Adds a ruff lint rule to ban raising raw exceptions. Most of these should at the very least be runtime exception, value errors, type errors or some other errors. There are hundreds of instance of these bad exception types already in the codebase, so I have noqa'd most of them. Hopefully this error code will get commiters to rethink what exception type they should raise when they submit a PR.
I also encourage people to gradually go and fix all the existing noqas that have been added so they can be removed overtime and our exception typing can be improved.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/124570
Approved by: https://github.com/ezyang
Fixes https://github.com/pytorch/pytorch/issues/118129
Suppressions automatically added with
```
import re
with open("error_file.txt", "r") as f:
errors = f.readlines()
error_lines = {}
for error in errors:
match = re.match(r"(.*):(\d+):\d+: error:.*\[(.*)\]", error)
if match:
file_path, line_number, error_type = match.groups()
if file_path not in error_lines:
error_lines[file_path] = {}
error_lines[file_path][int(line_number)] = error_type
for file_path, lines in error_lines.items():
with open(file_path, "r") as f:
code = f.readlines()
for line_number, error_type in sorted(lines.items(), key=lambda x: x[0], reverse=True):
code[line_number - 1] = code[line_number - 1].rstrip() + f" # type: ignore[{error_type}]\n"
with open(file_path, "w") as f:
f.writelines(code)
```
Signed-off-by: Edward Z. Yang <ezyang@meta.com>
Co-authored-by: Catherine Lee <csl@fb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/118533
Approved by: https://github.com/Skylion007, https://github.com/zou3519
Fixes https://github.com/pytorch/pytorch/issues/118129
Suppressions automatically added with
```
import re
with open("error_file.txt", "r") as f:
errors = f.readlines()
error_lines = {}
for error in errors:
match = re.match(r"(.*):(\d+):\d+: error:.*\[(.*)\]", error)
if match:
file_path, line_number, error_type = match.groups()
if file_path not in error_lines:
error_lines[file_path] = {}
error_lines[file_path][int(line_number)] = error_type
for file_path, lines in error_lines.items():
with open(file_path, "r") as f:
code = f.readlines()
for line_number, error_type in sorted(lines.items(), key=lambda x: x[0], reverse=True):
code[line_number - 1] = code[line_number - 1].rstrip() + f" # type: ignore[{error_type}]\n"
with open(file_path, "w") as f:
f.writelines(code)
```
Signed-off-by: Edward Z. Yang <ezyang@meta.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/118533
Approved by: https://github.com/Skylion007, https://github.com/zou3519
This replaces a bunch of unnecessary lambdas with the operator package. This is semantically equivalent, but the operator package is faster, and arguably more readable. When the FURB rules are taken out of preview, I will enable it as a ruff check.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/116027
Approved by: https://github.com/malfet
* Enable PERF402. Makes code more efficient and succinct by removing useless list copies that could be accomplished either via a list constructor or extend call. All test cases have noqa added since performance is not as sensitive in that folder.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/115505
Approved by: https://github.com/malfet
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
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/70621
Pytorch doesn't have support for qint16 yet. Add an option to handle qint16 via int16 & qint32 data types.
