Fixes#112633
Fixed errors relating to pydocstyle in the following files. The remaining errors are not covered in this issue. `torch/utils/dlpack.py` was not modified as the errors are relating to the function signature in the first line in the docstring which must be maintained as is for proper Sphinx interpretation.
```python
def from_dlpack(ext_tensor: Any) -> 'torch.Tensor':
"""from_dlpack(ext_tensor) -> Tensor
.....
"""
```
pydocstyle torch/utils/_contextlib.py --count
before: 4
after: 0
pydocstyle torch/backends/mps/__init__.py --count
before: 8
after: 1
**remaining errors**
```
torch/backends/mps/__init__.py:1 at module level:
D104: Missing docstring in public package
```
pydocstyle torch/backends/xeon/run_cpu.py --count
before: 13
after: 1
**remaining errors**
```
torch/backends/xeon/run_cpu.py:864 in public function `main`:
D103: Missing docstring in public function
```
pydocstyle torch/backends/cpu/__init__.py --count
before: 2
after: 1
**remaining errors**
```
torch/backends/cpu/__init__.py:1 at module level:
D104: Missing docstring in public package
```
pydocstyle torch/utils/cpp_backtrace.py --count
before: 4
after: 1
**remaining errors**
```
torch/utils/cpp_backtrace.py:1 at module level:
D100: Missing docstring in public module
```
pydocstyle torch/utils/bundled_inputs.py --count
before: 8
after: 1
**remaining errors**
```
torch/utils/bundled_inputs.py:1 at module level:
D100: Missing docstring in public module
```
pydocstyle torch/utils/file_baton.py --count
before: 8
after: 1
**remaining errors**
```
torch/utils/file_baton.py:1 at module level:
D100: Missing docstring in public module
```
pydocstyle torch/utils/mobile_optimizer.py --count
before: 6
after: 1
**remaining errors**
```
torch/utils/mobile_optimizer.py:8 in public class `LintCode`:
D101: Missing docstring in public class
```
pydocstyle torch/backends/opt_einsum/__init__.py --count
before: 7
after: 5
**remaining errors**
```
torch/backends/opt_einsum/__init__.py:1 at module level:
D104: Missing docstring in public package
torch/backends/opt_einsum/__init__.py:67 in public function `set_flags`:
D103: Missing docstring in public function
torch/backends/opt_einsum/__init__.py:77 in public function `flags`:
D103: Missing docstring in public function
torch/backends/opt_einsum/__init__.py:93 in public class `OptEinsumModule`:
D101: Missing docstring in public class
torch/backends/opt_einsum/__init__.py:94 in public method `__init__`:
D107: Missing docstring in __init__
```
pydocstyle torch/utils/_device.py --count
before: 9
after: 6
**remaining errors**
```
torch/utils/_device.py:58 in public class `DeviceContext`:
D101: Missing docstring in public class
torch/utils/_device.py:59 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/_device.py:62 in public method `__enter__`:
D105: Missing docstring in magic method
torch/utils/_device.py:68 in public method `__exit__`:
D105: Missing docstring in magic method
torch/utils/_device.py:73 in public method `__torch_function__`:
D105: Missing docstring in magic method
torch/utils/_device.py:80 in public function `device_decorator`:
D103: Missing docstring in public function
```
pydocstyle torch/utils/_freeze.py --count
before: 15
after: 7
**remaining errors**
```
torch/utils/_freeze.py:77 in public function `indent_msg`:
D103: Missing docstring in public function
torch/utils/_freeze.py:89 in public class `FrozenModule`:
D101: Missing docstring in public class
torch/utils/_freeze.py:100 in public class `Freezer`:
D101: Missing docstring in public class
torch/utils/_freeze.py:101 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/_freeze.py:106 in public method `msg`:
D102: Missing docstring in public method
torch/utils/_freeze.py:185 in public method `get_module_qualname`:
D102: Missing docstring in public method
torch/utils/_freeze.py:206 in public method `compile_string`:
D102: Missing docstring in public method
```
pydocstyle torch/utils/throughput_benchmark.py --count
before: 25
after: 8
**remaining errors**
```
torch/utils/throughput_benchmark.py:1 at module level:
D100: Missing docstring in public module
torch/utils/throughput_benchmark.py:27 in public class `ExecutionStats`:
D101: Missing docstring in public class
torch/utils/throughput_benchmark.py:28 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/throughput_benchmark.py:33 in public method `latency_avg_ms`:
D102: Missing docstring in public method
torch/utils/throughput_benchmark.py:37 in public method `num_iters`:
