Hi,
You can use torch.utils.data.random_split:
import torch
from torch.utils.data import random_split

data = torch.arange(0, 1000*94).reshape((1000, 1, 94))

train, test= random_split(data, [int(len(data)*0.9), int(len(data)*0.1)])

print(len(train))  # 900
print(len(test))  # 100


  
    
    
    How to split dataset into test and validation sets 
  
  
    I have a dataset in which the different images are classified into different folders. 
I want to split the data to test, train, valid sets. 
Please help
  


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