
"""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:
	snake_case					  =						None


snake_case					  =						logging.get_logger(__name__)


snake_case					  =						'''▁'''

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

snake_case					  =						{
    '''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'''
        )
    },
}

snake_case					  =						{
    '''google/reformer-crime-and-punishment''': 5_2_4_2_8_8,
}




class 	UpperCamelCase      (			_UpperCAmelCase ):

				"""simple docstring"""



				UpperCAmelCase_							: int		    =							VOCAB_FILES_NAMES
				UpperCAmelCase_							: Union[str, Any]		    =							PRETRAINED_VOCAB_FILES_MAP
				UpperCAmelCase_							: List[Any]		    =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				UpperCAmelCase_							: Dict		    =							["input_ids", "attention_mask"]
				UpperCAmelCase_							: List[Any]		    =							ReformerTokenizer


				def __init__(							self						,      lowercase__=None						,      lowercase__=None						,      lowercase__="</s>"						,      lowercase__="<unk>"						,      lowercase__=[]						,      **lowercase__						,      )       ->       Any:
									"""simple docstring"""







									super().__init__(
									    _lowerCAmelCase						,      tokenizer_file=_lowerCAmelCase						,      eos_token=_lowerCAmelCase						,      unk_token=_lowerCAmelCase						,      additional_special_tokens=_lowerCAmelCase						,      **_lowerCAmelCase						,      )

									SCREAMING_SNAKE_CASE           =      vocab_file
									SCREAMING_SNAKE_CASE           =      False if not self.vocab_file else True




				def 				A   (							self						,      lowercase__						,      lowercase__ = None     )       ->       Tuple[str]:
									"""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
									SCREAMING_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,)




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase			:					Optional[int]         =							{
    '''configuration_dpr''': ['''DPR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DPRConfig'''],
    '''tokenization_dpr''': [
        '''DPRContextEncoderTokenizer''',
        '''DPRQuestionEncoderTokenizer''',
        '''DPRReaderOutput''',
        '''DPRReaderTokenizer''',
    ],
}


try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase			:					List[str]         =							[
					    '''DPRContextEncoderTokenizerFast''',
					    '''DPRQuestionEncoderTokenizerFast''',
					    '''DPRReaderTokenizerFast''',
					]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase			:					Optional[Any]         =							[
					    '''DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''DPRContextEncoder''',
					    '''DPRPretrainedContextEncoder''',
					    '''DPRPreTrainedModel''',
					    '''DPRPretrainedQuestionEncoder''',
					    '''DPRPretrainedReader''',
					    '''DPRQuestionEncoder''',
					    '''DPRReader''',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase			:					Optional[int]         =							[
					    '''TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''TFDPRContextEncoder''',
					    '''TFDPRPretrainedContextEncoder''',
					    '''TFDPRPretrainedQuestionEncoder''',
					    '''TFDPRPretrainedReader''',
					    '''TFDPRQuestionEncoder''',
					    '''TFDPRReader''',
					]


if TYPE_CHECKING:
					from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
					from .tokenization_dpr import (
					    DPRContextEncoderTokenizer,
					    DPRQuestionEncoderTokenizer,
					    DPRReaderOutput,
					    DPRReaderTokenizer,
					)

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_dpr_fast import (
										    DPRContextEncoderTokenizerFast,
										    DPRQuestionEncoderTokenizerFast,
										    DPRReaderTokenizerFast,
										)

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_dpr import (
										    DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    DPRContextEncoder,
										    DPRPretrainedContextEncoder,
										    DPRPreTrainedModel,
										    DPRPretrainedQuestionEncoder,
										    DPRPretrainedReader,
										    DPRQuestionEncoder,
										    DPRReader,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_dpr import (
										    TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFDPRContextEncoder,
										    TFDPRPretrainedContextEncoder,
										    TFDPRPretrainedQuestionEncoder,
										    TFDPRPretrainedReader,
										    TFDPRQuestionEncoder,
										    TFDPRReader,
										)

else:
					import sys

					UpperCamelCase			:					List[Any]         =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

