mirror of
https://github.com/pytorch/pytorch.git
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29ea08616b
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18579 ghimport-source-id: 65124c95e49423de4ad1008c65e75057fea09b94 Differential Revision: D14778507 Pulled By: ezyang fbshipit-source-id: 1e4bb79f4800a116ce8fb7af2fefbd34da8d102c
91 lines
3.5 KiB
Python
91 lines
3.5 KiB
Python
import torch
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import unittest
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import os
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import re
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import textwrap
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path = os.path.dirname(os.path.realpath(__file__))
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rstpath = os.path.join(path, '../docs/source/')
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pypath = os.path.join(path, '../torch/_torch_docs.py')
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r1 = re.compile(r'\.\. autofunction:: (\w*)')
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r2 = re.compile(r'\.\. auto(?:method|attribute):: (\w*)')
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class TestDocCoverage(unittest.TestCase):
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@staticmethod
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def parse_rst(filename, regex):
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filename = os.path.join(rstpath, filename)
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ret = set()
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with open(filename, 'r') as f:
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lines = f.readlines()
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for l in lines:
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l = l.strip()
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name = regex.findall(l)
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if name:
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ret.add(name[0])
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return ret
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def test_torch(self):
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# TODO: The algorithm here is kind of unsound; we don't assume
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# every identifier in torch.rst lives in torch by virtue of
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# where it lives; instead, it lives in torch because at the
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# beginning of the file we specified automodule. This means
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# that this script can get confused if you have, e.g., multiple
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# automodule directives in the torch file. "Don't do that."
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# (Or fix this to properly handle that case.)
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# get symbols documented in torch.rst
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in_rst = self.parse_rst('torch.rst', r1)
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# get symbols in functional.py and _torch_docs.py
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whitelist = {
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# below are some jit functions
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'wait', 'fork', 'parse_type_comment', 'import_ir_module',
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'import_ir_module_from_buffer', 'merge_type_from_type_comment',
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'parse_ir',
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# below are symbols mistakely binded to torch.*, but should
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# go to torch.nn.functional.* instead
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'avg_pool1d', 'conv_transpose2d', 'conv_transpose1d', 'conv3d',
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'relu_', 'pixel_shuffle', 'conv2d', 'selu_', 'celu_', 'threshold_',
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'cosine_similarity', 'rrelu_', 'conv_transpose3d', 'conv1d', 'pdist',
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'adaptive_avg_pool1d', 'conv_tbc'
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}
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has_docstring = set(
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a for a in dir(torch)
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if getattr(torch, a).__doc__ and not a.startswith('_') and
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'function' in type(getattr(torch, a)).__name__)
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self.assertEqual(
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has_docstring & whitelist, whitelist,
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textwrap.dedent('''
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The whitelist in test_docs_coverage.py contains something
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that don't have docstring or not in torch.*. If you just
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removed something from torch.*, please remove it from whiltelist
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in test_docs_coverage.py'''))
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has_docstring -= whitelist
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# assert they are equal
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self.assertEqual(
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has_docstring, in_rst,
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textwrap.dedent('''
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List of functions documented in torch.rst and in python are different.
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Do you forget to add new thing to torch.rst, or whitelist things you
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don't want to document?''')
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)
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def test_tensor(self):
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in_rst = self.parse_rst('tensors.rst', r2)
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classes = [torch.FloatTensor, torch.LongTensor, torch.ByteTensor]
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has_docstring = set(x for c in classes for x in dir(c) if not x.startswith('_') and getattr(c, x).__doc__)
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self.assertEqual(
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has_docstring, in_rst,
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textwrap.dedent('''
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List of tensor methods documented in tensor.rst and in python are
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different. Do you forget to add new thing to tensor.rst, or whitelist
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things you don't want to document?''')
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)
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if __name__ == '__main__':
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unittest.main()
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