D102: Missing docstring in public method
torch/utils/throughput_benchmark.py:46 in public method `total_time_seconds`:
D102: Missing docstring in public method
torch/utils/throughput_benchmark.py:50 in public method `__str__`:
D105: Missing docstring in magic method
torch/utils/throughput_benchmark.py:94 in public method `__init__`:
D107: Missing docstring in __init__
```
pydocstyle torch/utils/hooks.py --count
before: 14
after: 11
**remaining errors**
```
torch/utils/hooks.py:1 at module level:
D100: Missing docstring in public module
torch/utils/hooks.py:23 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/hooks.py:34 in public method `remove`:
D102: Missing docstring in public method
torch/utils/hooks.py:44 in public method `__getstate__`:
D105: Missing docstring in magic method
torch/utils/hooks.py:50 in public method `__setstate__`:
D105: Missing docstring in magic method
torch/utils/hooks.py:64 in public method `__enter__`:
D105: Missing docstring in magic method
torch/utils/hooks.py:67 in public method `__exit__`:
D105: Missing docstring in magic method
torch/utils/hooks.py:82 in public function `warn_if_has_hooks`:
D103: Missing docstring in public function
torch/utils/hooks.py:103 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/hooks.py:188 in public method `setup_input_hook`:
D102: Missing docstring in public method
torch/utils/hooks.py:197 in public method `setup_output_hook`:
D102: Missing docstring in public method
```
pydocstyle torch/utils/_traceback.py --count
before: 19
after: 14
**remaining errors**
```
torch/utils/_traceback.py:47 in public function `report_compile_source_on_error`:
D103: Missing docstring in public function
torch/utils/_traceback.py:160 in public class `CapturedTraceback`:
D101: Missing docstring in public class
torch/utils/_traceback.py:163 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/_traceback.py:167 in public method `cleanup`:
D102: Missing docstring in public method
torch/utils/_traceback.py:170 in public method `summary`:
D102: Missing docstring in public method
torch/utils/_traceback.py:182 in public method `__getstate__`:
D105: Missing docstring in magic method
torch/utils/_traceback.py:190 in public method `extract`:
D205: 1 blank line required between summary line and description (found 0)
torch/utils/_traceback.py:190 in public method `extract`:
D400: First line should end with a period (not 't')
torch/utils/_traceback.py:213 in public method `format`:
D205: 1 blank line required between summary line and description (found 0)
torch/utils/_traceback.py:213 in public method `format`:
D400: First line should end with a period (not 'f')
torch/utils/_traceback.py:213 in public method `format`:
D401: First line should be in imperative mood (perhaps 'Format', not 'Formats')
torch/utils/_traceback.py:224 in public method `format_all`:
D200: One-line docstring should fit on one line with quotes (found 3)
torch/utils/_traceback.py:247 in private function `_extract_symbolized_tb`:
D205: 1 blank line required between summary line and description (found 0)
torch/utils/_traceback.py:247 in private function `_extract_symbolized_tb`:
D400: First line should end with a period (not 'f')
```
pydocstyle torch/utils/mkldnn.py --count
before: 28
after: 26
**remaining errors**
```
torch/utils/mkldnn.py:1 at module level:
D100: Missing docstring in public module
torch/utils/mkldnn.py:4 in public class `MkldnnLinear`:
D101: Missing docstring in public class
torch/utils/mkldnn.py:5 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/mkldnn.py:19 in public method `__getstate__`:
D105: Missing docstring in magic method
torch/utils/mkldnn.py:23 in public method `__setstate__`:
D105: Missing docstring in magic method
torch/utils/mkldnn.py:29 in public method `forward`:
D102: Missing docstring in public method
torch/utils/mkldnn.py:75 in public class `MkldnnConv1d`:
D101: Missing docstring in public class
torch/utils/mkldnn.py:76 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/mkldnn.py:82 in public method `__setstate__`:
D105: Missing docstring in magic method
torch/utils/mkldnn.py:88 in public class `MkldnnConv2d`:
D101: Missing docstring in public class
torch/utils/mkldnn.py:89 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/mkldnn.py:100 in public method `__setstate__`:
D105: Missing docstring in magic method
torch/utils/mkldnn.py:110 in public class `MkldnnConv3d`:
D101: Missing docstring in public class
