






"""simple docstring"""





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


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

A__       :			List[str]=						{
    """MCG-NJU/videomae-base""": """https://huggingface.co/MCG-NJU/videomae-base/resolve/main/config.json""",
}
class  __lowerCamelCase     (	_a	):
   a   :					int			    ="""videomae"""

   def __init__(       self			,					snake_case_=224			,					snake_case_=16			,					snake_case_=3			,					snake_case_=16			,					snake_case_=2			,					snake_case_=768			,					snake_case_=12			,					snake_case_=12			,					snake_case_=3072			,					snake_case_="gelu"			,					snake_case_=0.0			,					snake_case_=0.0			,					snake_case_=0.02			,					snake_case_=1E-12			,					snake_case_=True			,					snake_case_=True			,					snake_case_=6			,					snake_case_=384			,					snake_case_=4			,					snake_case_=1536			,					snake_case_=True			,					**snake_case_			,					)		->							List[Any]:
       super().__init__(**snake_case_   )

       UpperCamelCase__								=     image_size
       UpperCamelCase__								=     patch_size
       UpperCamelCase__								=     num_channels
       UpperCamelCase__								=     num_frames
       UpperCamelCase__								=     tubelet_size

       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__								=     qkv_bias
       UpperCamelCase__								=     use_mean_pooling

       UpperCamelCase__								=     decoder_num_attention_heads
       UpperCamelCase__								=     decoder_hidden_size
       UpperCamelCase__								=     decoder_num_hidden_layers
       UpperCamelCase__								=     decoder_intermediate_size
       UpperCamelCase__								=     norm_pix_loss












"""simple docstring"""





import torch

from transformers import PreTrainedModel

from .custom_configuration import CustomConfig, NoSuperInitConfig
class  __lowerCamelCase     (	_a	):
   a   :					List[Any]			    =CustomConfig

   def __init__(       self			,					snake_case_   )		->							str:
       super().__init__(snake_case_   )
       UpperCamelCase__								=     torch.nn.Linear(config.hidden_size			,					config.hidden_size   )

   def     SCREAMING_SNAKE_CASE__			(       self			,					snake_case_   )		->							Optional[int]:
       return self.linear(snake_case_   )







   def     SCREAMING_SNAKE_CASE__			(       self			,					snake_case_   )		->							Union[str, Any]:
       pass







class  __lowerCamelCase     (	_a	):
   a   :					Optional[int]			    =NoSuperInitConfig

   def __init__(       self			,					snake_case_   )		->							Optional[int]:
       super().__init__(snake_case_   )
       UpperCamelCase__								=     torch.nn.Linear(config.attribute			,					config.attribute   )

   def     SCREAMING_SNAKE_CASE__			(       self			,					snake_case_   )		->							int:
       return self.linear(snake_case_   )







   def     SCREAMING_SNAKE_CASE__			(       self			,					snake_case_   )		->							Union[str, Any]:
       pass




