




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


lowercase_     :    Dict      =			logging.get_logger(__name__)

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






class    __lowerCAmelCase			(	UpperCAmelCase__			):
			snake_case_				:			Any								=					"vilt"







			def __init__(	self   :      Union[str, Any]   ,   snake_case__   :      Any=30_522   ,   snake_case__   :      Tuple=2   ,   snake_case__   :      List[Any]=2   ,   snake_case__   :      int=40   ,   snake_case__   :      Optional[Any]=768   ,   snake_case__   :      str=12   ,   snake_case__   :      Union[str, Any]=12   ,   snake_case__   :      Dict=3_072   ,   snake_case__   :      str="gelu"   ,   snake_case__   :      Optional[int]=0.0   ,   snake_case__   :      Optional[int]=0.0   ,   snake_case__   :      str=0.02   ,   snake_case__   :      int=1e-12   ,   snake_case__   :      Dict=384   ,   snake_case__   :      List[Any]=32   ,   snake_case__   :      Union[str, Any]=3   ,   snake_case__   :      Optional[Any]=True   ,   snake_case__   :      List[str]=-1   ,   snake_case__   :      List[str]=False   ,   snake_case__   :      Optional[int]=-1   ,   **snake_case__   :      List[Any]   ,   ):




									"""simple docstring"""


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

									_UpperCAmelCase													=					vocab_size
									_UpperCAmelCase													=					type_vocab_size
									_UpperCAmelCase													=					modality_type_vocab_size
									_UpperCAmelCase													=					max_position_embeddings

									_UpperCAmelCase													=					hidden_size
									_UpperCAmelCase													=					num_hidden_layers
									_UpperCAmelCase													=					num_attention_heads
									_UpperCAmelCase													=					intermediate_size
									_UpperCAmelCase													=					hidden_act
									_UpperCAmelCase													=					hidden_dropout_prob
									_UpperCAmelCase													=					attention_probs_dropout_prob
									_UpperCAmelCase													=					initializer_range
									_UpperCAmelCase													=					layer_norm_eps

									_UpperCAmelCase													=					image_size
									_UpperCAmelCase													=					patch_size
									_UpperCAmelCase													=					num_channels
									_UpperCAmelCase													=					qkv_bias
									_UpperCAmelCase													=					max_image_length
									_UpperCAmelCase													=					num_images












from typing import TYPE_CHECKING

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


lowercase_     :    int      =			{
    'configuration_videomae': ['VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VideoMAEConfig'],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_     :    List[str]      =			[
				    'VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'VideoMAEForPreTraining',
				    'VideoMAEModel',
				    'VideoMAEPreTrainedModel',
				    'VideoMAEForVideoClassification',
				]

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_     :    Any      =			['VideoMAEFeatureExtractor']
				lowercase_     :    Dict      =			['VideoMAEImageProcessor']

if TYPE_CHECKING:
				from .configuration_videomae import VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP, VideoMAEConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_videomae import (
								    VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST,
								    VideoMAEForPreTraining,
								    VideoMAEForVideoClassification,
								    VideoMAEModel,
								    VideoMAEPreTrainedModel,
								)

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_videomae import VideoMAEFeatureExtractor
								from .image_processing_videomae import VideoMAEImageProcessor

else:
				import sys

				lowercase_     :    int      =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




