PyTorch的自适应池化Adaptive Pooling
简介 自适应池化Adaptive Pooling是PyTorch含有的一种池化层,在PyTorch的中有六种形式: 自适应最大池化Adaptive Max Pooling: torch.nn.AdaptiveMaxPool1d(output_size) torch.nn.AdaptiveMaxPool2d(output_size) torch.nn.AdaptiveMaxPool3d(output_size) 自适应平均池化Adaptive Average Pooling: torch.nn.AdaptiveAvgPool1d(output_size) torch.nn.AdaptiveAvgPool2d(output_size) torch.nn.AdaptiveAvgPool3d(output_size) 具体可见 官方文档 。 官方给出的例子: >>> # target output size of 5x7 >>> m = nn.AdaptiveMaxPool2d((5,7)) >>> input = torch.randn(1, 64, 8, 9) >>> output = m(input) >>> output.size() torch.Size([1, 64, 5, 7]) >>> # target output size of 7x7 (square) >>> m =