mirror of https://github.com/open-mmlab/mmcv.git
28 lines
900 B
Python
28 lines
900 B
Python
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import torch
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from mmcv.cnn.bricks import Conv2dAdaptivePadding
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def test_conv2d_samepadding():
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# test Conv2dAdaptivePadding with stride=1
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inputs = torch.rand((1, 3, 28, 28))
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conv = Conv2dAdaptivePadding(3, 3, kernel_size=3, stride=1)
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output = conv(inputs)
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assert output.shape == inputs.shape
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inputs = torch.rand((1, 3, 13, 13))
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conv = Conv2dAdaptivePadding(3, 3, kernel_size=3, stride=1)
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output = conv(inputs)
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assert output.shape == inputs.shape
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# test Conv2dAdaptivePadding with stride=2
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inputs = torch.rand((1, 3, 28, 28))
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conv = Conv2dAdaptivePadding(3, 3, kernel_size=3, stride=2)
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output = conv(inputs)
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assert output.shape == torch.Size([1, 3, 14, 14])
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inputs = torch.rand((1, 3, 13, 13))
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conv = Conv2dAdaptivePadding(3, 3, kernel_size=3, stride=2)
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output = conv(inputs)
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assert output.shape == torch.Size([1, 3, 7, 7])
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