
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"""
 SCREAMING_SNAKE_CASE_				:					List[str]
 SCREAMING_SNAKE_CASE_				:					Optional[str]       						=None
 # Automatically constructed
 SCREAMING_SNAKE_CASE_				:					ClassVar[str]       						="dict"
 SCREAMING_SNAKE_CASE_				:					ClassVar[Any]       						=None
 SCREAMING_SNAKE_CASE_				:					str       						=field(default="Translation"			,	init=__magic_name__			,	repr=__magic_name__							)

 def __call__(						self			:			Optional[int]   ):






      """simple docstring"""



      return pa.struct({lang: pa.string() for lang in sorted(self.languages   )}   )






 def      __lowerCAmelCase  (						self			:			List[str]   ):






      """simple docstring"""



      from .features import Value

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




@dataclass
class       _lowerCAmelCase  :

 """simple docstring"""
 SCREAMING_SNAKE_CASE_				:					Optional[List]       						=None
 SCREAMING_SNAKE_CASE_				:					Optional[int]       						=None
 SCREAMING_SNAKE_CASE_				:					Optional[str]       						=None
 # Automatically constructed
 SCREAMING_SNAKE_CASE_				:					ClassVar[str]       						="dict"
 SCREAMING_SNAKE_CASE_				:					ClassVar[Any]       						=None
 SCREAMING_SNAKE_CASE_				:					str       						=field(default="TranslationVariableLanguages"			,	init=__magic_name__			,	repr=__magic_name__							)

 def      __lowerCAmelCase  (						self			:			List[str]   ):






      """simple docstring"""



      UpperCamelCase						    =					sorted(set(self.languages   )   ) if self.languages else None
      UpperCamelCase						    =					len(self.languages   ) if self.languages else None

 def __call__(						self			:			Optional[Any]   ):






      """simple docstring"""



      return pa.struct({'language': pa.list_(pa.string()   ), 'translation': pa.list_(pa.string()   )}   )

 def      __lowerCAmelCase  (						self			:			Union[str, Any]					, SCREAMING_SNAKE_CASE__			:			Tuple   ):






      """simple docstring"""



      UpperCamelCase						    =					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.
      UpperCamelCase						    =					[]
      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.
      UpperCamelCase    ,		UpperCamelCase						    =					zip(*sorted(SCREAMING_SNAKE_CASE__   )   )

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






 def      __lowerCAmelCase  (						self			:			Optional[int]   ):






      """simple docstring"""



      from .features import Sequence, Value

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




# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_snake_case      = {
    '''configuration_efficientnet''': [
        '''EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''EfficientNetConfig''',
        '''EfficientNetOnnxConfig''',
    ]
}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _snake_case      = ['''EfficientNetImageProcessor''']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _snake_case      = [
     '''EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''EfficientNetForImageClassification''',
     '''EfficientNetModel''',
     '''EfficientNetPreTrainedModel''',
 ]

if TYPE_CHECKING:
 from .configuration_efficientnet import (
     EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP,
     EfficientNetConfig,
     EfficientNetOnnxConfig,
 )

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .image_processing_efficientnet import EfficientNetImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_efficientnet import (
      EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST,
      EfficientNetForImageClassification,
      EfficientNetModel,
      EfficientNetPreTrainedModel,
  )

else:
 import sys

 _snake_case      = _LazyModule(__name__, globals()['''__file__'''], _import_structure)


