

from typing import TYPE_CHECKING

from ..utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available


__UpperCAmelCase	=			{
    'configuration_utils': ['GenerationConfig'],
    'streamers': ['TextIteratorStreamer', 'TextStreamer'],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase	=			[
          'Constraint',
          'ConstraintListState',
          'DisjunctiveConstraint',
          'PhrasalConstraint',
      ]
      __UpperCAmelCase	=			[
          'BeamHypotheses',
          'BeamScorer',
          'BeamSearchScorer',
          'ConstrainedBeamSearchScorer',
      ]
      __UpperCAmelCase	=			[
          'EpsilonLogitsWarper',
          'EtaLogitsWarper',
          'ForcedBOSTokenLogitsProcessor',
          'ForcedEOSTokenLogitsProcessor',
          'HammingDiversityLogitsProcessor',
          'InfNanRemoveLogitsProcessor',
          'LogitsProcessor',
          'LogitsProcessorList',
          'LogitsWarper',
          'MinLengthLogitsProcessor',
          'MinNewTokensLengthLogitsProcessor',
          'NoBadWordsLogitsProcessor',
          'NoRepeatNGramLogitsProcessor',
          'PrefixConstrainedLogitsProcessor',
          'RepetitionPenaltyLogitsProcessor',
          'SequenceBiasLogitsProcessor',
          'EncoderRepetitionPenaltyLogitsProcessor',
          'TemperatureLogitsWarper',
          'TopKLogitsWarper',
          'TopPLogitsWarper',
          'TypicalLogitsWarper',
          'EncoderNoRepeatNGramLogitsProcessor',
          'ExponentialDecayLengthPenalty',
          'LogitNormalization',
      ]
      __UpperCAmelCase	=			[
          'MaxNewTokensCriteria',
          'MaxLengthCriteria',
          'MaxTimeCriteria',
          'StoppingCriteria',
          'StoppingCriteriaList',
          'validate_stopping_criteria',
      ]
      __UpperCAmelCase	=			[
          'GenerationMixin',
          'top_k_top_p_filtering',
          'GreedySearchEncoderDecoderOutput',
          'GreedySearchDecoderOnlyOutput',
          'SampleEncoderDecoderOutput',
          'SampleDecoderOnlyOutput',
          'BeamSearchEncoderDecoderOutput',
          'BeamSearchDecoderOnlyOutput',
          'BeamSampleEncoderDecoderOutput',
          'BeamSampleDecoderOnlyOutput',
          'ContrastiveSearchEncoderDecoderOutput',
          'ContrastiveSearchDecoderOnlyOutput',
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase	=			[
          'TFForcedBOSTokenLogitsProcessor',
          'TFForcedEOSTokenLogitsProcessor',
          'TFLogitsProcessor',
          'TFLogitsProcessorList',
          'TFLogitsWarper',
          'TFMinLengthLogitsProcessor',
          'TFNoBadWordsLogitsProcessor',
          'TFNoRepeatNGramLogitsProcessor',
          'TFRepetitionPenaltyLogitsProcessor',
          'TFTemperatureLogitsWarper',
          'TFTopKLogitsWarper',
          'TFTopPLogitsWarper',
          'TFForceTokensLogitsProcessor',
          'TFSuppressTokensAtBeginLogitsProcessor',
          'TFSuppressTokensLogitsProcessor',
      ]
      __UpperCAmelCase	=			[
          'TFGenerationMixin',
          'tf_top_k_top_p_filtering',
          'TFGreedySearchDecoderOnlyOutput',
          'TFGreedySearchEncoderDecoderOutput',
          'TFSampleEncoderDecoderOutput',
          'TFSampleDecoderOnlyOutput',
          'TFBeamSearchEncoderDecoderOutput',
          'TFBeamSearchDecoderOnlyOutput',
          'TFBeamSampleEncoderDecoderOutput',
          'TFBeamSampleDecoderOnlyOutput',
          'TFContrastiveSearchEncoderDecoderOutput',
          'TFContrastiveSearchDecoderOnlyOutput',
      ]

try:
      if not is_flax_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase	=			[
          'FlaxForcedBOSTokenLogitsProcessor',
          'FlaxForcedEOSTokenLogitsProcessor',
          'FlaxLogitsProcessor',
          'FlaxLogitsProcessorList',
          'FlaxLogitsWarper',
          'FlaxMinLengthLogitsProcessor',
          'FlaxTemperatureLogitsWarper',
          'FlaxTopKLogitsWarper',
          'FlaxTopPLogitsWarper',
      ]
      __UpperCAmelCase	=			[
          'FlaxGenerationMixin',
          'FlaxGreedySearchOutput',
          'FlaxSampleOutput',
          'FlaxBeamSearchOutput',
      ]

