code: from typing import TYPE_CHECKING
  
  from ..utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available
  
  
  lowerCamelCase__           =				{
      'configuration_utils': ['GenerationConfig'],
      'streamers': ['TextIteratorStreamer', 'TextStreamer'],
  }
  
  try:
  		if not is_torch_available():
  				raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  		pass
  else:
  		lowerCamelCase__           =				[
  		    'Constraint',
  		    'ConstraintListState',
  		    'DisjunctiveConstraint',
  		    'PhrasalConstraint',
  		]
  		lowerCamelCase__           =				[
  		    'BeamHypotheses',
  		    'BeamScorer',
  		    'BeamSearchScorer',
  		    'ConstrainedBeamSearchScorer',
  		]
  		lowerCamelCase__           =				[
  		    'EpsilonLogitsWarper',
  		    'EtaLogitsWarper',
  		    'ForcedBOSTokenLogitsProcessor',
  		    'ForcedEOSTokenLogitsProcessor',
  		    'HammingDiversityLogitsProcessor',
  		    'InfNanRemoveLogitsProcessor',
  		    'LogitsProcessor',
  		    'LogitsProcessorList',
  		    'LogitsWarper',
  		    'MinLengthLogitsProcessor',
  		    'MinNewTokensLengthLogitsProcessor',
  		    'NoBadWordsLogitsProcessor',
  		    'NoRepeatNGramLogitsProcessor',
  		    'PrefixConstrainedLogitsProcessor',
  		    'RepetitionPenaltyLogitsProcessor',
  		    'SequenceBiasLogitsProcessor',
  		    'EncoderRepetitionPenaltyLogitsProcessor',
  		    'TemperatureLogitsWarper',
  		    'TopKLogitsWarper',
  		    'TopPLogitsWarper',
  		    'TypicalLogitsWarper',
  		    'EncoderNoRepeatNGramLogitsProcessor',
  		    'ExponentialDecayLengthPenalty',
  		    'LogitNormalization',
  		]
  		lowerCamelCase__           =				[
  		    'MaxNewTokensCriteria',
  		    'MaxLengthCriteria',
  		    'MaxTimeCriteria',
  		    'StoppingCriteria',
  		    'StoppingCriteriaList',
  		    'validate_stopping_criteria',
  		]
  		lowerCamelCase__           =				[
  		    '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:
  		lowerCamelCase__           =				[
  		    'TFForcedBOSTokenLogitsProcessor',
  		    'TFForcedEOSTokenLogitsProcessor',
  		    'TFLogitsProcessor',
  		    'TFLogitsProcessorList',
  		    'TFLogitsWarper',
  		    'TFMinLengthLogitsProcessor',
  		    'TFNoBadWordsLogitsProcessor',
  		    'TFNoRepeatNGramLogitsProcessor',
  		    'TFRepetitionPenaltyLogitsProcessor',
  		    'TFTemperatureLogitsWarper',
  		    'TFTopKLogitsWarper',
  		    'TFTopPLogitsWarper',
  		    'TFForceTokensLogitsProcessor',
  		    'TFSuppressTokensAtBeginLogitsProcessor',
  		    'TFSuppressTokensLogitsProcessor',
  		]
  		lowerCamelCase__           =				[
  		    '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:
  		lowerCamelCase__           =				[
  		    'FlaxForcedBOSTokenLogitsProcessor',
  		    'FlaxForcedEOSTokenLogitsProcessor',
  		    'FlaxLogitsProcessor',
  		    'FlaxLogitsProcessorList',
  		    'FlaxLogitsWarper',
  		    'FlaxMinLengthLogitsProcessor',
  		    'FlaxTemperatureLogitsWarper',
  		    'FlaxTopKLogitsWarper',
  		    'FlaxTopPLogitsWarper',
  		]
  		lowerCamelCase__           =				[
  		    '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
  
  		lowerCamelCase__           =				_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
  
  
  
  
  
  
style_context: 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:
  		lowerCamelCase__           =				None
  
  
  lowerCamelCase__           =				logging.get_logger(__name__)
  
  
  lowerCamelCase__           =				'▁'
  
  lowerCamelCase__           =				{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}
  
  lowerCamelCase__           =				{
      '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'
          )
      },
  }
  
  lowerCamelCase__           =				{
      'google/reformer-crime-and-punishment': 52_42_88,
  }
  
  
  
  
  class 					UpperCamelCase	(     snake_case__      ):
  					__UpperCamelCase						=   VOCAB_FILES_NAMES
  					__UpperCamelCase						=   PRETRAINED_VOCAB_FILES_MAP
  					__UpperCamelCase						=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  					__UpperCamelCase						=   ["""input_ids""", """attention_mask"""]
  					__UpperCamelCase						=   ReformerTokenizer
  
  
  
  
  					def __init__( self :					Tuple      ,_lowerCAmelCase :					Dict=None      ,_lowerCAmelCase :					Union[str, Any]=None      ,_lowerCAmelCase :					int="</s>"      ,_lowerCAmelCase :					Dict="<unk>"      ,_lowerCAmelCase :					Dict=[]      ,**_lowerCAmelCase :					Optional[Any]      ,):
  
  
  							"""simple docstring"""
  
  
  
  
  							super().__init__(
  							    _lowerCAmelCase      ,tokenizer_file=_lowerCAmelCase      ,eos_token=_lowerCAmelCase      ,unk_token=_lowerCAmelCase      ,additional_special_tokens=_lowerCAmelCase      ,**_lowerCAmelCase      ,)
  
  							__snake_case		       =     vocab_file
  							__snake_case		       =     False if not self.vocab_file else True
  
  
  
  
  
  
  
  					def 							UpperCamelCase_						( self :					Dict      ,_lowerCAmelCase :					str      ,_lowerCAmelCase :					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(_lowerCAmelCase						):
  									logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""						)
  									return
  							__snake_case		       =     os.path.join(
  							    _lowerCAmelCase      ,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)
  
  							if os.path.abspath(self.vocab_file						) != os.path.abspath(_lowerCAmelCase						):
  									copyfile(self.vocab_file      ,_lowerCAmelCase						)
  
  							return (out_vocab_file,)
  
  
  
  
  
  