1 import torch
2 import torch.utils.data as Data
3
4 torch.manual_seed(1) # reproducible
5
6 BATCH_SIZE = 5
7 # BATCH_SIZE = 8
8
9 x = torch.linspace(1, 10, 10) # this is x data (torch tensor)
10 y = torch.linspace(10, 1, 10) # this is y data (torch tensor)
11
12 torch_dataset = Data.TensorDataset(x, y)
13 loader = Data.DataLoader(
14 dataset=torch_dataset, # torch TensorDataset format
15 batch_size=BATCH_SIZE, # mini batch size
16 shuffle=True, # random shuffle for training
17 num_workers=2, # subprocesses for loading data
18 )
19
20
21 def show_batch():
22 for epoch in range(3): # train entire dataset 3 times
23 for step, (batch_x, batch_y) in enumerate(loader): # for each training step
24 # train your data...
25 print('Epoch: ', epoch, '| Step: ', step, '| batch x: ',
26 batch_x.numpy(), '| batch y: ', batch_y.numpy())
27
28
29 if __name__ == '__main__':
30 show_batch()
