pytorch:分批训练

在这里插入代码import torch
import torch.utils.data as Data#批处理模块

torch.manual_seed(1)    # reproducible

BATCH_SIZE = 5#每小批5个
# 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(#使训练分批
    dataset=torch_dataset,      # torch TensorDataset format
    batch_size=BATCH_SIZE,      # mini batch size
    shuffle=True,               # 训练时随机打乱数据再抽样
    num_workers=2,              # subprocesses for loading data
)


def show_batch():
    for epoch in range(3):   # 训练整个数据集三次（每次都是拆分成小组训练）
        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()片

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