others (#112695) 
Fixes #112632

Before: 171
```
torch/backends/_nnapi/prepare.py:24 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/_nnapi/prepare.py:46 in public method `init`:
        D102: Missing docstring in public method
torch/backends/_nnapi/prepare.py:60 in public method `forward`:
        D102: Missing docstring in public method
torch/backends/_nnapi/prepare.py:94 in public function `convert_model_to_nnapi`:
        D103: Missing docstring in public function
torch/backends/_nnapi/prepare.py:153 in public function `process_for_nnapi`:
        D103: Missing docstring in public function
torch/backends/_nnapi/prepare.py:177 in private nested class `ShapeComputeModule`:
        D400: First line should end with a period (not 'n')
torch/backends/_nnapi/serializer.py:19 in public class `NNAPI_OperandCode`:
        D101: Missing docstring in public class
torch/backends/_nnapi/serializer.py:35 in public class `NNAPI_OperationCode`:
        D101: Missing docstring in public class
torch/backends/_nnapi/serializer.py:133 in public class `NNAPI_FuseCode`:
        D101: Missing docstring in public class
torch/backends/_nnapi/serializer.py:140 in public class `OperandValueSourceType`:
        D101: Missing docstring in public class
torch/backends/_nnapi/serializer.py:150 in public class `TorchScalarTypes`:
        D101: Missing docstring in public class
torch/backends/_nnapi/serializer.py:154 in public function `approx_equal`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:158 in public function `tensor_size`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:172 in public function `change_element`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:194 in public class `DimOrder`:
        D101: Missing docstring in public class
torch/backends/_nnapi/serializer.py:225 in public method `use_nchw`:
        D102: Missing docstring in public method
torch/backends/_nnapi/serializer.py:233 in public function `broadcast_shapes`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:260 in public function `get_conv_pool_shape`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:284 in public function `fix_shape`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:301 in public function `reverse_map_dim`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:312 in public function `flex_name`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:1337 in private method `_do_add_binary`:
        D400: First line should end with a period (not 's')
torch/backends/_nnapi/serializer.py:1337 in private method `_do_add_binary`:
        D401: First line should be in imperative mood; try rephrasing (found 'Helper')
torch/backends/_nnapi/serializer.py:2180 in public function `serialize_model`:
        D202: No blank lines allowed after function docstring (found 1)
torch/backends/_nnapi/serializer.py:2180 in public function `serialize_model`:
        D205: 1 blank line required between summary line and description (found 0)
torch/backends/_nnapi/serializer.py:2180 in public function `serialize_model`:
        D400: First line should end with a period (not ':')
torch/backends/cuda/__init__.py:1 at module level:
        D104: Missing docstring in public package
torch/backends/cuda/__init__.py:30 in public function `is_built`:
        D205: 1 blank line required between summary line and description (found 0)
torch/backends/cuda/__init__.py:30 in public function `is_built`:
        D209: Multi-line docstring closing quotes should be on a separate line
torch/backends/cuda/__init__.py:30 in public function `is_built`:
        D400: First line should end with a period (not 's')
torch/backends/cuda/__init__.py:30 in public function `is_built`:
        D401: First line should be in imperative mood (perhaps 'Return', not 'Returns')
torch/backends/cuda/__init__.py:37 in public class `cuFFTPlanCacheAttrContextProp`:
        D101: Missing docstring in public class
torch/backends/cuda/__init__.py:40 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/cuda/__init__.py:44 in public method `__get__`:
        D105: Missing docstring in magic method
torch/backends/cuda/__init__.py:47 in public method `__set__`:
        D105: Missing docstring in magic method
torch/backends/cuda/__init__.py:54 in public class `cuFFTPlanCache`:
        D205: 1 blank line required between summary line and description (found 0)
torch/backends/cuda/__init__.py:54 in public class `cuFFTPlanCache`:
        D400: First line should end with a period (not 'e')
torch/backends/cuda/__init__.py:60 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/cuda/__init__.py:73 in public method `clear`:
        D102: Missing docstring in public method
torch/backends/cuda/__init__.py:78 in public class `cuFFTPlanCacheManager`:
        D205: 1 blank line required between summary line and description (found 0)
