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| import torch | |
| # from transformers import BertTokenizerFast | |
| from colbert.modeling.hf_colbert import HF_ColBERT | |
| from colbert.infra import ColBERTConfig | |
| from colbert.modeling.tokenization.utils import _split_into_batches, _sort_by_length | |
| class DocTokenizer(): | |
| def __init__(self, config: ColBERTConfig): | |
| self.tok = HF_ColBERT.raw_tokenizer_from_pretrained(config.checkpoint) | |
| self.config = config | |
| self.doc_maxlen = config.doc_maxlen | |
| self.D_marker_token, self.D_marker_token_id = '[D]', self.tok.convert_tokens_to_ids('[unused1]') | |
| self.cls_token, self.cls_token_id = self.tok.cls_token, self.tok.cls_token_id | |
| self.sep_token, self.sep_token_id = self.tok.sep_token, self.tok.sep_token_id | |
| # assert self.D_marker_token_id == 2 | |
| def tokenize(self, batch_text, add_special_tokens=False): | |
| assert type(batch_text) in [list, tuple], (type(batch_text)) | |
| tokens = [self.tok.tokenize(x, add_special_tokens=False) for x in batch_text] | |
| if not add_special_tokens: | |
| return tokens | |
| prefix, suffix = [self.cls_token, self.D_marker_token], [self.sep_token] | |
| tokens = [prefix + lst + suffix for lst in tokens] | |
| return tokens | |
| def encode(self, batch_text, add_special_tokens=False): | |
| assert type(batch_text) in [list, tuple], (type(batch_text)) | |
| ids = self.tok(batch_text, add_special_tokens=False)['input_ids'] | |
| if not add_special_tokens: | |
| return ids | |
| prefix, suffix = [self.cls_token_id, self.D_marker_token_id], [self.sep_token_id] | |
| ids = [prefix + lst + suffix for lst in ids] | |
| return ids | |
| def tensorize(self, batch_text, bsize=None): | |
| assert type(batch_text) in [list, tuple], (type(batch_text)) | |
| # add placehold for the [D] marker | |
| batch_text = ['. ' + x for x in batch_text] | |
| obj = self.tok(batch_text, padding='longest', truncation='longest_first', | |
| return_tensors='pt', max_length=self.doc_maxlen) | |
| ids, mask = obj['input_ids'], obj['attention_mask'] | |
| # postprocess for the [D] marker | |
| ids[:, 1] = self.D_marker_token_id | |
| if bsize: | |
| ids, mask, reverse_indices = _sort_by_length(ids, mask, bsize) | |
| batches = _split_into_batches(ids, mask, bsize) | |
| return batches, reverse_indices | |
| return ids, mask | |