
"""simple docstring"""

import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCamelCase			:       Tuple									=				logging.get_logger(__name__)


UpperCamelCase			:       Any									=				{
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

UpperCamelCase			:       Optional[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"
        )
    },
}

UpperCamelCase			:       Optional[int]									=				{"facebook/blenderbot_small-90M": 5_1_2}






def 							A		(       snake_case   :List[Any]	)   ->			List[Any]:
 __UpperCamelCase       						= set()
 __UpperCamelCase       						= word[0]
 for char in word[1:]:
  pairs.add((prev_char, char)	)
  __UpperCamelCase       						= char

 __UpperCamelCase       						= set(_lowerCamelCase	)
 return pairs





class __lowerCAmelCase	(   a__    ):
     lowercase		     =		VOCAB_FILES_NAMES
     lowercase		     =		PRETRAINED_VOCAB_FILES_MAP
     lowercase		     =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowercase		     =		["input_ids", "attention_mask"]





     def __init__(			self			,  __UpperCAmelCase			,  __UpperCAmelCase			,  __UpperCAmelCase="__start__"			,  __UpperCAmelCase="__end__"			,  __UpperCAmelCase="__unk__"			,  __UpperCAmelCase="__null__"			,  **__UpperCAmelCase			,  ):

      '''simple docstring'''




      super().__init__(unk_token=_A			,  bos_token=_A			,  eos_token=_A			,  pad_token=_A			,  **_A   )

      with open(_A			,  encoding='utf-8'   ) as vocab_handle:
       __UpperCamelCase       						= json.load(_A   )
      __UpperCamelCase       						= {v: k for k, v in self.encoder.items()}
      with open(_A			,  encoding='utf-8'   ) as merges_handle:
       __UpperCamelCase       						= merges_handle.read().split('\n'   )[1:-1]
      __UpperCamelCase       						= [tuple(merge.split()   ) for merge in merges]
      __UpperCamelCase       						= dict(zip(_A			,  range(len(_A   )   )   )   )
      __UpperCamelCase       						= {}





     @property
     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      return len(self.encoder   )





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      return dict(self.encoder			,  **self.added_tokens_encoder   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      if token in self.cache:
       return self.cache[token]
      __UpperCamelCase       						= re.sub('([.,!?()])'			,  R' \1'			,  _A   )
      __UpperCamelCase       						= re.sub('(\')'			,  R' \1 '			,  _A   )
      __UpperCamelCase       						= re.sub(R'\s{2,}'			,  ' '			,  _A   )
      if "\n" in token:
       __UpperCamelCase       						= token.replace('\n'			,  ' __newln__'   )

      __UpperCamelCase       						= token.split(' '   )
      __UpperCamelCase       						= []
      for token in tokens:
       if not len(_A   ):
        continue

       __UpperCamelCase       						= token.lower()
       __UpperCamelCase       						= tuple(_A   )
       __UpperCamelCase       						= tuple(list(word[:-1]   ) + [word[-1] + '</w>']   )
       __UpperCamelCase       						= get_pairs(_A   )

       if not pairs:
        words.append(_A   )
        continue

       while True:
        __UpperCamelCase       						= min(_A			,  key=lambda __UpperCAmelCase   : self.bpe_ranks.get(_A			,  float('inf'   )   )   )
        if bigram not in self.bpe_ranks:
         break
        __UpperCamelCase       						= bigram
        __UpperCamelCase       						= []
        __UpperCamelCase       						= 0

        while i < len(_A   ):
         try:
          __UpperCamelCase       						= word.index(_A			,  _A   )
          new_word.extend(word[i:j]   )
          __UpperCamelCase       						= j
         except ValueError:
          new_word.extend(word[i:]   )
          break

         if word[i] == first and i < len(_A   ) - 1 and word[i + 1] == second:
          new_word.append(first + second   )
          i += 2
         else:
          new_word.append(word[i]   )
          i += 1
        __UpperCamelCase       						= tuple(_A   )
        __UpperCamelCase       						= new_word
        if len(_A   ) == 1:
         break
        else:
         __UpperCamelCase       						= get_pairs(_A   )
       __UpperCamelCase       						= '@@ '.join(_A   )
       __UpperCamelCase       						= word[:-4]

       __UpperCamelCase       						= word
       words.append(_A   )
      return " ".join(_A   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      __UpperCamelCase       						= []

      __UpperCamelCase       						= re.findall(R'\S+\n?'			,  _A   )

      for token in words:
       split_tokens.extend(list(self.bpe(_A   ).split(' '   )   )   )
      return split_tokens





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      __UpperCamelCase       						= token.lower()
      return self.encoder.get(_A			,  self.encoder.get(self.unk_token   )   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      return self.decoder.get(_A			,  self.unk_token   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      __UpperCamelCase       						= ' '.join(_A   ).replace('@@ '			,  ''   ).strip()
      return out_string







     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  __UpperCAmelCase = None   ):

      '''simple docstring'''




      if not os.path.isdir(_A   ):
       logger.error(F'Vocabulary path ({save_directory}) should be a directory'   )
       return
      __UpperCamelCase       						= os.path.join(
          _A			,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )
      __UpperCamelCase       						= os.path.join(
          _A			,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']   )

      with open(_A			,  'w'			,  encoding='utf-8'   ) as f:
       f.write(json.dumps(self.encoder			,  indent=2			,  sort_keys=_A			,  ensure_ascii=_A   ) + '\n'   )

      __UpperCamelCase       						= 0
      with open(_A			,  'w'			,  encoding='utf-8'   ) as writer:
       writer.write('#version: 0.2\n'   )
       for bpe_tokens, token_index in sorted(self.bpe_ranks.items()			,  key=lambda __UpperCAmelCase   : kv[1]   ):
        if index != token_index:
         logger.warning(
             F'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
             ' Please check that the tokenizer is not corrupted!'   )
         __UpperCamelCase       						= token_index
        writer.write(' '.join(_A   ) + '\n'   )
        index += 1

      return vocab_file, merge_file





"""simple docstring"""

import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp






def 							A		(       )   ->			List[Any]:
 __UpperCamelCase       						= ArgumentParser(
     description=(
         'PyTorch TPU distributed training launch helper utility that will spawn up multiple distributed processes'
     )	)

 # Optional arguments for the launch helper
 parser.add_argument('--num_cores'       ,      type=snake_case       ,      default=1       ,      help='Number of TPU cores to use (1 or 8).'	)

 # positional
 parser.add_argument(
     'training_script'       ,      type=snake_case       ,      help=(
         'The full path to the single TPU training '
         'program/script to be launched in parallel, '
         'followed by all the arguments for the '
         'training script'
     )       ,      )

 # rest from the training program
 parser.add_argument('training_script_args'       ,      nargs=snake_case	)

 return parser.parse_args()






def 							A		(       )   ->			Optional[int]:
 __UpperCamelCase       						= parse_args()

 # Import training_script as a module.
 __UpperCamelCase       						= Path(args.training_script	)
 sys.path.append(str(script_fpath.parent.resolve()	)	)
 __UpperCamelCase       						= script_fpath.stem
 __UpperCamelCase       						= importlib.import_module(snake_case	)

 # Patch sys.argv
 __UpperCamelCase       						= [args.training_script] + args.training_script_args + ['--tpu_num_cores', str(args.num_cores	)]

 xmp.spawn(mod._mp_fn       ,      args=()       ,      nprocs=args.num_cores	)


if __name__ == "__main__":
      main()



