GPT2TokenizerFast

src/transformers/__init__.py

@@ -108,7 +108,7 @@ from .tokenization_bert_japanese import BertJapaneseTokenizer, CharacterTokenize
 from .tokenization_camembert import CamembertTokenizer
 from .tokenization_ctrl import CTRLTokenizer
 from .tokenization_distilbert import DistilBertTokenizer
-from .tokenization_gpt2 import GPT2Tokenizer
+from .tokenization_gpt2 import GPT2Tokenizer, GPT2TokenizerFast
 from .tokenization_openai import OpenAIGPTTokenizer
 from .tokenization_roberta import RobertaTokenizer
 from .tokenization_t5 import T5Tokenizer

src/transformers/tokenization_gpt2.py

@@ -22,7 +22,7 @@ from functools import lru_cache
 
 import regex as re
 
-from .tokenization_utils import PreTrainedTokenizer
+from .tokenization_utils import PreTrainedTokenizer, FastPreTrainedTokenizer
 
 
 logger = logging.getLogger(__name__)
@@ -246,3 +246,36 @@ class GPT2Tokenizer(PreTrainedTokenizer):
                 index += 1
 
         return vocab_file, merge_file
+
+class GPT2TokenizerFast(FastPreTrainedTokenizer):
+    vocab_files_names = VOCAB_FILES_NAMES
+    pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP
+    max_model_input_sizes = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
+
+    def __init__(self, vocab_file, merges_file, unk_token="<|endoftext|>", bos_token="<|endoftext|>",
+                 eos_token="<|endoftext|>", pad_to_max_length=False, add_prefix_space=False,
+                 max_length=None, stride=0, truncation_strategy='longest_first', **kwargs):
+
+        try:
+            from tokenizers import Tokenizer, models, pre_tokenizers, decoders
+
+            super(GPT2TokenizerFast, self).__init__(bos_token=bos_token, eos_token=eos_token, unk_token=unk_token, **kwargs)
+
+            self._tokenizer = Tokenizer(models.BPE.from_files(vocab_file, merges_file))
+            self._update_special_tokens()
+            self._tokenizer.with_pre_tokenizer(pre_tokenizers.ByteLevel.new(add_prefix_space))
+            self._tokenizer.with_decoder(decoders.ByteLevel.new())
+            if max_length:
+                self._tokenizer.with_truncation(max_length, stride, truncation_strategy)
+            self._tokenizer.with_padding(
+                max_length if pad_to_max_length else None,
+                self.padding_side,
+                self.pad_token_id if self.pad_token_id is not None else 0,
+                self.pad_token_type_id,
+                self.pad_token if self.pad_token is not None else ""
+            )
+            self._decoder = decoders.ByteLevel.new()
+
+        except (AttributeError, ImportError) as e:
+            logger.error("Make sure you installed `tokenizers` with `pip install tokenizers==0.0.8`")
+            raise e
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