


'''simple docstring'''







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 			__lowerCamelCase			:
    """simple docstring"""
    a													=   42
    a													=   None
    # Automatically constructed
    a													=   "dict"
    a													=   None
    a													=   field(default="Translation"    , init=a_    , repr=a_	)


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


    def        A   (  self      :							Optional[int]):
           from .features import Value

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




@dataclass
class 			__lowerCamelCase			:
    """simple docstring"""
    a													=   None
    a													=   None
    a													=   None
    # Automatically constructed
    a													=   "dict"
    a													=   None
    a													=   field(default="TranslationVariableLanguages"    , init=a_    , repr=a_	)


    def        A   (  self      :							Union[str, Any]):
           _A					:     List[str]     = sorted(set(self.languages)) if self.languages else None
           _A					:     Tuple     = len(self.languages) if self.languages else None


    def __call__(  self      :							List[Any]):
           return pa.struct({'language': pa.list_(pa.string()), 'translation': pa.list_(pa.string())})


    def        A   (  self      :							Optional[int]				,							SCREAMING_SNAKE_CASE      :							Union[str, Any]):
           _A					:     Dict     = set(self.languages)
           if self.languages and set(SCREAMING_SNAKE_CASE) - lang_set:
                  raise ValueError(
                      F'Some languages in example ({", ".join(sorted(set(SCREAMING_SNAKE_CASE) - lang_set))}) are not in valid set ({", ".join(SCREAMING_SNAKE_CASE)}).')

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

        # Ensure translations are in ascending order by language code.
           _A  ,			_A					:     Any     = zip(*sorted(SCREAMING_SNAKE_CASE))

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


    def        A   (  self      :							Optional[int]):
           from .features import Sequence, Value

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










'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


A				:					Optional[int]    						=			{
    '''configuration_mask2former''': [
        '''MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''Mask2FormerConfig''',
    ],
}

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A				:					Tuple    						=			['''Mask2FormerImageProcessor''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A				:					Dict    						=			[
       '''MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''Mask2FormerForUniversalSegmentation''',
       '''Mask2FormerModel''',
       '''Mask2FormerPreTrainedModel''',
   ]

if TYPE_CHECKING:
   from .configuration_maskaformer import MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskaFormerConfig

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .image_processing_maskaformer import MaskaFormerImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_maskaformer import (
          MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          MaskaFormerForUniversalSegmentation,
          MaskaFormerModel,
          MaskaFormerPreTrainedModel,
      )


else:
   import sys

   A				:					Optional[Any]    						=			_LazyModule(__name__, globals()['''__file__'''], _import_structure)






