这篇教程pytorch 6 batch_train 批训练操作写得很实用，希望能帮到您。
看代码吧~import torchimport torch.utils.data as Datatorch.manual_seed(1) # reproducible# BATCH_SIZE = 5 BATCH_SIZE = 8 # 每次使用8个数据同时传入网路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=False, # 设置不随机打乱数据 random shuffle for training num_workers=2, # 使用两个进程提取数据，subprocesses for loading data)def show_batch(): for epoch in range(3): # 全部的数据使用3遍，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()BATCH_SIZE = 8 , 所有数据利用三次Epoch: 0 | Step: 0 | batch x: [1. 2. 3. 4. 5. 6. 7. 8.] | batch y: [10. 9. 8. 7. 6. 5. 4. 3.]Epoch: 0 | Step: 1 | batch x: [ 9. 10.] | batch y: [2. 1.]Epoch: 1 | Step: 0 | batch x: [1. 2. 3. 4. 5. 6. 7. 8.] | batch y: [10. 9. 8. 7. 6. 5. 4. 3.]Epoch: 1 | Step: 1 | batch x: [ 9. 10.] | batch y: [2. 1.]Epoch: 2 | Step: 0 | batch x: [1. 2. 3. 4. 5. 6. 7. 8.] | batch y: [10. 9. 8. 7. 6. 5. 4. 3.]Epoch: 2 | Step: 1 | batch x: [ 9. 10.] | batch y: [2. 1.] 补充：pytorch批训练bug 问题描述：在进行pytorch神经网络批训练的时候，有时会出现报错 TypeError: batch must contain tensors, numbers, dicts or lists; found <class 'torch.autograd.variable.Variable'>
解决办法：第一步：检查(重点！！！！！)： train_dataset = Data.TensorDataset(train_x, train_y) train_x，和train_y格式，要求是tensor类，我第一次出错就是因为传入的是variable 可以这样将数据变为tensor类： train_x = torch.FloatTensor(train_x) 第二步：train_loader = Data.DataLoader( dataset=train_dataset, batch_size=batch_size, shuffle=True ) 实例化一个DataLoader对象 第三步： for epoch in range(epochs): for step, (batch_x, batch_y) in enumerate(train_loader): batch_x, batch_y = Variable(batch_x), Variable(batch_y) 这样就可以批训练了 需要注意的是：train_loader输出的是tensor，在训练网络时，需要变成Variable 以上为个人经验，希望能给大家一个参考，也希望大家多多支持51zixue.net。
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