if TYPE_CHECKING:
      from .configuration_utils import GenerationConfig
      from .streamers import TextIteratorStreamer, TextStreamer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .beam_constraints import Constraint, ConstraintListState, DisjunctiveConstraint, PhrasalConstraint
            from .beam_search import BeamHypotheses, BeamScorer, BeamSearchScorer, ConstrainedBeamSearchScorer
            from .logits_process import (
                EncoderNoRepeatNGramLogitsProcessor,
                EncoderRepetitionPenaltyLogitsProcessor,
                EpsilonLogitsWarper,
                EtaLogitsWarper,
                ExponentialDecayLengthPenalty,
                ForcedBOSTokenLogitsProcessor,
                ForcedEOSTokenLogitsProcessor,
                HammingDiversityLogitsProcessor,
                InfNanRemoveLogitsProcessor,
                LogitNormalization,
                LogitsProcessor,
                LogitsProcessorList,
                LogitsWarper,
                MinLengthLogitsProcessor,
                MinNewTokensLengthLogitsProcessor,
                NoBadWordsLogitsProcessor,
                NoRepeatNGramLogitsProcessor,
                PrefixConstrainedLogitsProcessor,
                RepetitionPenaltyLogitsProcessor,
                SequenceBiasLogitsProcessor,
                TemperatureLogitsWarper,
                TopKLogitsWarper,
                TopPLogitsWarper,
                TypicalLogitsWarper,
            )
            from .stopping_criteria import (
                MaxLengthCriteria,
                MaxNewTokensCriteria,
                MaxTimeCriteria,
                StoppingCriteria,
                StoppingCriteriaList,
                validate_stopping_criteria,
            )
            from .utils import (
                BeamSampleDecoderOnlyOutput,
                BeamSampleEncoderDecoderOutput,
                BeamSearchDecoderOnlyOutput,
                BeamSearchEncoderDecoderOutput,
                ContrastiveSearchDecoderOnlyOutput,
                ContrastiveSearchEncoderDecoderOutput,
                GenerationMixin,
                GreedySearchDecoderOnlyOutput,
                GreedySearchEncoderDecoderOutput,
                SampleDecoderOnlyOutput,
                SampleEncoderDecoderOutput,
                top_k_top_p_filtering,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tf_logits_process import (
                TFForcedBOSTokenLogitsProcessor,
                TFForcedEOSTokenLogitsProcessor,
                TFForceTokensLogitsProcessor,
                TFLogitsProcessor,
                TFLogitsProcessorList,
                TFLogitsWarper,
                TFMinLengthLogitsProcessor,
                TFNoBadWordsLogitsProcessor,
                TFNoRepeatNGramLogitsProcessor,
                TFRepetitionPenaltyLogitsProcessor,
                TFSuppressTokensAtBeginLogitsProcessor,
                TFSuppressTokensLogitsProcessor,
                TFTemperatureLogitsWarper,
                TFTopKLogitsWarper,
                TFTopPLogitsWarper,
            )
            from .tf_utils import (
                TFBeamSampleDecoderOnlyOutput,
                TFBeamSampleEncoderDecoderOutput,
                TFBeamSearchDecoderOnlyOutput,
                TFBeamSearchEncoderDecoderOutput,
                TFContrastiveSearchDecoderOnlyOutput,
                TFContrastiveSearchEncoderDecoderOutput,
                TFGenerationMixin,
                TFGreedySearchDecoderOnlyOutput,
                TFGreedySearchEncoderDecoderOutput,
                TFSampleDecoderOnlyOutput,
                TFSampleEncoderDecoderOutput,
                tf_top_k_top_p_filtering,
            )

      try:
            if not is_flax_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .flax_logits_process import (
                FlaxForcedBOSTokenLogitsProcessor,
                FlaxForcedEOSTokenLogitsProcessor,
                FlaxLogitsProcessor,
                FlaxLogitsProcessorList,
                FlaxLogitsWarper,
                FlaxMinLengthLogitsProcessor,
                FlaxTemperatureLogitsWarper,
                FlaxTopKLogitsWarper,
                FlaxTopPLogitsWarper,
            )
            from .flax_utils import FlaxBeamSearchOutput, FlaxGenerationMixin, FlaxGreedySearchOutput, FlaxSampleOutput
else:
      import sys

      __UpperCAmelCase	=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








"""simple docstring"""




import os
from shutil import copyfile
from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
      from .tokenization_reformer import ReformerTokenizer
else:
      __UpperCAmelCase	=			None


__UpperCAmelCase	=			logging.get_logger(__name__)


__UpperCAmelCase	=			'▁'

__UpperCAmelCase	=			{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

__UpperCAmelCase	=			{
    'vocab_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'
        )
    },
    'tokenizer_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json'
        )
    },
}

__UpperCAmelCase	=			{
    'google/reformer-crime-and-punishment': 52_4288,
}







class        __lowercase     (      __lowerCamelCase   ):
  snake_case_			    =    VOCAB_FILES_NAMES
  snake_case_			    =    PRETRAINED_VOCAB_FILES_MAP
  snake_case_			    =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  snake_case_			    =    ["""input_ids""", """attention_mask"""]
  snake_case_			    =    ReformerTokenizer

  def __init__(					self						:     List[Any]   ,A						:     Dict=None   ,A						:     List[str]=None   ,A						:     Union[str, Any]="</s>"   ,A						:     List[str]="<unk>"   ,A						:     Tuple=[]   ,**A						:     Optional[int]   ,):






   '''simple docstring'''
   super().__init__(
       A   ,tokenizer_file=A   ,eos_token=A   ,unk_token=A   ,additional_special_tokens=A   ,**A   ,)

   UpperCAmelCase__   :					Tuple   				=   vocab_file
   UpperCAmelCase__   :					Optional[Any]   				=   False if not self.vocab_file else True




  def 				__lowercase    (					self						:     Any   ,A						:     str   ,A						:     Optional[str] = None      ):






   '''simple docstring'''
   if not self.can_save_slow_tokenizer:
    raise ValueError(
        """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
        """tokenizer."""      )

   if not os.path.isdir(A      ):
    logger.error(f"Vocabulary path ({save_directory}) should be a directory"      )
    return
   UpperCAmelCase__   :					Tuple   				=   os.path.join(
       A   ,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]      )

   if os.path.abspath(self.vocab_file      ) != os.path.abspath(A      ):
    copyfile(self.vocab_file   ,A      )

   return (out_vocab_file,)





