




"""simple docstring"""





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


A				=							logging.get_logger(__name__)

A				=							{
    """google/vivit-b-16x2-kinetics400""": (
        """https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"""
    ),
    # See all Vivit models at https://huggingface.co/models?filter=vivit
}



class   a__					(						__magic_name__ ):
			lowercase_		=						"vivit"


			def __init__(   self   :     Union[str, Any]   ,	UpperCamelCase_   :     Dict=224   ,	UpperCamelCase_   :     Optional[Any]=32   ,	UpperCamelCase_   :     List[Any]=[2, 16, 16]   ,	UpperCamelCase_   :     str=3   ,	UpperCamelCase_   :     Tuple=768   ,	UpperCamelCase_   :     Tuple=12   ,	UpperCamelCase_   :     Any=12   ,	UpperCamelCase_   :     Any=3072   ,	UpperCamelCase_   :     int="gelu_fast"   ,	UpperCamelCase_   :     Any=0.0   ,	UpperCamelCase_   :     Tuple=0.0   ,	UpperCamelCase_   :     Optional[int]=0.02   ,	UpperCamelCase_   :     Tuple=1e-06   ,	UpperCamelCase_   :     Optional[int]=True   ,	**UpperCamelCase_   :     int   ,	):


						"""simple docstring"""




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

						__UpperCAmelCase						:			Dict												=       image_size
						__UpperCAmelCase						:			Optional[Any]												=       num_frames
						__UpperCAmelCase						:			List[Any]												=       tubelet_size
						__UpperCAmelCase						:			Optional[Any]												=       num_channels
						__UpperCAmelCase						:			Optional[int]												=       qkv_bias

						super().__init__(**UpperCamelCase_)









"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


a		:					Optional[Any]	      =     {
    '''configuration_owlvit''': [
        '''OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''OwlViTConfig''',
        '''OwlViTOnnxConfig''',
        '''OwlViTTextConfig''',
        '''OwlViTVisionConfig''',
    ],
    '''processing_owlvit''': ['''OwlViTProcessor'''],
}


try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a		:					str	      =     ['''OwlViTFeatureExtractor''']
		a		:					List[Any]	      =     ['''OwlViTImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a		:					List[Any]	      =     [
		    '''OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''OwlViTModel''',
		    '''OwlViTPreTrainedModel''',
		    '''OwlViTTextModel''',
		    '''OwlViTVisionModel''',
		    '''OwlViTForObjectDetection''',
		]

if TYPE_CHECKING:
		from .configuration_owlvit import (
		    OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    OwlViTConfig,
		    OwlViTOnnxConfig,
		    OwlViTTextConfig,
		    OwlViTVisionConfig,
		)
		from .processing_owlvit import OwlViTProcessor

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_owlvit import OwlViTFeatureExtractor
				from .image_processing_owlvit import OwlViTImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_owlvit import (
				    OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    OwlViTForObjectDetection,
				    OwlViTModel,
				    OwlViTPreTrainedModel,
				    OwlViTTextModel,
				    OwlViTVisionModel,
				)

else:
		import sys

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