* For qint16 tensors in NNAPI, the user sends a qint32 tensor. We convert the qint32 to int16 for the converter and set the zero point and scale for nnapi
* inputs to the model have to have fixed scale and zero point and are only supported for testing
* Added a flag use_int16_for_qint16 which will be used maintain backwards compatibility in the converter when true qint16 is supported in PyTorch
ghstack-source-id: 146507483
Test Plan: pytest test/test_nnapi.py
Reviewed By: dreiss
Differential Revision: D33285124
fbshipit-source-id: b6376fa1bb18a0b9f6a18c545f600222b650cb66
Summary:
NNAPI converter failed with 1 const value and one tensor earlier
Code suggestions from dreiss
Test Plan:
pytest test/test_nnapi.py::TestNNAPI::test_pointwise_binary
Imported from OSS
Reviewed By: anshuljain1
Differential Revision: D28893881
fbshipit-source-id: 59240373fb03c6fdafa4cb2fa4d8408dd20092f6
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61796
We can easily handle nnapi conversion for nhwc inputs
that have 1 channel or H & W are 1
Test Plan:
pytest test/test_nnapi.py::TestNNAPI::test_flatten
Imported from OSS
Reviewed By: saketh-are
Differential Revision: D29827735
fbshipit-source-id: 65dee4b42fceef1b032bf5dd1c4cc6e020d01e14
Summary: As title
Test Plan: pytest test/test_nnapi.py::TestNNAPI::test_cat
Reviewed By: anshuljain1
Differential Revision: D29480747
fbshipit-source-id: 161803054ff1a4c2c750fc30a5f0fc6d8a24b2c9
Summary:
Same as title
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61021
Test Plan: pytest test/test_nnapi.py::TestNNAPI
Reviewed By: anshuljain1
Differential Revision: D29480746
fbshipit-source-id: 7217c8f3a811db8c3c373f3e7ca31caf9502ef22
Summary:
Add support for aten::slice op in the NNAPI model converter
* If start = 0; end = max -> identity
* Flexible shapes can be passed through
* Flexible shapes can't be sliced over
Pull Request resolved: https://github.com/pytorch/pytorch/pull/59364
Test Plan: pytest test/test_nnapi.py::TestNNAPI::test_slice
Reviewed By: anshuljain1
Differential Revision: D28881039
fbshipit-source-id: 3c1c630ff27b5bba6eda403d87570c61d43ae90e
Summary:
* Add support for aten::detach op in the NNAPI model converter as a no-op
* Also add flexible op support for add_pointwise_simple_unary_op
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58543
Test Plan: pytest test/test_nnapi.py::TestNNAPI::test_detatch
Reviewed By: anshuljain1
Differential Revision: D28531942
fbshipit-source-id: 4387dbbbadd8ce6b690841f3a903e68a380b849d
Summary:
Add support for aten::div op in the NNAPI model converter. Startup time
variable size support isn't supported as shapes go as inputs to NNAPI op
Runtime variable size support to supported soon
Pull Request resolved: https://github.com/pytorch/pytorch/pull/60885
Test Plan: pytest test/test_nnapi.py::TestNNAPI::test_flatten
Reviewed By: anshuljain1
Differential Revision: D29451725
fbshipit-source-id: 8902745f7758c8cc88ad4b4ce02b8301ff894bd4
Summary:
Add support for aten::div op in the NNAPI model converter. Add variable
size input test as well.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58541
Test Plan: pytest test/test_nnapi.py::TestNNAPI::test_div
Reviewed By: anshuljain1
Differential Revision: D28531943
fbshipit-source-id: e96342146f6de216f7b88443618edfc54963747c
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58540
Add support for aten::to op in the NNAPI model converter for simple
cases like to("cpu"), to("gpu")
Test Plan: pytest test/test_nnapi.py::TestNNAPI::test_to
Reviewed By: anshuljain1
Differential Revision: D28531941
fbshipit-source-id: 0c934f7aceaff2669307c3426efe32046d8c44f3
Summary:
Add support for aten::softmax op in the NNAPI model converter with
flexible size
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58539
Test Plan: pytest test/test_nnapi.py::TestNNAPI::test_softmax
Reviewed By: anshuljain1
Differential Revision: D28531946
fbshipit-source-id: 8633f3e3f7f52795f9866ff16ad0867ea36a19e8
Summary:
Add support for aten::avgpool2d op in the NNAPI model converter with var
size support
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58538
Test Plan: pytest test/test_nnapi.py::TestNNAPI::test_avgpool2d
Reviewed By: anshuljain1
Differential Revision: D28531944
fbshipit-source-id: 43ff8c9389365698c282f204042b49c7ec84d824
