mirror of
https://github.com/wassname/pytorch-for-numpy-users.git
synced 2026-06-27 16:10:21 +08:00
Kentaro Wada
60 lines
1.7 KiB
Python
Executable File
60 lines
1.7 KiB
Python
Executable File
#!/usr/bin/env python
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import collections
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import os.path as osp
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import tabulate
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import yaml
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TEMPLATE = '''\
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# PyTorch for Numpy users.
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[](https://travis-ci.com/wkentaro/pytorch-for-numpy-users)
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[PyTorch](https://github.com/pytorch/pytorch.git) version of [_Torch for Numpy users_](https://github.com/torch/torch7/wiki/Torch-for-Numpy-users).
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{contents}
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'''
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here = osp.dirname(osp.abspath(__file__))
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def get_section(title, data, h=2):
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if not isinstance(data, list):
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content = '%s %s\n\n' % ('#' * h, title.capitalize())
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for sub_title, sub_data in data.items():
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content += get_section(sub_title, sub_data, h=h+1)
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return content
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headers = ['Numpy', 'PyTorch']
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rows = []
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for d in data:
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numpy = '`' + d['numpy'] + '`' if d['numpy'] is not None else ''
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pytorch = '`' + d['pytorch'] + '`' if d['pytorch'] is not None else ''
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rows.append([numpy, pytorch])
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content = '%s %s\n\n' % ('#' * h, title.capitalize())
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content += tabulate.tabulate(rows, headers=headers, tablefmt='pipe')
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content += '\n\n'
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return content
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def get_contents():
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# keep order in yaml file
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yaml.add_constructor(yaml.resolver.BaseResolver.DEFAULT_MAPPING_TAG,
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lambda loader, node: \
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collections.OrderedDict(loader.construct_pairs(node)))
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yaml_file = osp.join(here, 'conversions.yaml')
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data = yaml.load(open(yaml_file))
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contents = []
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for title, data in data.items():
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section = get_section(title, data)
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contents.append(section)
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return '\n'.join(contents)
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print(TEMPLATE.format(contents=get_contents()))
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