import torch


def mask_tokens_nomlm(inputs, tokenizer, args):

    """ Prepare masked tokens inputs/labels for masked language modeling: 80% MASK, 10% random, 10% original. """

    labels = inputs.clone()

    att_mask = [val == tokenizer.pad_token_id for val in labels.tolist()]

    attention_mask = torch.full(labels.shape, 1).masked_fill_(torch.tensor(att_mask, dtype=torch.uint8), value=0)

    return inputs, labels