torch/backends/cuda/__init__.py:78 in public class `cuFFTPlanCacheManager`:
        D400: First line should end with a period (not ',')
torch/backends/cuda/__init__.py:89 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/cuda/__init__.py:93 in public method `__getitem__`:
        D105: Missing docstring in magic method
torch/backends/cuda/__init__.py:106 in public method `__getattr__`:
        D105: Missing docstring in magic method
torch/backends/cuda/__init__.py:109 in public method `__setattr__`:
        D105: Missing docstring in magic method
torch/backends/cuda/__init__.py:116 in public class `cuBLASModule`:
        D101: Missing docstring in public class
torch/backends/cuda/__init__.py:117 in public method `__getattr__`:
        D105: Missing docstring in magic method
torch/backends/cuda/__init__.py:126 in public method `__setattr__`:
        D105: Missing docstring in magic method
torch/backends/cuda/__init__.py:147 in public function `preferred_linalg_library`:
        D202: No blank lines allowed after function docstring (found 1)
torch/backends/cuda/__init__.py:204 in public class `SDPBackend`:
        D204: 1 blank line required after class docstring (found 0)
torch/backends/cudnn/__init__.py:1 at module level:
        D104: Missing docstring in public package
torch/backends/cudnn/__init__.py:81 in public function `version`:
        D400: First line should end with a period (not 'N')
torch/backends/cudnn/__init__.py:81 in public function `version`:
        D401: First line should be in imperative mood (perhaps 'Return', not 'Returns')
torch/backends/cudnn/__init__.py:95 in public function `is_available`:
        D401: First line should be in imperative mood (perhaps 'Return', not 'Returns')
torch/backends/cudnn/__init__.py:99 in public function `is_acceptable`:
        D103: Missing docstring in public function
torch/backends/cudnn/__init__.py:122 in public function `set_flags`:
        D103: Missing docstring in public function
torch/backends/cudnn/__init__.py:150 in public function `flags`:
        D103: Missing docstring in public function
torch/backends/cudnn/__init__.py:174 in public class `CudnnModule`:
        D101: Missing docstring in public class
torch/backends/cudnn/__init__.py:175 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/mkl/__init__.py:1 at module level:
        D104: Missing docstring in public package
torch/backends/mkl/__init__.py:5 in public function `is_available`:
        D401: First line should be in imperative mood (perhaps 'Return', not 'Returns')
torch/backends/mkl/__init__.py:14 in public class `verbose`:
        D205: 1 blank line required between summary line and description (found 0)
torch/backends/mkl/__init__.py:14 in public class `verbose`:
        D400: First line should end with a period (not 'y')
torch/backends/mkl/__init__.py:41 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/mkl/__init__.py:44 in public method `__enter__`:
        D105: Missing docstring in magic method
torch/backends/mkl/__init__.py:53 in public method `__exit__`:
        D105: Missing docstring in magic method
torch/backends/mkldnn/__init__.py:1 at module level:
        D104: Missing docstring in public package
torch/backends/mkldnn/__init__.py:9 in public function `is_available`:
        D401: First line should be in imperative mood (perhaps 'Return', not 'Returns')
torch/backends/mkldnn/__init__.py:19 in public class `verbose`:
        D205: 1 blank line required between summary line and description (found 0)
torch/backends/mkldnn/__init__.py:19 in public class `verbose`:
        D400: First line should end with a period (not 'y')
torch/backends/mkldnn/__init__.py:47 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/mkldnn/__init__.py:50 in public method `__enter__`:
        D105: Missing docstring in magic method
torch/backends/mkldnn/__init__.py:59 in public method `__exit__`:
        D105: Missing docstring in magic method
torch/backends/mkldnn/__init__.py:64 in public function `set_flags`:
        D103: Missing docstring in public function
torch/backends/mkldnn/__init__.py:71 in public function `flags`:
        D103: Missing docstring in public function
torch/backends/mkldnn/__init__.py:81 in public class `MkldnnModule`:
        D101: Missing docstring in public class
torch/backends/mkldnn/__init__.py:82 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/openmp/__init__.py:1 at module level:
        D104: Missing docstring in public package
torch/backends/openmp/__init__.py:5 in public function `is_available`:
        D401: First line should be in imperative mood (perhaps 'Return', not 'Returns')
