Clarification on the purpose and functionality of _pad_tensors_to_max_len in Trainer subclass

[oussaidene]

Hi,

I came across the following method in the codebase and wanted to ask for clarification about its purpose:

def _pad_tensors_to_max_len(self, tensor, max_length):
    if self.tokenizer is not None and hasattr(self.tokenizer, "pad_token_id"):
        # If PAD token is not defined at least EOS token has to be defined
        pad_token_id = (
            self.tokenizer.pad_token_id if self.tokenizer.pad_token_id is not None else self.tokenizer.eos_token_id
        )
    else:
        if self.model.config.pad_token_id is not None:
            pad_token_id = self.model.config.pad_token_id
        else:
            raise ValueError("Pad_token_id must be set in the configuration of the model, in order to pad tensors")
    tensor[tensor == -100] = self.tokenizer.pad_token_id
    padded_tensor = pad_token_id * torch.ones(
        (tensor.shape[0], max_length), dtype=tensor.dtype, device=tensor.device
    )
    padded_tensor[:, : tensor.shape[-1]] = tensor
    return padded_tensor

Thank you!