



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


snake_case_			=     logging.get_logger(__name__)

snake_case_			=     {
    """facebook/vit-mae-base""": """https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json""",
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}


class 	a__     (				_lowercase	):
	__magic_name__		:    str	    =     "vit_mae"


	def __init__(self : Optional[Any],					__UpperCAmelCase : Any=768,					__UpperCAmelCase : Any=12,					__UpperCAmelCase : List[Any]=12,					__UpperCAmelCase : Dict=3072,					__UpperCAmelCase : Union[str, Any]="gelu",					__UpperCAmelCase : List[str]=0.0,					__UpperCAmelCase : Optional[int]=0.0,					__UpperCAmelCase : List[str]=0.02,					__UpperCAmelCase : List[Any]=1e-12,					__UpperCAmelCase : int=224,					__UpperCAmelCase : Dict=16,					__UpperCAmelCase : str=3,					__UpperCAmelCase : Dict=True,					__UpperCAmelCase : List[Any]=16,					__UpperCAmelCase : str=512,					__UpperCAmelCase : Tuple=8,					__UpperCAmelCase : Optional[Any]=2048,					__UpperCAmelCase : str=0.75,					__UpperCAmelCase : str=False,					**__UpperCAmelCase : Union[str, Any],					)     ->			Optional[int]:

					"""simple docstring"""

					super().__init__(**__UpperCAmelCase      )

					SCREAMING_SNAKE_CASE  :						List[str]      					= hidden_size
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= num_hidden_layers
					SCREAMING_SNAKE_CASE  :						int      					= num_attention_heads
					SCREAMING_SNAKE_CASE  :						List[Any]      					= intermediate_size
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= hidden_act
					SCREAMING_SNAKE_CASE  :						int      					= hidden_dropout_prob
					SCREAMING_SNAKE_CASE  :						List[Any]      					= attention_probs_dropout_prob
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= initializer_range
					SCREAMING_SNAKE_CASE  :						List[str]      					= layer_norm_eps
					SCREAMING_SNAKE_CASE  :						str      					= image_size
					SCREAMING_SNAKE_CASE  :						List[str]      					= patch_size
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= num_channels
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= qkv_bias
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= decoder_num_attention_heads
					SCREAMING_SNAKE_CASE  :						Any      					= decoder_hidden_size
					SCREAMING_SNAKE_CASE  :						Any      					= decoder_num_hidden_layers
					SCREAMING_SNAKE_CASE  :						List[str]      					= decoder_intermediate_size
					SCREAMING_SNAKE_CASE  :						int      					= mask_ratio
					SCREAMING_SNAKE_CASE  :						int      					= norm_pix_loss









'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case_			=     {
    """configuration_timesformer""": ["""TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TimesformerConfig"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case_			=     [
	    """TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """TimesformerModel""",
	    """TimesformerForVideoClassification""",
	    """TimesformerPreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_timesformer import (
		    TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TimesformerForVideoClassification,
		    TimesformerModel,
		    TimesformerPreTrainedModel,
		)

else:
	import sys

	snake_case_			=     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




