from typing import TYPE_CHECKING

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


_UpperCamelCase				:		Union[str, Any]       			=		{
    'configuration_led': ['LED_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LEDConfig'],
    'tokenization_led': ['LEDTokenizer'],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase				:		Tuple       			=		['LEDTokenizerFast']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase				:		int       			=		[
         'LED_PRETRAINED_MODEL_ARCHIVE_LIST',
         'LEDForConditionalGeneration',
         'LEDForQuestionAnswering',
         'LEDForSequenceClassification',
         'LEDModel',
         'LEDPreTrainedModel',
     ]


try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase				:		List[Any]       			=		['TFLEDForConditionalGeneration', 'TFLEDModel', 'TFLEDPreTrainedModel']


if TYPE_CHECKING:
     from .configuration_led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig
     from .tokenization_led import LEDTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_led_fast import LEDTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_led import (
              LED_PRETRAINED_MODEL_ARCHIVE_LIST,
              LEDForConditionalGeneration,
              LEDForQuestionAnswering,
              LEDForSequenceClassification,
              LEDModel,
              LEDPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel

else:
     import sys

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




'''simple docstring'''




def 						__snake_case (       lowerCAmelCase       :     str			):
 __UpperCAmelCase         =					5381
 for x in s:
  __UpperCAmelCase         =					((hash_value << 5) + hash_value) + ord(lowerCAmelCase			)
 return hash_value & 0Xffff_ffff



