


'''simple docstring'''






from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate




@dataclass(frozen=_SCREAMING_SNAKE_CASE    )
class 	a       (       _SCREAMING_SNAKE_CASE    ):
	# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
	_lowerCAmelCase	   =		field(default="""summarization"""					,			metadata={"""include_in_asdict_even_if_is_default""": True}    )
	_lowerCAmelCase	   =		Features({"""text""": Value("""string"""    )}    )
	_lowerCAmelCase	   =		Features({"""summary""": Value("""string"""    )}    )
	_lowerCAmelCase	   =		"""text"""
	_lowerCAmelCase	   =		"""summary"""
	@property
	def 							__UpperCAmelCase						(	self  )   ->							Dict[str, str]:
						return {self.text_column: "text", self.summary_column: "summary"}





'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_   :      str				    =      {
    "configuration_nllb_moe": [
        "NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "NllbMoeConfig",
    ]
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_   :      Tuple				    =      [
     "NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST",
     "NllbMoeForConditionalGeneration",
     "NllbMoeModel",
     "NllbMoePreTrainedModel",
     "NllbMoeTop2Router",
     "NllbMoeSparseMLP",
 ]


if TYPE_CHECKING:
 from .configuration_nllb_moe import (
     NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP,
     NllbMoeConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_nllb_moe import (
      NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST,
      NllbMoeForConditionalGeneration,
      NllbMoeModel,
      NllbMoePreTrainedModel,
      NllbMoeSparseMLP,
      NllbMoeTopaRouter,
  )


else:
 import sys

 a_   :      str				    =      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