torch/utils/mkldnn.py:111 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/mkldnn.py:122 in public method `__setstate__`:
D105: Missing docstring in magic method
torch/utils/mkldnn.py:133 in public class `MkldnnBatchNorm`:
D101: Missing docstring in public class
torch/utils/mkldnn.py:136 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/mkldnn.py:155 in public method `__getstate__`:
D105: Missing docstring in magic method
torch/utils/mkldnn.py:163 in public method `__setstate__`:
D105: Missing docstring in magic method
torch/utils/mkldnn.py:171 in public method `forward`:
D102: Missing docstring in public method
torch/utils/mkldnn.py:184 in public class `MkldnnPrelu`:
D101: Missing docstring in public class
torch/utils/mkldnn.py:185 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/mkldnn.py:190 in public method `__getstate__`:
D105: Missing docstring in magic method
torch/utils/mkldnn.py:194 in public method `__setstate__`:
D105: Missing docstring in magic method
torch/utils/mkldnn.py:199 in public method `forward`:
D102: Missing docstring in public method
torch/utils/mkldnn.py:205 in public function `to_mkldnn`:
D103: Missing docstring in public function
```
pydocstyle torch/utils/weak.py --count
before: 32
after: 30
**remaining errors**
```
torch/utils/weak.py:1 at module level:
D100: Missing docstring in public module
torch/utils/weak.py:42 in public class `WeakIdRef`:
D101: Missing docstring in public class
torch/utils/weak.py:45 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/weak.py:54 in public method `__call__`:
D102: Missing docstring in public method
torch/utils/weak.py:61 in public method `__hash__`:
D105: Missing docstring in magic method
torch/utils/weak.py:64 in public method `__eq__`:
D105: Missing docstring in magic method
torch/utils/weak.py:84 in public class `WeakIdKeyDictionary`:
D101: Missing docstring in public class
torch/utils/weak.py:87 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/weak.py:131 in public method `__delitem__`:
D105: Missing docstring in magic method
torch/utils/weak.py:135 in public method `__getitem__`:
D105: Missing docstring in magic method
torch/utils/weak.py:138 in public method `__len__`:
D105: Missing docstring in magic method
torch/utils/weak.py:145 in public method `__repr__`:
D105: Missing docstring in magic method
torch/utils/weak.py:148 in public method `__setitem__`:
D105: Missing docstring in magic method
torch/utils/weak.py:151 in public method `copy`:
D102: Missing docstring in public method
torch/utils/weak.py:162 in public method `__deepcopy__`:
D105: Missing docstring in magic method
torch/utils/weak.py:172 in public method `get`:
D102: Missing docstring in public method
torch/utils/weak.py:175 in public method `__contains__`:
D105: Missing docstring in magic method
torch/utils/weak.py:182 in public method `items`:
D102: Missing docstring in public method
torch/utils/weak.py:189 in public method `keys`:
D102: Missing docstring in public method
torch/utils/weak.py:198 in public method `values`:
D102: Missing docstring in public method
torch/utils/weak.py:216 in public method `popitem`:
D102: Missing docstring in public method
torch/utils/weak.py:224 in public method `pop`:
D102: Missing docstring in public method
torch/utils/weak.py:228 in public method `setdefault`:
D102: Missing docstring in public method
torch/utils/weak.py:231 in public method `update`:
D102: Missing docstring in public method
torch/utils/weak.py:241 in public method `__ior__`:
D105: Missing docstring in magic method
torch/utils/weak.py:245 in public method `__or__`:
D105: Missing docstring in magic method
torch/utils/weak.py:252 in public method `__ror__`:
D105: Missing docstring in magic method
torch/utils/weak.py:262 in public method `__eq__`:
D105: Missing docstring in magic method
torch/utils/weak.py:276 in public method `__init__`:
D107: Missing docstring in __init__
torch/utils/weak.py:280 in public method `__call__`:
D102: Missing docstring in public method
```
@mikaylagawarecki @jbschlosser @svekars
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113311
Approved by: https://github.com/ezyang
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
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/36282
The reason to do this explicitly in the tool is that we don't want to capture warmup in profiling (as well as input cloning). So instead we make the benchmarking code explicitly aware of the profiler.
