




"""simple docstring"""

# Lint as: python3

import hashlib
from typing import Union



def 				a (						__snake_case     :				Union[str, int, bytes]  ):



				'''simple docstring'''





				if isinstance(__snake_case,    __snake_case  ):
								# Data already in bytes, returns as it as
								return hash_data
				elif isinstance(__snake_case,    __snake_case  ):
								# We keep the data as it as for it ot be later encoded to UTF-8
								# However replace `\\` with `/` for Windows compatibility
								UpperCAmelCase_					:Optional[Any]      			=      hash_data.replace('''\\''',    '''/'''  )
				elif isinstance(__snake_case,    __snake_case  ):
								UpperCAmelCase_					:Union[str, Any]      			=      str(__snake_case  )
				else:
								# If data is not of the required type, raise error
								raise InvalidKeyError(__snake_case  )

				return hash_data.encode('''utf-8'''  )



class  _snake_case				(							A__       ):

				'''simple docstring'''




				def __init__(							self      :  List[str]					,							snake_case      :  List[Any]     ):
								UpperCAmelCase_					:Tuple      			=      '''\nFAILURE TO GENERATE DATASET: Invalid key type detected'''
								UpperCAmelCase_					:int      			=      f'\nFound Key {hash_data} of type {type(snake_case     )}'
								UpperCAmelCase_					:List[str]      			=      '''\nKeys should be either str, int or bytes type'''
								super().__init__(f'{self.prefix}{self.err_msg}{self.suffix}'     )



class  _snake_case				(							A__       ):

				'''simple docstring'''




				def __init__(							self      :  Any					,							snake_case      :  str					,							snake_case      :  Union[str, Any]					,							snake_case      :  int=""     ):
								UpperCAmelCase_					:Union[str, Any]      			=      key
								UpperCAmelCase_					:Optional[Any]      			=      duplicate_key_indices
								UpperCAmelCase_					:Dict      			=      fix_msg
								UpperCAmelCase_					:Union[str, Any]      			=      '''Found multiple examples generated with the same key'''
								if len(snake_case     ) <= 20:
												UpperCAmelCase_					:Optional[Any]      			=      f'\nThe examples at index {", ".join(snake_case     )} have the key {key}'
								else:
												UpperCAmelCase_					:List[Any]      			=      f'\nThe examples at index {", ".join(duplicate_key_indices[:20]     )}... ({len(snake_case     ) - 20} more) have the key {key}'
								UpperCAmelCase_					:Any      			=      '''\n''' + fix_msg if fix_msg else ''''''
								super().__init__(f'{self.prefix}{self.err_msg}{self.suffix}'     )



class  _snake_case				:

				'''simple docstring'''




				def __init__(							self      :  int					,							snake_case      :  str     ):
								UpperCAmelCase_					:List[Any]      			=      hashlib.mda(_as_bytes(snake_case     )     )





				def 				snake_case_ (							self      :  int					,							snake_case      :  Union[str, int, bytes]     ):
								UpperCAmelCase_					:Any      			=      self._split_mda.copy()
								UpperCAmelCase_					:Optional[int]      			=      _as_bytes(snake_case     )
								mda.update(snake_case     )
								# Convert to integer with hexadecimal conversion
								return int(mda.hexdigest()					,							16     )








"""simple docstring"""

from typing import TYPE_CHECKING

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


__lowerCamelCase								=						{
    "configuration_bart": ["BART_PRETRAINED_CONFIG_ARCHIVE_MAP", "BartConfig", "BartOnnxConfig"],
    "tokenization_bart": ["BartTokenizer"],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase								=						["BartTokenizerFast"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase								=						[
						    "BART_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "BartForCausalLM",
						    "BartForConditionalGeneration",
						    "BartForQuestionAnswering",
						    "BartForSequenceClassification",
						    "BartModel",
						    "BartPretrainedModel",
						    "PretrainedBartModel",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase								=						[
						    "TFBartForConditionalGeneration",
						    "TFBartForSequenceClassification",
						    "TFBartModel",
						    "TFBartPretrainedModel",
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase								=						[
						    "FlaxBartDecoderPreTrainedModel",
						    "FlaxBartForCausalLM",
						    "FlaxBartForConditionalGeneration",
						    "FlaxBartForQuestionAnswering",
						    "FlaxBartForSequenceClassification",
						    "FlaxBartModel",
						    "FlaxBartPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
						from .tokenization_bart import BartTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_bart_fast import BartTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_bart import (
												    BART_PRETRAINED_MODEL_ARCHIVE_LIST,
												    BartForCausalLM,
												    BartForConditionalGeneration,
												    BartForQuestionAnswering,
												    BartForSequenceClassification,
												    BartModel,
												    BartPretrainedModel,
												    PretrainedBartModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_bart import (
												    TFBartForConditionalGeneration,
												    TFBartForSequenceClassification,
												    TFBartModel,
												    TFBartPretrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_bart import (
												    FlaxBartDecoderPreTrainedModel,
												    FlaxBartForCausalLM,
												    FlaxBartForConditionalGeneration,
												    FlaxBartForQuestionAnswering,
												    FlaxBartForSequenceClassification,
												    FlaxBartModel,
												    FlaxBartPreTrainedModel,
												)

else:
						import sys

						__lowerCamelCase								=						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


