pytorch 在sequential中使用view来reshape的例子

import torch.nn as nnclass Reshape(nn.Module): def __init__(self, *args):  super(Reshape, self).__init__()  self.shape = args def forward(self, x):  # 如果数据集最后一个batch样本数量小于定义的batch_batch大小，会出现mismatch问题。可以自己修改下，如只传入后面的shape，然后通过x.szie(0)，来输入。  return x.view(self.shape)

class Reshape(nn.Module): def __init__(self, *args):  super(Reshape, self).__init__()  self.shape = args def forward(self, x):  return x.view((x.size(0),)+self.shape)