



from typing import TYPE_CHECKING

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


snake_case_			:     str  	=  {
    'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
    'configuration_data2vec_text': [
        'DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Data2VecTextConfig',
        'Data2VecTextOnnxConfig',
    ],
    'configuration_data2vec_vision': [
        'DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Data2VecVisionConfig',
        'Data2VecVisionOnnxConfig',
    ],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_			:     int  	=  [
					    'DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'Data2VecAudioForAudioFrameClassification',
					    'Data2VecAudioForCTC',
					    'Data2VecAudioForSequenceClassification',
					    'Data2VecAudioForXVector',
					    'Data2VecAudioModel',
					    'Data2VecAudioPreTrainedModel',
					]
					snake_case_			:     Tuple  	=  [
					    'DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'Data2VecTextForCausalLM',
					    'Data2VecTextForMaskedLM',
					    'Data2VecTextForMultipleChoice',
					    'Data2VecTextForQuestionAnswering',
					    'Data2VecTextForSequenceClassification',
					    'Data2VecTextForTokenClassification',
					    'Data2VecTextModel',
					    'Data2VecTextPreTrainedModel',
					]
					snake_case_			:     Optional[int]  	=  [
					    'DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'Data2VecVisionForImageClassification',
					    'Data2VecVisionForMaskedImageModeling',
					    'Data2VecVisionForSemanticSegmentation',
					    'Data2VecVisionModel',
					    'Data2VecVisionPreTrainedModel',
					]

if is_tf_available():
					snake_case_			:     Union[str, Any]  	=  [
					    'TFData2VecVisionForImageClassification',
					    'TFData2VecVisionForSemanticSegmentation',
					    'TFData2VecVisionModel',
					    'TFData2VecVisionPreTrainedModel',
					]

if TYPE_CHECKING:
					from .configuration_dataavec_audio import DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP, DataaVecAudioConfig
					from .configuration_dataavec_text import (
					    DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    DataaVecTextConfig,
					    DataaVecTextOnnxConfig,
					)
					from .configuration_dataavec_vision import (
					    DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    DataaVecVisionConfig,
					    DataaVecVisionOnnxConfig,
					)

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_dataavec_audio import (
										    DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST,
										    DataaVecAudioForAudioFrameClassification,
										    DataaVecAudioForCTC,
										    DataaVecAudioForSequenceClassification,
										    DataaVecAudioForXVector,
										    DataaVecAudioModel,
										    DataaVecAudioPreTrainedModel,
										)
										from .modeling_dataavec_text import (
										    DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    DataaVecTextForCausalLM,
										    DataaVecTextForMaskedLM,
										    DataaVecTextForMultipleChoice,
										    DataaVecTextForQuestionAnswering,
										    DataaVecTextForSequenceClassification,
										    DataaVecTextForTokenClassification,
										    DataaVecTextModel,
										    DataaVecTextPreTrainedModel,
										)
										from .modeling_dataavec_vision import (
										    DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST,
										    DataaVecVisionForImageClassification,
										    DataaVecVisionForMaskedImageModeling,
										    DataaVecVisionForSemanticSegmentation,
										    DataaVecVisionModel,
										    DataaVecVisionPreTrainedModel,
										)
					if is_tf_available():
										from .modeling_tf_dataavec_vision import (
										    TFDataaVecVisionForImageClassification,
										    TFDataaVecVisionForSemanticSegmentation,
										    TFDataaVecVisionModel,
										    TFDataaVecVisionPreTrainedModel,
										)

else:
					import sys

					snake_case_			:     List[Any]  	=  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







'''simple docstring'''
from __future__ import annotations






def A__   (					UpperCAmelCase_							):
						if not nums:
												return 0
						_UpperCamelCase :		Any			    =       nums[0]
						_UpperCamelCase :		Optional[int]			    =       0
						for num in nums[1:]:
												_UpperCamelCase    ,      _UpperCamelCase :		Optional[Any]			    =       (
												    max_excluding + num,
												    max(UpperCAmelCase_  ,  UpperCAmelCase_							),
												)
						return max(UpperCAmelCase_  ,  UpperCAmelCase_							)


if __name__ == "__main__":
					import doctest

					doctest.testmod()


