
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase__        =						logging.get_logger(__name__)

lowerCamelCase__        =						{
    'dandelin/vilt-b32-mlm': 'https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json'
}







class 	A__				(	_lowercase      ):
				lowercase            =    'vilt'






				def __init__(		self   : int       ,	a   : Union[str, Any]=30_522       ,	a   : Tuple=2       ,	a   : str=2       ,	a   : Tuple=40       ,	a   : Dict=768       ,	a   : Union[str, Any]=12       ,	a   : List[str]=12       ,	a   : Optional[Any]=3_072       ,	a   : Union[str, Any]="gelu"       ,	a   : List[Any]=0.0       ,	a   : List[str]=0.0       ,	a   : List[Any]=0.0_2       ,	a   : Dict=1E-12       ,	a   : Optional[Any]=384       ,	a   : Optional[int]=32       ,	a   : Optional[Any]=3       ,	a   : Tuple=True       ,	a   : str=-1       ,	a   : Any=False       ,	a   : List[str]=-1       ,	**a   : Optional[int]       ,	):






							'''simple docstring'''







							super().__init__(tie_word_embeddings=snake_case__       ,	**snake_case__  )

							lowerCAmelCase__ : Dict   =						vocab_size
							lowerCAmelCase__ : Any   =						type_vocab_size
							lowerCAmelCase__ : Tuple   =						modality_type_vocab_size
							lowerCAmelCase__ : Union[str, Any]   =						max_position_embeddings

							lowerCAmelCase__ : List[Any]   =						hidden_size
							lowerCAmelCase__ : Optional[Any]   =						num_hidden_layers
							lowerCAmelCase__ : Dict   =						num_attention_heads
							lowerCAmelCase__ : Dict   =						intermediate_size
							lowerCAmelCase__ : int   =						hidden_act
							lowerCAmelCase__ : List[str]   =						hidden_dropout_prob
							lowerCAmelCase__ : List[Any]   =						attention_probs_dropout_prob
							lowerCAmelCase__ : Optional[Any]   =						initializer_range
							lowerCAmelCase__ : int   =						layer_norm_eps

							lowerCAmelCase__ : Dict   =						image_size
							lowerCAmelCase__ : Any   =						patch_size
							lowerCAmelCase__ : int   =						num_channels
							lowerCAmelCase__ : int   =						qkv_bias
							lowerCAmelCase__ : str   =						max_image_length
							lowerCAmelCase__ : str   =						num_images

"""simple docstring"""
from typing import TYPE_CHECKING

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


lowercase		:    Dict			=       {
    'configuration_mobilenet_v1': [
        'MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MobileNetV1Config',
        'MobileNetV1OnnxConfig',
    ],
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    Optional[int]			=       ['MobileNetV1FeatureExtractor']
			lowercase		:    Union[str, Any]			=       ['MobileNetV1ImageProcessor']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    Tuple			=       [
			    'MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'MobileNetV1ForImageClassification',
			    'MobileNetV1Model',
			    'MobileNetV1PreTrainedModel',
			    'load_tf_weights_in_mobilenet_v1',
			]


if TYPE_CHECKING:
			from .configuration_mobilenet_va import (
			    MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    MobileNetVaConfig,
			    MobileNetVaOnnxConfig,
			)

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
						from .image_processing_mobilenet_va import MobileNetVaImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_mobilenet_va import (
						    MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST,
						    MobileNetVaForImageClassification,
						    MobileNetVaModel,
						    MobileNetVaPreTrainedModel,
						    load_tf_weights_in_mobilenet_va,
						)


else:
			import sys

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