torch/nn/intrinsic/qat/modules/conv_fused.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/intrinsic/qat/modules/linear_fused.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/intrinsic/qat/modules/linear_relu.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/qat/__init__.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/qat/dynamic/__init__.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/qat/dynamic/modules/linear.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/qat/modules/__init__.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/qat/modules/conv.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/qat/modules/embedding_ops.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/qat/modules/linear.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantizable/modules/activation.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantizable/modules/rnn.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/_reference/modules/__init__.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/_reference/modules/conv.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/_reference/modules/linear.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/_reference/modules/rnn.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/_reference/modules/sparse.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/_reference/modules/utils.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/dynamic/modules/__init__.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/dynamic/modules/conv.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/dynamic/modules/linear.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/dynamic/modules/rnn.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/functional.py:1 at module level:
        D400: First line should end with a period (not 'l')
torch/nn/quantized/modules/__init__.py:1 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/modules/activation.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/modules/batchnorm.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/modules/conv.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/modules/dropout.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/modules/embedding_ops.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/modules/functional_modules.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/modules/linear.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/modules/normalization.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/modules/rnn.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/quantized/modules/utils.py:2 at module level:
        D400: First line should end with a period (not 's')
torch/nn/utils/_expanded_weights/conv_utils.py:13 in public function `conv_picker`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:23 in public function `conv_args_and_kwargs`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:31 in public function `conv_normalizer`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:35 in public function `conv_input_for_string_padding`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:43 in public function `int_padding_for_string_padding`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:59 in public function `conv_padding_for_same`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:66 in public function `conv_backward`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:131 in public function `conv_unfold_weight_grad_sample`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:166 in public function `conv_group_weight_grad_sample`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:189 in public function `unfold3d`:
        D202: No blank lines allowed after function docstring (found 1)
torch/nn/utils/_expanded_weights/conv_utils.py:189 in public function `unfold3d`:
        D205: 1 blank line required between summary line and description (found 0)
torch/nn/utils/_expanded_weights/conv_utils.py:189 in public function `unfold3d`:
        D401: First line should be in imperative mood (perhaps 'Extract', not 'Extracts')
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:6 in public function `is_batch_first`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:19 in public function `standard_kwargs`:
        D205: 1 blank line required between summary line and description (found 0)
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:19 in public function `standard_kwargs`:
        D300: Use """triple double quotes""" (found '''-quotes)
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:19 in public function `standard_kwargs`:
        D400: First line should end with a period (not 'e')
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:28 in public function `forward_helper`:
        D205: 1 blank line required between summary line and description (found 0)
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:28 in public function `forward_helper`:
        D300: Use """triple double quotes""" (found '''-quotes)