Example output:
```
I0408 16:06:40.300040 85516 throughput_benchmark-inl.h:106] Using Autograd profiler. Trace will be saved to /tmp/tmpt0gsz85y
I0408 16:06:40.302232 85516 throughput_benchmark-inl.h:111] Starting threads
I0408 16:06:40.302258 85524 throughput_benchmark-inl.h:78] Starting forward thread 1
I0408 16:06:40.302259 85525 throughput_benchmark-inl.h:78] Starting forward thread 2
I0408 16:06:40.302261 85523 throughput_benchmark-inl.h:78] Starting forward thread 0
I0408 16:06:40.302259 85526 throughput_benchmark-inl.h:78] Starting forward thread 3
I0408 16:06:40.412879 85525 throughput_benchmark-inl.h:88] Shutting down forward thread 2. Total number of finished threads: 1
I0408 16:06:40.412971 85523 throughput_benchmark-inl.h:88] Shutting down forward thread 0. Total number of finished threads: 2
I0408 16:06:40.412989 85526 throughput_benchmark-inl.h:88] Shutting down forward thread 3. Total number of finished threads: 3
I0408 16:06:40.413033 85524 throughput_benchmark-inl.h:88] Shutting down forward thread 1. Total number of finished threads: 4
I0408 16:06:40.413056 85516 throughput_benchmark-inl.h:123] Finished benchmark
Average latency per example: 443.256us
Total number of iterations: 1000
Total number of iterations per second (across all threads): 9024.12
Total time: 110.814ms
```
Test Plan: Imported from OSS
Differential Revision: D20987125
Pulled By: ezyang
fbshipit-source-id: 1f8980c3a5a0abdc268c7a16c99aa9ea868689eb
Summary:
The `assert False` lint error has been causing CI to fail:
./torch/utils/throughput_benchmark.py:14:13: B011 Do not call assert False since python -O removes these calls. Instead callers should raise AssertionError().
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22424
Differential Revision: D16083464
Pulled By: bddppq
fbshipit-source-id: 6d96e36c8fcbb391d071b75fe79c22d526c1ba3c
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22293
Just wrapping C class with nicer python interface which now
ust print dirrectly to get all the data. Later we can add various
visualizations there
Differential Revision: D16023999
fbshipit-source-id: 8436e37e36965821a690035617784dcdc352dcd1
Summary:
This is useful for measuring inference performance of your
models. This is a very basic benchmark for now. We don't support
batching on the benchmark side, no inter and intra op parallelizm is
supported yet, just caller based parallelizm.
Main phylosophy here is that user should be able to provide inputs
from python and just stack them within the benchmark. API should be
exactly the same as passing inputs to module.forward.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20766
Test Plan: Added a new unit test
Differential Revision: D15435461
Pulled By: salexspb
fbshipit-source-id: db08829dc3f4398bb1d8aa16cc4a58b6c72f16c6
