def __compute_spellchecker_loss(self, embeddings: torch.Tensor,
targets: torch.LongTensor) -> torch.Tensor:
mask = targets > 0
non_masked_targets = targets.masked_select(mask) - 1
non_masked_embeddings = embeddings.masked_select(
mask.unsqueeze(-1)).view(-1, self.output_dim + 1)
return self.losses['spellchecker'](non_masked_embeddings,
non_masked_targets)
def mask_at_indexes(
tokenizer: PreTrainedTokenizer,
ids: pt.LongTensor,
tokens_mask: pt.BoolTensor,
indexes: pt.LongTensor,
) -> pt.LongTensor:
masked_token_ids = ids.masked_select(tokens_mask)
masked_token_ids[indexes] = tokenizer.mask_token_id
masked_ids = ids.masked_scatter(tokens_mask, masked_token_ids)
masked_ids = cast(pt.LongTensor, masked_ids)
return masked_ids
