


'''simple docstring'''






from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__A	:	Optional[Any]     =     logging.get_logger(__name__)

__A	:	Optional[Any]     =     {
    'facebook/data2vec-vision-base-ft': (
        'https://huggingface.co/facebook/data2vec-vision-base-ft/resolve/main/config.json'
    ),
}
class 						__UpperCamelCase	(						lowercase__							):
							lowercase			:		Union[str, Any]   		=  'data2vec-vision'





							def __init__(  self		:List[Any]  ,_UpperCamelCase		:Dict=7_6_8  ,_UpperCamelCase		:str=1_2  ,_UpperCamelCase		:str=1_2  ,_UpperCamelCase		:Tuple=3_0_7_2  ,_UpperCamelCase		:Optional[Any]="gelu"  ,_UpperCamelCase		:Optional[int]=0.0  ,_UpperCamelCase		:Any=0.0  ,_UpperCamelCase		:Optional[int]=0.02  ,_UpperCamelCase		:List[Any]=1E-1_2  ,_UpperCamelCase		:int=2_2_4  ,_UpperCamelCase		:Union[str, Any]=1_6  ,_UpperCamelCase		:Union[str, Any]=3  ,_UpperCamelCase		:Tuple=False  ,_UpperCamelCase		:Optional[int]=False  ,_UpperCamelCase		:Tuple=False  ,_UpperCamelCase		:Union[str, Any]=False  ,_UpperCamelCase		:int=0.1  ,_UpperCamelCase		:Union[str, Any]=0.1  ,_UpperCamelCase		:int=True  ,_UpperCamelCase		:Optional[Any]=[3, 5, 7, 1_1]  ,_UpperCamelCase		:Any=[1, 2, 3, 6]  ,_UpperCamelCase		:Any=True  ,_UpperCamelCase		:List[str]=0.4  ,_UpperCamelCase		:int=2_5_6  ,_UpperCamelCase		:Tuple=1  ,_UpperCamelCase		:Union[str, Any]=False  ,_UpperCamelCase		:Tuple=2_5_5  ,**_UpperCamelCase		:str  ,):
									super().__init__(**_UpperCamelCase			)

									snake_case_		:							List[str]			       =						hidden_size
									snake_case_		:							Tuple			       =						num_hidden_layers
									snake_case_		:							List[Any]			       =						num_attention_heads
									snake_case_		:							Union[str, Any]			       =						intermediate_size
									snake_case_		:							Dict			       =						hidden_act
									snake_case_		:							Optional[int]			       =						hidden_dropout_prob
									snake_case_		:							List[Any]			       =						attention_probs_dropout_prob
									snake_case_		:							Union[str, Any]			       =						initializer_range
									snake_case_		:							Tuple			       =						layer_norm_eps

									snake_case_		:							List[str]			       =						image_size
									snake_case_		:							Tuple			       =						patch_size
									snake_case_		:							str			       =						num_channels
									snake_case_		:							List[str]			       =						use_mask_token
									snake_case_		:							List[str]			       =						use_absolute_position_embeddings
									snake_case_		:							str			       =						use_relative_position_bias
									snake_case_		:							List[Any]			       =						use_shared_relative_position_bias
									snake_case_		:							int			       =						layer_scale_init_value
									snake_case_		:							str			       =						drop_path_rate
									snake_case_		:							Optional[int]			       =						use_mean_pooling
									# decode head attributes (semantic segmentation)
									snake_case_		:							Any			       =						out_indices
									snake_case_		:							List[str]			       =						pool_scales
									# auxiliary head attributes (semantic segmentation)
									snake_case_		:							Union[str, Any]			       =						use_auxiliary_head
									snake_case_		:							str			       =						auxiliary_loss_weight
									snake_case_		:							Any			       =						auxiliary_channels
									snake_case_		:							Dict			       =						auxiliary_num_convs
									snake_case_		:							int			       =						auxiliary_concat_input
									snake_case_		:							List[str]			       =						semantic_loss_ignore_index





class 						__UpperCamelCase	(						lowercase__							):
							lowercase			:		Optional[Any]   		=  version.parse('1.11'							)





							@property
							def 		a__   (  self		:Union[str, Any]			):
									return OrderedDict(
									    [
									        ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
									    ]			)





							@property
							def 		a__   (  self		:List[Any]			):
									return 1E-4



'''simple docstring'''






from typing import TYPE_CHECKING

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


__A	:	Tuple     =     {
    'configuration_audio_spectrogram_transformer': [
        'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'ASTConfig',
    ]
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__A	:	Tuple     =     [
							    'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'ASTForAudioClassification',
							    'ASTModel',
							    'ASTPreTrainedModel',
							]

try:
							if not is_speech_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__A	:	int     =     ['ASTFeatureExtractor']

if TYPE_CHECKING:
							from .configuration_audio_spectrogram_transformer import (
							    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    ASTConfig,
							)

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_audio_spectrogram_transformer import (
														    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ASTForAudioClassification,
														    ASTModel,
														    ASTPreTrainedModel,
														)

							try:
														if not is_speech_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
							import sys

							__A	:	Union[str, Any]     =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)