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Add copyright pre-commit-hook (#1742)
* first commit * Add copyright pre-commit-hook
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import inspect | ||
import platform | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import torch | ||
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import mmcv | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
from .builder import RUNNER_BUILDERS, RUNNERS | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import onnx | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import warnings | ||
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import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
item1 = [1, 2] | ||
item2 = {'a': 0} | ||
item3 = True | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
item1 = [1, 2] | ||
item2 = {'a': 0} | ||
item3 = True | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
item1 = [1, 2] | ||
item2 = {'a': 0} | ||
item3 = True | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
_base_ = './base.py' | ||
item1 = [2, 3] | ||
item2 = {'a': 1} | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
_base_ = './base.py' | ||
item1 = {'a': 0, '_delete_': True} | ||
item2 = {'b': 0} |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
_base_ = './expected.py' | ||
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_deprecation_ = dict( | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
_base_ = './deprecated.py' |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
_base_ = './base.py' | ||
item3 = {'a': 1} |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
item1 = 'expected' |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
_base_ = './d.py' | ||
item4 = 'test_recursive_bases' |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
filename = 'reserved.py' |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
item1 = '{{fileBasename}}' | ||
item2 = '{{ fileDirname}}' | ||
item3 = 'abc_{{ fileBasenameNoExtension }}' |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
item1 = [1, 2] | ||
item2 = {'a': 0} | ||
item3 = True | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
_base_ = './i_base.py' | ||
item_cfg = {'b': 2} | ||
item6 = {'cfg': item_cfg} |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
_base_ = ['./l1.py', './l2.yaml', './l3.json', './l4.py'] | ||
item3 = False | ||
item4 = 'test' |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
item1 = [1, 2] |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
item5 = dict(a=0, b=1) | ||
item6 = [dict(a=0), dict(b=1)] | ||
item7 = dict(a=[0, 1, 2], b=dict(c=[3.1, 4.2, 5.3])) |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
_base_ = ['./l1.py', './l2.yaml', './l3.json', 'a.py'] | ||
item3 = False | ||
item4 = 'test' |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
test_item1 = [1, 2] | ||
bool_item2 = True | ||
str_item3 = 'test' | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
custom_imports = dict(imports=['r'], allow_failed_imports=False) |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import os | ||
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os.environ["TEST_VALUE"] = 'test' |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
item = [{'a': 0}, {'b': 0, 'c': 0}] |
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# Copyright (c) OpenMMLab. All rights reserved. | ||
#!/usr/bin/env python | ||
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import argparse | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import torch | ||
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from mmcv.cnn.bricks import Conv2dAdaptivePadding | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import warnings | ||
from unittest.mock import patch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import pytest | ||
import torch | ||
import torch.nn as nn | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import pytest | ||
import torch | ||
import torch.nn as nn | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import torch | ||
import torch.nn as nn | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import torch | ||
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from mmcv.cnn.bricks import GeneralizedAttention | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import torch | ||
from torch.nn.functional import relu6 | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import torch.nn as nn | ||
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import mmcv | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import pytest | ||
import torch | ||
import torch.nn as nn | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import os | ||
import platform | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import torch | ||
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from mmcv.cnn.bricks import Scale | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import torch | ||
import torch.nn.functional as F | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import copy | ||
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import pytest | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
from unittest.mock import patch | ||
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import pytest | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import os | ||
import os.path as osp | ||
import sys | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import torch | ||
import torch.nn.functional as F | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import copy | ||
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import numpy as np | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import torch | ||
from torch.autograd import gradcheck | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import torch | ||
import torch.nn as nn | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
""" | ||
CommandLine: | ||
pytest tests/test_corner_pool.py | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import os | ||
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import numpy as np | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
""" | ||
CommandLine: | ||
pytest tests/test_merge_cells.py | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import pytest | ||
import torch | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import os | ||
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import numpy | ||
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import pytest | ||
import torch | ||
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This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import pytest | ||
import torch | ||
|
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
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# Copyright (c) OpenMMLab. All rights reserved. | ||
import numpy as np | ||
import pytest | ||
import torch | ||
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