Okay, my input includes X and Y, where the X are the token-sequences that comes from actual sentences which passed through the tokenizer, the shape is (18000, 23), as there is 18000 data and the padding size is 23.
For example, part of the X is:
[[   1    8 2860   45    4   73    5  124    4  520    7   44    4  156
    49  553    2    0    0    0    0    0    0]
 [   1   15    7   23   11   13    5  124    4   14  121  242   52  401
    17  401    2    0    0    0    0    0    0] ...]

Then, Y are the label-tensors for each token-sequence in X, the shape is (18000,). For example, part of the Y is:
[0, 0, 0, 1, 1, ...]

And I use
train = torch.utils.data.TensorDataset(x_train, y_train)
train_loader = DataLoader(train, batch_size=BATCH_SIZE, shuffle=True)

to put them together to train.