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:28 in public function `forward_helper`:
        D400: First line should end with a period (not ')')
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:84 in public function `maybe_scale_by_batch_size`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:90 in public function `set_grad_sample_if_exists`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:108 in public function `unpack_expanded_weight_or_tensor`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:123 in public function `sum_over_all_but_batch_and_last_n`:
        D205: 1 blank line required between summary line and description (found 0)
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:123 in public function `sum_over_all_but_batch_and_last_n`:
        D400: First line should end with a period (not 't')
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:123 in public function `sum_over_all_but_batch_and_last_n`:
        D401: First line should be in imperative mood (perhaps 'Calculate', not 'Calculates')
torch/nn/utils/convert_parameters.py:1 at module level:
        D100: Missing docstring in public module
torch/nn/utils/convert_parameters.py:57 in private function `_check_param_device`:
        D202: No blank lines allowed after function docstring (found 1)
torch/nn/utils/convert_parameters.py:57 in private function `_check_param_device`:
        D205: 1 blank line required between summary line and description (found 0)
torch/nn/utils/convert_parameters.py:57 in private function `_check_param_device`:
        D400: First line should end with a period (not 'd')
torch/nn/utils/convert_parameters.py:57 in private function `_check_param_device`:
        D401: First line should be in imperative mood; try rephrasing (found 'This')
torch/nn/utils/rnn.py:1 at module level:
        D100: Missing docstring in public module
torch/nn/utils/rnn.py:28 in public class `PackedSequence`:
        D204: 1 blank line required after class docstring (found 0)
torch/nn/utils/rnn.py:63 in public method `__new__`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:73 in public method `pin_memory`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:80 in public method `cuda`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:87 in public method `cpu`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:94 in public method `double`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:97 in public method `float`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:100 in public method `half`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:103 in public method `long`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:106 in public method `int`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:109 in public method `short`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:112 in public method `char`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:115 in public method `byte`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:119 in public method `to`:
        D202: No blank lines allowed after function docstring (found 1)
torch/nn/utils/rnn.py:119 in public method `to`:
        D401: First line should be in imperative mood (perhaps 'Perform', not 'Performs')
torch/nn/utils/rnn.py:146 in public method `is_cuda`:
        D400: First line should end with a period (not 'u')
torch/nn/utils/rnn.py:150 in public method `is_pinned`:
        D400: First line should end with a period (not 'y')
torch/nn/utils/rnn.py:150 in public method `is_pinned`:
        D401: First line should be in imperative mood (perhaps 'Return', not 'Returns')
torch/nn/utils/rnn.py:198 in public function `invert_permutation`:
        D103: Missing docstring in public function
torch/nn/utils/rnn.py:274 in public function `pad_packed_sequence`:
        D401: First line should be in imperative mood (perhaps 'Pad', not 'Pads')
torch/nn/utils/rnn.py:347 in public function `pad_sequence`:
        D202: No blank lines allowed after function docstring (found 1)
torch/nn/utils/rnn.py:347 in public function `pad_sequence`:
        D400: First line should end with a period (not '`')
torch/nn/utils/rnn.py:408 in public function `unpad_sequence`:
        D202: No blank lines allowed after function docstring (found 1)
torch/nn/utils/rnn.py:408 in public function `unpad_sequence`:
        D400: First line should end with a period (not 's')
torch/nn/utils/rnn.py:454 in public function `pack_sequence`:
        D400: First line should end with a period (not 's')
torch/nn/utils/rnn.py:490 in public function `unpack_sequence`:
        D202: No blank lines allowed after function docstring (found 1)
torch/nn/utils/rnn.py:490 in public function `unpack_sequence`:
        D400: First line should end with a period (not 's')
171
```