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/57563
Add flexible size support for upsample_nearest2d op in nnapi model conversion
Test Plan:
pytest test/test_nnapi.py
Imported from OSS
Reviewed By: dreiss
Differential Revision: D28200847
fbshipit-source-id: 901fe3f6e68e4c16ece730f3ffa68dc88c6ed6c3
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/57562
Add flexible size support for qadd op in nnapi model conversion
Test Plan:
pytest test/test_nnapi.py
Imported from OSS
Reviewed By: dreiss
Differential Revision: D28200849
fbshipit-source-id: d5b2ea8e9eb8ae405ff2c960f7549cef60bc0991
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/57561
Add flexible size support for conv2d op in nnapi model conversion
Test Plan:
pytest test/test_nnapi.py
Imported from OSS
Reviewed By: dreiss
Differential Revision: D28200848
fbshipit-source-id: d94ccf48a3d8453aa8e96c7cac02948c4cd870cc
Summary:
Fixes https://github.com/pytorch/pytorch/issues/48141
~Mypy is complaining about a missing arg in a function call.~
```bash
torch/backends/_nnapi/serializer.py:806: error: Too few arguments for "_do_add_binary" [call-arg]
Found 1 error in 1 file (checked 1140 source files)
```
9392137dbe/torch/backends/_nnapi/serializer.py (L804-L806)
~dreiss, would you mind take a look when you have some cycles to spare and see what would be the appropriated value for `fuse_code` here? Thanks :)~
Edit: https://github.com/pytorch/pytorch/issues/48925 got merged a couple of days ago. The blocking part is now unblocked, and I just pushed the changes to make mypy happy again. This PR is ready for review.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/48142
Reviewed By: ezyang
Differential Revision: D28006249
Pulled By: walterddr
fbshipit-source-id: 5e43eeba7143512a549efaad31541f86718add7c
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/54701
We need NNAPI models to support inputs (and, by extension, intermediate
values and outputs) whose shape is only determined at load time. For
example, a vision models input shape might be dependent on the aspect
ratio of the device camera. While NNAPI has full support for variable
shapes (by setting components of the operand shape to 0), the guidance
we have received is that vendor-provided drivers for real hardware are
not able to support this efficiently. Therefore, we take a hybrid
approach where shapes are calculated at model load time to
semi-dynamically construct our NNAPI model. While this doesn't let us
have truly dynamic input shapes, it does allow us to ensure that the
vendor driver only sees fixed shapes, so we get maximum performance.
In this initial commit, only PReLU supports dynamic shapes. Additional
operators will be converted in separate diffs.
- In order to convert a flexible-shape model, the user supplies inputs
with shapes containing dimensions of size 0 for the flexible
dimensions.
- During conversion, we generate code to compute the shapes of all
intermediates and outputs as a function of the input shapes.
- We no longer run the input model to produce the output templates.
Instead, we generate code to return properly-sized templates, given
the input shapes.
- All of this generated code goes into a "ShapeComputeModule" that is
used by the NnapiModule during initialization.
- The ShapeComputeModule mutates the serialized model to fill in the
computed sizes for each operand. This requires us to change the dtype
for the serialized model to int32, but this should be fine because
everything in it is already 4-byte aligned.
- NnapiInitWrapper no longer exists. Instead, initialization is
performed on the first run, based on the real arguments. We plan to
provide an API for doing eager initialization.
- Unit test updated to allow separate arguments to be given for trace,
conversion, and inference. A flexible-shape test case was added for
PReLU.
Test Plan: Unit test
Reviewed By: axitkhurana
Differential Revision: D27536796
Pulled By: dreiss
fbshipit-source-id: 105585f247987b1e6ec6946a6fe44401237cb0a0
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/54700
This is an internal method just to make it more clear what
len(self.operands) is doing.
Test Plan: Unit test
Reviewed By: axitkhurana
Differential Revision: D27536794
Pulled By: dreiss
fbshipit-source-id: 678cee8a47df6757dd2e6feabf2560fd82d32e26
