nlp-tt-pad-tensor-ds.py

padded_dataset = []
for i in tqdm(range(len(reviews))):
    padded_dataset.append(pad_tensor(reviews[i], int(max_pad_length)))
    
X = torch.stack(padded_dataset)
y = torch.tensor(labels)

#train test splitting
X_train, X_test, y_train, y_test = train_test_split(X,
                                                    y,
                                                    test_size=.25,
                                                    random_state=42)

X_train, y_train = torch.tensor(X_train), torch.tensor(y_train)
X_test, y_test = torch.tensor(X_test), torch.tensor(y_test)