






from __future__ import annotations

from enum import Enum, unique
from typing import TypeVar

# Create a generic variable that can be 'Enum', or any subclass.
lowerCamelCase_		  =						TypeVar("""T""", bound="""Enum""")




@unique
class 							a_				(		a_	):


       '''simple docstring'''






       __a:			Optional[Any]									=					8_0
       __a:			Any									=					7_0
       __a:			Union[str, Any]									=					6_0
       __a:			Tuple									=					5_0
       __a:			Dict									=					4_0
       __a:			Tuple									=					3_0
       __a:			Any									=					2_0
       __a:			List[str]									=					1_0




@unique
class 							a_				(		a_	):


       '''simple docstring'''






       __a:			Any									=					2_4
       __a:			int									=					2_1
       __a:			Tuple									=					1_8
       __a:			List[str]									=					1_5
       __a:			List[str]									=					1_2
       __a:			Optional[int]									=					9
       __a:			Tuple									=					6
       __a:			List[Any]									=					3
       __a:			int									=					2
       __a:			Optional[Any]									=					1
       __a:			Dict									=					-1
       __a:			Dict									=					-2
       __a:			Union[str, Any]									=					-3
       __a:			List[Any]									=					-6
       __a:			Optional[Any]									=					-9
       __a:			Any									=					-1_2
       __a:			int									=					-1_5
       __a:			str									=					-1_8
       __a:			List[Any]									=					-2_1
       __a:			List[Any]									=					-2_4

       @classmethod
       def   _lowercase (	cls     )      ->      dict:
              '''simple docstring'''

              return {unit.name: unit.value for unit in cls if unit.value > 0}






       @classmethod
       def   _lowercase (	cls     )      ->      dict:
              '''simple docstring'''

              return {unit.name: unit.value for unit in cls if unit.value < 0}


def   lowerCamelCase      (		a_			)			->    str:
       lowerCAmelCase_       		=  SIUnit.get_positive() if value > 0 else SIUnit.get_negative()
       for name_prefix, value_prefix in prefixes.items():
              lowerCAmelCase_       		=  value / (10**value_prefix)
              if numerical_part > 1:
                     return F'''{numerical_part!s} {name_prefix}'''
       return str(a_			)
def   lowerCamelCase      (		a_			)			->    str:
       for prefix in BinaryUnit:
              lowerCAmelCase_       		=  value / (2**prefix.value)
              if numerical_part > 1:
                     return F'''{numerical_part!s} {prefix.name}'''
       return str(a_			)


if __name__ == "__main__":
  import doctest

  doctest.testmod()











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase_		  =						{
    """configuration_prophetnet""": ["""PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ProphetNetConfig"""],
    """tokenization_prophetnet""": ["""ProphetNetTokenizer"""],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase_		  =						[
		    """PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """ProphetNetDecoder""",
		    """ProphetNetEncoder""",
		    """ProphetNetForCausalLM""",
		    """ProphetNetForConditionalGeneration""",
		    """ProphetNetModel""",
		    """ProphetNetPreTrainedModel""",
		]


if TYPE_CHECKING:
		from .configuration_prophetnet import PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ProphetNetConfig
		from .tokenization_prophetnet import ProphetNetTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_prophetnet import (
				    PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ProphetNetDecoder,
				    ProphetNetEncoder,
				    ProphetNetForCausalLM,
				    ProphetNetForConditionalGeneration,
				    ProphetNetModel,
				    ProphetNetPreTrainedModel,
				)

else:
		import sys

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



