



"""simple docstring"""






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


__snake_case				:  Union[str, Any] =       logging.get_logger(__name__)

__snake_case				:  List[str] =       {
    "facebook/timesformer": "https://huggingface.co/facebook/timesformer/resolve/main/config.json",
}



class      A__  (    __SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      'timesformer'

	def __init__(	self:						Dict			,     _SCREAMING_SNAKE_CASE:						Optional[Any]=224			,     _SCREAMING_SNAKE_CASE:						Optional[Any]=16			,     _SCREAMING_SNAKE_CASE:						List[str]=3			,     _SCREAMING_SNAKE_CASE:						str=8			,     _SCREAMING_SNAKE_CASE:						Union[str, Any]=768			,     _SCREAMING_SNAKE_CASE:						Optional[int]=12			,     _SCREAMING_SNAKE_CASE:						Optional[int]=12			,     _SCREAMING_SNAKE_CASE:						Any=3072			,     _SCREAMING_SNAKE_CASE:						Union[str, Any]="gelu"			,     _SCREAMING_SNAKE_CASE:						Optional[int]=0.0			,     _SCREAMING_SNAKE_CASE:						Dict=0.0			,     _SCREAMING_SNAKE_CASE:						List[str]=0.02			,     _SCREAMING_SNAKE_CASE:						List[str]=1e-6			,     _SCREAMING_SNAKE_CASE:						Union[str, Any]=True			,     _SCREAMING_SNAKE_CASE:						Any="divided_space_time"			,     _SCREAMING_SNAKE_CASE:						Tuple=0			,     **_SCREAMING_SNAKE_CASE:						Dict			,     )							->			int:

				"""simple docstring"""

				super().__init__(**__a)

				__lowerCAmelCase :    Union[str, Any]				=			image_size
				__lowerCAmelCase :    str				=			patch_size
				__lowerCAmelCase :    List[str]				=			num_channels
				__lowerCAmelCase :    Dict				=			num_frames

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

				__lowerCAmelCase :    List[str]				=			attention_type
				__lowerCAmelCase :    Tuple				=			drop_path_rate
'''simple docstring'''


from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
					if not (is_transformers_available() and is_torch_available()):
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					from ...utils.dummy_torch_and_transformers_objects import (
					    ImageTextPipelineOutput,
					    UniDiffuserPipeline,
					)
else:
					from .modeling_text_decoder import UniDiffuserTextDecoder
					from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
					from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline
