pytorch之 batch_train

 import torch
 import torch.utils.data as Data
 
 torch.manual_seed(1)    # reproducible
 
 BATCH_SIZE = 5
 # BATCH_SIZE = 8
 
 x = torch.linspace(1, 10, 10)       # this is x data (torch tensor)
 y = torch.linspace(10, 1, 10)       # this is y data (torch tensor)
 
 torch_dataset = Data.TensorDataset(x, y)
 loader = Data.DataLoader(
     dataset=torch_dataset,      # torch TensorDataset format
     batch_size=BATCH_SIZE,      # mini batch size
     shuffle=True,               # random shuffle for training
     num_workers=2,              # subprocesses for loading data
 )
 
 def show_batch():
     for epoch in range(3):   # train entire dataset 3 times
         for step, (batch_x, batch_y) in enumerate(loader):  # for each training step
             # train your data...
             print('Epoch: ', epoch, '| Step: ', step, '| batch x: ',
                   batch_x.numpy(), '| batch y: ', batch_y.numpy())
 
 if __name__ == '__main__':
     show_batch()