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https://github.com/pytorch/pytorch.git
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e6779d4357
Summary:
I've written custom parsers and emitters for everything from docstrings to classes and functions. However, I recently came across an issue when I was parsing/generating from the TensorFlow codebase: inconsistent use of `Args:` and `Arguments:` in its docstrings.
```sh
(pytorch#c348fae)$ for name in 'Args:' 'Arguments:'; do
printf '%-10s %04d\n' "$name" "$(rg -IFtpy --count-matches "$name" | paste -s -d+ -- | bc)"; done
Args: 1095
Arguments: 0336
```
It is easy enough to extend my parsers to support both variants, however it looks like `Arguments:` is wrong anyway, as per:
- https://google.github.io/styleguide/pyguide.html#doc-function-args @ [`ddccc0f`](https://github.com/google/styleguide/blob/ddccc0f/pyguide.md)
- https://chromium.googlesource.com/chromiumos/docs/+/master/styleguide/python.md#describing-arguments-in-docstrings @ [`9fc0fc0`](https://chromium.googlesource.com/chromiumos/docs/+/9fc0fc0/styleguide/python.md)
- https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html @ [`c0ae8e3`](https://github.com/sphinx-contrib/napoleon/blob/c0ae8e3/docs/source/example_google.rst)
Therefore, only `Args:` is valid. This PR replaces them throughout the codebase.
PS: For related PRs, see tensorflow/tensorflow/pull/45420
PPS: The trackbacks automatically appearing below are sending the same changes to other repositories in the [PyTorch](https://github.com/pytorch) organisation.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49736
Reviewed By: albanD
Differential Revision: D25710534
Pulled By: soumith
fbshipit-source-id: 61e8ff01abb433e9f78185c2d1d0cbd7c22c1619
51 lines
1.5 KiB
Python
51 lines
1.5 KiB
Python
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from caffe2.python import schema
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from caffe2.python.layers.layers import (
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get_categorical_limit,
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ModelLayer,
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IdList
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)
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import numpy as np
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class MergeIdLists(ModelLayer):
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"""Merge multiple ID_LISTs into a single ID_LIST
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Args:
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model: A layer model instance
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input_record: Tuple (Struct) of ID_LIST features to be
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merged
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Returns:
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the merged ID_LIST feature
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"""
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def __init__(self, model, input_record, name='merged'):
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super(MergeIdLists, self).__init__(model, name, input_record)
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assert all(schema.equal_schemas(x, IdList) for x in input_record), \
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"Inputs to MergeIdLists should all be IdLists."
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assert all(record.items.metadata is not None
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for record in self.input_record), \
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"Features without metadata are not supported"
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merge_dim = max(get_categorical_limit(record)
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for record in self.input_record)
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assert merge_dim is not None, "Unbounded features are not supported"
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self.output_schema = schema.NewRecord(
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model.net, schema.List(
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schema.Scalar(
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np.int64,
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blob=model.net.NextBlob(name),
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metadata=schema.Metadata(categorical_limit=merge_dim)
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)))
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def add_ops(self, net):
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return net.MergeIdLists(self.input_record.field_blobs(),
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self.output_schema.field_blobs())
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