pool = nn.MaxPool1d(kernel_size\, stride=None\, padding=0\, dilation=1\, return_indices=False\, ceil_mode=False),MaxPool2d(kernel_size\, stride=None\, padding=0\, dilation=1\, return_indices=False\, ceil_mode=False),MaxPool3d(kernel_size\, stride=None\, padding=0\, dilation=1\, return_indices=False\, ceil_mode=False),MaxUnpool1d(kernel_size\, stride=None\, padding=0),MaxUnpool2d(kernel_size\, stride=None\, padding=0),MaxUnpool3d(kernel_size\, stride=None\, padding=0),AvgPool1d(kernel_size\, stride=None\, padding=0\, ceil_mode=False\, count_include_pad=True),AvgPool2d(kernel_size\, stride=None\, padding=0\, ceil_mode=False\, count_include_pad=True),AvgPool3d(kernel_size\, stride=None\, padding=0\, ceil_mode=False\, count_include_pad=True),FractionalMaxPool2d(kernel_size\, output_size=None\, output_ratio=None\, return_indices=False\, random_samples=None),LPPool1d(norm_type\, kernel_size\, stride=None\, ceil_mode=False),LPPool2d(norm_type\, kernel_size\, stride=None\, ceil_mode=False),AdaptiveMaxPool1d(output_size\, return_indices=False),AdaptiveMaxPool2d(output_size\, return_indices=False),AdaptiveMaxPool3d(output_size\, return_indices=False),AdaptiveAvgPool1d(output_size),AdaptiveAvgPool2d(output_size),AdaptiveAvgPool3d(output_size)
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      Pooling Layer

      Pytorch Public Recipes

      Library: pytorch

      Shortcut: pytorch.layer.pooling

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