nn.AdaptiveMaxPool2d
时间: 2023-10-18 11:05:28 浏览: 41
nn.AdaptiveMaxPool2d is a PyTorch module that performs adaptive max pooling operation over the input tensor. Adaptive max pooling is a type of pooling operation where the size of the output tensor is flexible and depends on the size of the input tensor.
The nn.AdaptiveMaxPool2d module takes as input a 4D tensor of shape (batch_size, channels, height, width) and returns a 4D tensor of shape (batch_size, channels, output_height, output_width), where the output_height and output_width are determined by the specified output size.
The module works by dividing the input tensor into rectangular regions and taking the maximum value of each region. The size of the regions is determined by the output size specified in the constructor.
For example, if the input tensor has shape (1, 64, 32, 32) and the output size is (16, 16), then the output tensor will have shape (1, 64, 16, 16). The input tensor is divided into 16 x 16 regions and the maximum value of each region is taken to form the output tensor.
The nn.AdaptiveMaxPool2d module is useful when the input tensor has variable size and the output tensor needs to have a fixed size. It can also be used to reduce the spatial dimensions of the input tensor while retaining the most important features.