https://discuss.pytorch.org/t/why-i-use-shuffle-false-the-order-of-data-are-changed/106340

dataloader_shuffle.py

from torch.utils.data import DataLoader, Dataset
import torch, torch.nn as nn
import numpy as np

class DS(Dataset):
    # Constructor
    def __init__(self):
        super().__init__()      
        X = list(np.arange(15000))
        self.x = X
        self.len = len(self.x)
        
    # Getter
    def __getitem__(self, index):    
        return self.x[index]
    
    # Get length
    def __len__(self):
        return self.len

if __name__ == '__main__':
    dataset = DS()
    dloader = DataLoader(dataset=dataset, batch_size=360, shuffle=False)

    for i, data in enumerate(dloader):
        labels = data
        print(dataset.x[i*360:(i+1)*360])
        print('from dloader', labels)
        input()