PyTorch基本用法(八)——批训练

文章作者：Tyan
博客：noahsnail.com  |  CSDN  | 

本文主要是关于PyTorch的一些用法。

import torch
import torch.utils.data as Data
from torch.autograd import Variable

# 定义batch size
BATCH_SIZE = 5

# 定义数据
x = torch.linspace(1, 10, 10)
y = torch.linspace(10, 1, 10)

print x.numpy()
print y.numpy()

[  1.   2.   3.   4.   5.   6.   7.   8.   9.  10.]
[ 10.   9.   8.   7.   6.   5.   4.   3.   2.   1.]

# 定义数据库
dataset = Data.TensorDataset(data_tensor = x, target_tensor = y)

# 定义数据加载器
loader = Data.DataLoader(dataset = dataset, batch_size = BATCH_SIZE, shuffle = True, num_workers = 2)

# 训练过程
for epoch in xrange(5):
    for step, (batch_x, batch_y) in enumerate(loader):
        # 训练过程
        print 'Epoch: ', epoch, '| Step: ', step, '| batch x: ', batch_x.numpy(), '| betch y: ', batch_y.numpy()

Epoch:  0 | Step:  0 | batch x:  [ 7.  4.  8.  5.  2.] | betch y:  [ 4.  7.  3.  6.  9.]
Epoch:  0 | Step:  1 | batch x:  [ 10.   6.   3.   1.   9.] | betch y:  [  1.   5.   8.  10.   2.]
Epoch:  1 | Step:  0 | batch x:  [  6.   7.  10.   1.   3.] | betch y:  [  5.   4.   1.  10.   8.]
Epoch:  1 | Step:  1 | batch x:  [ 9.  4.  5.  8.  2.] | betch y:  [ 2.  7.  6.  3.  9.]
Epoch:  2 | Step:  0 | batch x:  [ 5.  4.  7.  3.  8.] | betch y:  [ 6.  7.  4.  8.  3.]
Epoch:  2 | Step:  1 | batch x:  [  6.   9.   2.  10.   1.] | betch y:  [  5.   2.   9.   1.  10.]
Epoch:  3 | Step:  0 | batch x:  [  9.   1.   5.   3.  10.] | betch y:  [  2.  10.   6.   8.   1.]
Epoch:  3 | Step:  1 | batch x:  [ 8.  6.  4.  2.  7.] | betch y:  [ 3.  5.  7.  9.  4.]
Epoch:  4 | Step:  0 | batch x:  [ 10.   5.   9.   7.   3.] | betch y:  [ 1.  6.  2.  4.  8.]
Epoch:  4 | Step:  1 | batch x:  [ 6.  8.  2.  4.  1.] | betch y:  [  5.   3.   9.   7.  10.]