

from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union

import pyarrow as pa


if TYPE_CHECKING:
						from .features import FeatureType



@dataclass
class   __lowercase    :




			"""simple docstring"""







			_UpperCAmelCase       :							List[Any]      							=					42
			_UpperCAmelCase       :							int      							=					None
			# Automatically constructed
			_UpperCAmelCase       :							Any      							=					'''dict'''
			_UpperCAmelCase       :							Optional[Any]      							=					None
			_UpperCAmelCase       :							int      							=					field(default='''Translation'''		,	init=UpperCAmelCase_		,	repr=UpperCAmelCase_     )



			def __call__(			self  :					Union[str, Any]):
									return pa.struct({lang: pa.string() for lang in sorted(self.languages)})




			def 	_SCREAMING_SNAKE_CASE      (			self  :					str):
									from .features import Value

									return {k: Value("string") for k in sorted(self.languages)}







@dataclass
class   __lowercase    :




			"""simple docstring"""







			_UpperCAmelCase       :							int      							=					None
			_UpperCAmelCase       :							Any      							=					None
			_UpperCAmelCase       :							List[str]      							=					None
			# Automatically constructed
			_UpperCAmelCase       :							List[Any]      							=					'''dict'''
			_UpperCAmelCase       :							List[Any]      							=					None
			_UpperCAmelCase       :							Dict      							=					field(default='''TranslationVariableLanguages'''		,	init=UpperCAmelCase_		,	repr=UpperCAmelCase_     )



			def 	_SCREAMING_SNAKE_CASE      (			self  :					Any):
									SCREAMING_SNAKE_CASE_:			Any  		=	sorted(set(self.languages)) if self.languages else None
									SCREAMING_SNAKE_CASE_:			Optional[int]  		=	len(self.languages) if self.languages else None



			def __call__(			self  :					Optional[int]):
									return pa.struct({"language": pa.list_(pa.string()), "translation": pa.list_(pa.string())})



			def 	_SCREAMING_SNAKE_CASE      (			self  :					List[str]       ,						lowerCAmelCase__  :					Union[str, Any]):
									SCREAMING_SNAKE_CASE_:			List[str]  		=	set(self.languages)
									if self.languages and set(__A) - lang_set:
															raise ValueError(
															    F"Some languages in example ({', '.join(sorted(set(__A) - lang_set))}) are not in valid set ({', '.join(__A)}).")

									# Convert dictionary into tuples, splitting out cases where there are
									# multiple translations for a single language.
									SCREAMING_SNAKE_CASE_:			Optional[int]  		=	[]
									for lang, text in translation_dict.items():
															if isinstance(__A       ,						__A):
																					translation_tuples.append((lang, text))
															else:
																					translation_tuples.extend([(lang, el) for el in text])

        # Ensure translations are in ascending order by language code.
									SCREAMING_SNAKE_CASE_		,   SCREAMING_SNAKE_CASE_:			Optional[Any]  		=	zip(*sorted(__A))

									return {"language": languages, "translation": translations}




			def 	_SCREAMING_SNAKE_CASE      (			self  :					int):
									from .features import Sequence, Value

									return {
									    "language": Sequence(Value("string")),
									    "translation": Sequence(Value("string")),
									}









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase							:  Optional[int]            =						{
    """configuration_nllb_moe""": [
        """NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """NllbMoeConfig""",
    ]
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase							:  Optional[int]            =						[
						    """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

						lowerCAmelCase							:  Any            =						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