After: 81
```
torch/backends/_nnapi/prepare.py:24 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/_nnapi/prepare.py:46 in public method `init`:
        D102: Missing docstring in public method
torch/backends/_nnapi/prepare.py:60 in public method `forward`:
        D102: Missing docstring in public method
torch/backends/_nnapi/prepare.py:94 in public function `convert_model_to_nnapi`:
        D103: Missing docstring in public function
torch/backends/_nnapi/prepare.py:153 in public function `process_for_nnapi`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:19 in public class `NNAPI_OperandCode`:
        D101: Missing docstring in public class
torch/backends/_nnapi/serializer.py:35 in public class `NNAPI_OperationCode`:
        D101: Missing docstring in public class
torch/backends/_nnapi/serializer.py:133 in public class `NNAPI_FuseCode`:
        D101: Missing docstring in public class
torch/backends/_nnapi/serializer.py:140 in public class `OperandValueSourceType`:
        D101: Missing docstring in public class
torch/backends/_nnapi/serializer.py:150 in public class `TorchScalarTypes`:
        D101: Missing docstring in public class
torch/backends/_nnapi/serializer.py:154 in public function `approx_equal`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:158 in public function `tensor_size`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:172 in public function `change_element`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:194 in public class `DimOrder`:
        D101: Missing docstring in public class
torch/backends/_nnapi/serializer.py:225 in public method `use_nchw`:
        D102: Missing docstring in public method
torch/backends/_nnapi/serializer.py:233 in public function `broadcast_shapes`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:260 in public function `get_conv_pool_shape`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:284 in public function `fix_shape`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:301 in public function `reverse_map_dim`:
        D103: Missing docstring in public function
torch/backends/_nnapi/serializer.py:312 in public function `flex_name`:
        D103: Missing docstring in public function
torch/backends/cuda/__init__.py:1 at module level:
        D104: Missing docstring in public package
torch/backends/cuda/__init__.py:39 in public class `cuFFTPlanCacheAttrContextProp`:
        D101: Missing docstring in public class
torch/backends/cuda/__init__.py:42 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/cuda/__init__.py:46 in public method `__get__`:
        D105: Missing docstring in magic method
torch/backends/cuda/__init__.py:49 in public method `__set__`:
        D105: Missing docstring in magic method
torch/backends/cuda/__init__.py:63 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/cuda/__init__.py:76 in public method `clear`:
        D102: Missing docstring in public method
torch/backends/cuda/__init__.py:91 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/cuda/__init__.py:95 in public method `__getitem__`:
        D105: Missing docstring in magic method
torch/backends/cuda/__init__.py:108 in public method `__getattr__`:
        D105: Missing docstring in magic method
torch/backends/cuda/__init__.py:111 in public method `__setattr__`:
        D105: Missing docstring in magic method
torch/backends/cuda/__init__.py:118 in public class `cuBLASModule`:
        D101: Missing docstring in public class
torch/backends/cuda/__init__.py:119 in public method `__getattr__`:
        D105: Missing docstring in magic method
torch/backends/cuda/__init__.py:128 in public method `__setattr__`:
        D105: Missing docstring in magic method
torch/backends/cudnn/__init__.py:1 at module level:
        D104: Missing docstring in public package
torch/backends/cudnn/__init__.py:99 in public function `is_acceptable`:
        D103: Missing docstring in public function
torch/backends/cudnn/__init__.py:122 in public function `set_flags`:
        D103: Missing docstring in public function
torch/backends/cudnn/__init__.py:150 in public function `flags`:
        D103: Missing docstring in public function
torch/backends/cudnn/__init__.py:174 in public class `CudnnModule`:
        D101: Missing docstring in public class
torch/backends/cudnn/__init__.py:175 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/mkl/__init__.py:1 at module level:
        D104: Missing docstring in public package
torch/backends/mkl/__init__.py:42 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/mkl/__init__.py:45 in public method `__enter__`:
        D105: Missing docstring in magic method
torch/backends/mkl/__init__.py:54 in public method `__exit__`:
        D105: Missing docstring in magic method
torch/backends/mkldnn/__init__.py:1 at module level:
        D104: Missing docstring in public package
torch/backends/mkldnn/__init__.py:48 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/mkldnn/__init__.py:51 in public method `__enter__`:
        D105: Missing docstring in magic method
torch/backends/mkldnn/__init__.py:60 in public method `__exit__`:
        D105: Missing docstring in magic method
torch/backends/mkldnn/__init__.py:65 in public function `set_flags`:
        D103: Missing docstring in public function
torch/backends/mkldnn/__init__.py:72 in public function `flags`:
        D103: Missing docstring in public function
torch/backends/mkldnn/__init__.py:82 in public class `MkldnnModule`:
        D101: Missing docstring in public class
torch/backends/mkldnn/__init__.py:83 in public method `__init__`:
        D107: Missing docstring in __init__
torch/backends/openmp/__init__.py:1 at module level:
        D104: Missing docstring in public package
torch/nn/utils/_expanded_weights/conv_utils.py:13 in public function `conv_picker`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:23 in public function `conv_args_and_kwargs`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:31 in public function `conv_normalizer`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:35 in public function `conv_input_for_string_padding`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:43 in public function `int_padding_for_string_padding`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:59 in public function `conv_padding_for_same`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:66 in public function `conv_backward`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:131 in public function `conv_unfold_weight_grad_sample`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/conv_utils.py:166 in public function `conv_group_weight_grad_sample`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:6 in public function `is_batch_first`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:87 in public function `maybe_scale_by_batch_size`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:93 in public function `set_grad_sample_if_exists`:
        D103: Missing docstring in public function
torch/nn/utils/_expanded_weights/expanded_weights_utils.py:111 in public function `unpack_expanded_weight_or_tensor`:
        D103: Missing docstring in public function
torch/nn/utils/convert_parameters.py:1 at module level:
        D100: Missing docstring in public module
torch/nn/utils/rnn.py:1 at module level:
        D100: Missing docstring in public module
torch/nn/utils/rnn.py:64 in public method `__new__`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:74 in public method `pin_memory`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:81 in public method `cuda`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:88 in public method `cpu`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:95 in public method `double`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:98 in public method `float`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:101 in public method `half`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:104 in public method `long`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:107 in public method `int`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:110 in public method `short`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:113 in public method `char`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:116 in public method `byte`:
        D102: Missing docstring in public method
torch/nn/utils/rnn.py:198 in public function `invert_permutation`:
        D103: Missing docstring in public function
81
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/112695
Approved by: https://github.com/mikaylagawarecki
 2023-11-07 23:52:16 +00:00
Edward Z. Yang
3bf922a6ce Apply UFMT to low traffic torch modules (#106249) 
Signed-off-by: Edward Z. Yang <ezyang@meta.com>

Pull Request resolved: https://github.com/pytorch/pytorch/pull/106249
Approved by: https://github.com/Skylion007
 2023-07-29 23:37:30 +00:00
Nikita Shulga
4cfa06f706 [BE] Deprecate has_XYZ attributes (#103279) 
Use [`__getattr__`](https://peps.python.org/pep-0562/) to raise warningwhen one tries to access `has_XYZ` methods and recommend appropriate `torch.backends.XYZ` methods

Make respective properties in `torch._C` private (by prefixing them with underscore), to exclude from `from torch._C import *`.

Added `warnings.simplefilter` to workaround Python-3.11 torch.compile lineinfo issue.

Fixes https://github.com/pytorch/pytorch/issues/102484

Pull Request resolved: https://github.com/pytorch/pytorch/pull/103279
Approved by: https://github.com/janeyx99, https://github.com/Skylion007
 2023-06-10 05:17:17 +00:00
Xuehai Pan
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.:

f152a79be9/caffe2/python/net_printer.py (L184-L190)

f152a79be9/test/test_jit_fuser_te.py (L2628-L2635)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94588
Approved by: https://github.com/ezyang, https://github.com/albanD
 2023-02-10 21:16:33 +00:00
Aaron Gokaslan
8fce9a09cd [BE]: pyupgrade Python to 3.8 - imports and object inheritance only (#94308) 
Apply parts of pyupgrade to torch (starting with the safest changes).
This PR only does two things: removes the need to inherit from object and removes unused future imports.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94308
Approved by: https://github.com/ezyang, https://github.com/albanD
 2023-02-07 21:10:56 +00:00
Jing Xu
0e95746580 [RFC] enable oneMKL&oneDNN on-demands verbose functinality (#63212) 
**RFC:
Problem statement** 
Intel oneMKL and oneDNN are used to accelerate performance on Intel platforms. Both these 2 libraries provide verbose functionality to dump detailed operator execution information as well as execution time. These verbose messages are very helpful to performance profiling. However, the verbose functionality works for the entire execution. In many scenarios, though, we only would like to profile partial of the execution process. This feature is to expose PyTorch API functions to control oneDNN and oneMKL verbose functionality in runtime.

**Additional context**  
The most used performance profiling steps are shown as the following code snippet:

```
def inference(model, inputs):
    # step0 (optional): jit
    model = torch.jit.trace(model, inputs)

    # step1: warmup
    for _ in range(100):
        model(inputs)

    # step2: performance profiling. We only care the profiling result, as well as oneDNN and oneMKL verbose messages, of this step
    model(inputs)

    # step3 (optional): benchmarking
    t0 = time.time()
    for _ in range(100):
        model(inputs)
    t1 = time.time()
    print(‘dur: {}’.format((t1-t0)/100))
    return model(inputs)
```

Since environment variables MKL_VERBOSE and DNNL_VERBOSE will be effect to the entire progress, we will get a great number of verbose messages for all of 101 iterations (if step3 is not involved). However, we only care about the verbose messages dumped in step2. It is very difficult to filter unnecessary verbose messages out if we are running into a complicated usages scenario. Also, jit trace will also bring more undesired verbose messages.

Furthermore, there are more complicated topologies or usages like cascaded topologies as below:

```
model1 = Model1()
model2 = Model2()
model3 = Model3()
x1 = inference(model1, x)
x2 = inference(model2, x1)
y = inference(model3, x2)
```

There are many cases that it is very hard to split these child topologies out. In this scenario, it is not possible to investigate performance of each individual topology with `DNNL_VERBOSE` and `MKL_VERBOSE`.

To solve this issue, oneDNN and oneMKL provide API functions to make it possible to control verbose functionality in runtime.
```
int mkl_verbose (int enable)
status dnnl::set_verbose(int level)
```

oneDNN and oneMKL print verbose messages to stdout when oneMKL or oneDNN ops are executed.
Sample verbose messages:
```
MKL_VERBOSE SGEMM(t,n,768,2048,3072,0x7fff64115800,0x7fa1aca58040,3072,0x1041f5c0,3072,0x7fff64115820,0x981f0c0,768) 8.52ms CNR:OFF Dyn:1 FastMM:1 TID:0  NThr:44
dnnl_verbose,exec,cpu,inner_product,brgemm:avx512_core,forward_training,src_f32::blocked:ab:f0 wei_f32::blocked:AB16b64a:f0 bia_f32::blocked:a:f0 dst_f32::blocked:ab:f0,,,mb16ic768oc768,0.0839844
```

**Design and implementation** 
The design is to make python-interfaced wrap functions to invoke mkl_verbose and dnnl::set_verbose functions.

**Design concern**  

- Need to add wrapper C++ functions for mkl_verbose and dnnl::set_verbose functions in torch/csrc and aten/csrc.
- Python API functions will be added to device-specific backends
  - with torch.backends.mkl.verbose(1):
  - with torch.backends.mkldnn.verbose(1):

**Use cases**  
```
def inference(model, inputs):
    # step0 (optional): jit
    model = torch.jit.trace(model, inputs)

    # step1: warmup
    for _ in range(100):
        model(inputs)

    # step2: performance profiling
    with torch.backends.mkl.verbose(1), torch.backends.mkldnn.verbose(1):
        model(inputs)

    # step3 (optional): benchmarking
    t0 = time.time()
    for _ in range(100):
        model(inputs)
    t1 = time.time()
    print(‘dur: {}’.format((t1-t0)/100))
    return model(inputs)
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63212
Approved by: https://github.com/VitalyFedyunin, https://github.com/malfet
 2022-07-27 23:29:35 +00:00
jiayisun
b9bf91feb8 Add torch.backends.mkldnn.enabled flag (#25459) 
Summary:
This PR is about add torch.backends.mkldnn.enabled flag said in https://github.com/pytorch/pytorch/issues/25186 which can be used disable mkldnn at runtime step as torch.backends.cudnn.enabled.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/25459

Differential Revision: D17258926

Pulled By: ezyang

fbshipit-source-id: e179ad364cc608fdaa7d0f37e2e762ceb5eda598
 2019-09-11 12:09:40 -07:00
Edward Yang
50df3e5e2e Add ability to query if built with CUDA and MKL-DNN. (#18362) 
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18362
ghimport-source-id: 374b7ab97e2d6a894368007133201f510539296f

Stack from [ghstack](https://github.com/ezyang/ghstack):
* #18242 Test running a CUDA build on CPU machine.
* **#18362 Add ability to query if built with CUDA and MKL-DNN.**

Fixes #18108.

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

Differential Revision: D14584430

fbshipit-source-id: 7605a1ac4e8f2a7c70d52e5a43ad7f03f0457473
 2019-03-25 10:39:09 -07:00