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__)






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,)





