




from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


SCREAMING_SNAKE_CASE__       :      Tuple  =   logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__       :      str  =   {
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

SCREAMING_SNAKE_CASE__       :      Any  =   {
    'vocab_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'
    },
    'merges_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'
    },
    'tokenizer_config_file': {
        'facebook/blenderbot_small-90M': (
            'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'
        )
    },
}

SCREAMING_SNAKE_CASE__       :      str  =   {
    'facebook/blenderbot_small-90M': 512,
}




class 		UpperCamelCase__	(lowerCAmelCase__     ):

    '''simple docstring'''



    lowerCamelCase_      :	Optional[Any]	     =      VOCAB_FILES_NAMES
    lowerCamelCase_      :	List[Any]	     =      PRETRAINED_VOCAB_FILES_MAP
    lowerCamelCase_      :	Optional[Any]	     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowerCamelCase_      :	Optional[Any]	     =      BlenderbotSmallTokenizer







    def __init__(    self     ,  UpperCamelCase__=None     ,  UpperCamelCase__=None     ,  UpperCamelCase__="<|endoftext|>"     ,  UpperCamelCase__="<|endoftext|>"     ,  UpperCamelCase__="<|endoftext|>"     ,  UpperCamelCase__=False     ,  UpperCamelCase__=True     ,  **UpperCamelCase__     ,  )     ->      Optional[Any]:
           super().__init__(
               ByteLevelBPETokenizer(
                   vocab=UpperCamelCase__     ,  merges=UpperCamelCase__     ,  add_prefix_space=UpperCamelCase__     ,  trim_offsets=UpperCamelCase__     ,  )     ,  bos_token=UpperCamelCase__     ,  eos_token=UpperCamelCase__     ,  unk_token=UpperCamelCase__     ,  **UpperCamelCase__     ,  )
           lowerCamelCase   :      List[str]			 =					add_prefix_space







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__=None     )     ->      Any:
           lowerCamelCase   :      Any			 =					[self.bos_token_id] + token_ids_a + [self.eos_token_id]
           if token_ids_a is None:
                  return output

           return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__ = None     )     ->      List[int]:
           lowerCamelCase   :      Tuple			 =					[self.sep_token_id]
           lowerCamelCase   :      Optional[int]			 =					[self.cls_token_id]

           if token_ids_a is None:
                  return len(cls + token_ids_a + sep     ) * [0]
           return len(cls + token_ids_a + sep + sep + token_ids_a + sep     ) * [0]













'''simple docstring'''

import argparse
import logging
import pickle
from collections import Counter


logging.basicConfig(
    format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
lowercase_					= logging.getLogger(__name__)

if __name__ == "__main__":
      lowercase_					= argparse.ArgumentParser(
          description="""Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)"""
      )
      parser.add_argument(
          """--data_file""", type=str, default="""data/dump.bert-base-uncased.pickle""", help="""The binarized dataset."""
      )
      parser.add_argument(
          """--token_counts_dump""", type=str, default="""data/token_counts.bert-base-uncased.pickle""", help="""The dump file."""
      )
      parser.add_argument("""--vocab_size""", default=30_522, type=int)
      lowercase_					= parser.parse_args()

      logger.info(f"""Loading data from {args.data_file}""")
      with open(args.data_file, """rb""") as fp:
            lowercase_					= pickle.load(fp)

      logger.info("""Counting occurrences for MLM.""")
      lowercase_					= Counter()
      for tk_ids in data:
            counter.update(tk_ids)
      lowercase_					= [0] * args.vocab_size
      for k, v in counter.items():
            lowercase_					= v

      logger.info(f"""Dump to {args.token_counts_dump}""")
      with open(args.token_counts_dump, """wb""") as handle:
            pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)



