So I’m trying to manually split my training data into batches such that I can easily access them via indexing, and not relying on DataLoader to split them up for me, since that way I won’t be able to access the individual batches by indexing. So I tried the following:
train_data = datasets.ANY(root='data', transform=T_train, download=True)
BS = 200
num_batches = len(train_data) // BS
sequence = list(range(len(train_data)))
np.random.shuffle(sequence)  # To shuffle the training data
subsets = [Subset(train_data, sequence[i * BS: (i + 1) * BS]) for i in range(num_batches)]
train_loader = [DataLoader(sub, batch_size=BS) for sub in subsets]  # Create multiple batches, each with BS number of samples

Which works during training just fine.
However, when I attempted another way to manually split the training data I got different end results, even with all the same parameters and the following settings:
device = torch.device('cuda')
torch.manual_seed(0)
np.random.seed(0)
torch.backends.cudnn.benchmark = False
torch.backends.cudnn.deterministic = True
torch.cuda.empty_cache()

I only split the training data the following way this time:
train_data = list(datasets.ANY(root='data', transform=T_train, download=True))  # Cast into a list
BS = 200
num_batches = len(train_data) // BS
np.random.shuffle(train_data)  # To shuffle the training data
train_loader = [DataLoader(train_data[i*BS: (i+1)*BS], batch_size=BS) for i in range(num_batches)]

But this gives me different results than the first approach, even though (I believe ) that both approaches are identical in manually splitting the training data into batches. I even tried not shuffling at all and loading the data just as it is, but I still got different results (85.2% v.s 81.98% accuracy). I even manually checked that the loaded images from the batches match; and are the same using both methods.
Not only that, when I load the training data the conventional way as follows:
BS = 200
train_loader = DataLoader(train_data, batch_size=BS, shuffle=True)

I get even more drastic results!
Can somebody please explain to me why these differences arise, and how to fix it?