Small inconsistency in Chapter 2, Part 3 example

I noticed a small inconsistency at the end of Chapter 2, Part 3.

The example shows:

encoded_sequences = [
[...], # length 16
[...], # length 8
]

model_inputs = torch.tensor(encoded_sequences)

Since the two sequences have different lengths, torch.tensor(encoded_sequences) will raise an error because tensors require all rows to have the same length.

A simple fix would be to make encoded_sequences rectangular by padding the shorter sequence before converting it to a tensor. This would make the example consistent with the explanation.

Thanks for the great course!

Start in Chapter 2, Part 3 and locate the example containing encoded_sequences and torch.tensor(encoded_sequences). Verify the sequence lengths and update the example so the sequences are rectangular before tensor conversion; done means the example matches the explanation and no longer raises a shape error.

Written by the indexing model from the issue text.