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


_lowerCamelCase        =logging.get_logger(__name__)

_lowerCamelCase        ={
    """MCG-NJU/videomae-base""": """https://huggingface.co/MCG-NJU/videomae-base/resolve/main/config.json""",
}





class 							A__		(     __SCREAMING_SNAKE_CASE):
						_UpperCAmelCase    :   int   	=      """videomae"""
						def __init__(				self   ,  __magic_name__=2_2_4   ,  __magic_name__=1_6   ,  __magic_name__=3   ,  __magic_name__=1_6   ,  __magic_name__=2   ,  __magic_name__=7_6_8   ,  __magic_name__=1_2   ,  __magic_name__=1_2   ,  __magic_name__=3_0_7_2   ,  __magic_name__="gelu"   ,  __magic_name__=0.0   ,  __magic_name__=0.0   ,  __magic_name__=0.02   ,  __magic_name__=1e-12   ,  __magic_name__=True   ,  __magic_name__=True   ,  __magic_name__=6   ,  __magic_name__=3_8_4   ,  __magic_name__=4   ,  __magic_name__=1_5_3_6   ,  __magic_name__=True   ,  **__magic_name__   ,  ):
							super().__init__(**__magic_name__				)

							lowerCamelCase		:     str          =				image_size
							lowerCamelCase		:     Tuple          =				patch_size
							lowerCamelCase		:     Union[str, Any]          =				num_channels
							lowerCamelCase		:     Optional[int]          =				num_frames
							lowerCamelCase		:     int          =				tubelet_size

							lowerCamelCase		:     Optional[int]          =				hidden_size
							lowerCamelCase		:     Union[str, Any]          =				num_hidden_layers
							lowerCamelCase		:     int          =				num_attention_heads
							lowerCamelCase		:     List[Any]          =				intermediate_size
							lowerCamelCase		:     List[Any]          =				hidden_act
							lowerCamelCase		:     List[Any]          =				hidden_dropout_prob
							lowerCamelCase		:     Optional[Any]          =				attention_probs_dropout_prob
							lowerCamelCase		:     Any          =				initializer_range
							lowerCamelCase		:     List[Any]          =				layer_norm_eps
							lowerCamelCase		:     str          =				qkv_bias
							lowerCamelCase		:     List[str]          =				use_mean_pooling

							lowerCamelCase		:     List[str]          =				decoder_num_attention_heads
							lowerCamelCase		:     Optional[int]          =				decoder_hidden_size
							lowerCamelCase		:     Optional[Any]          =				decoder_num_hidden_layers
							lowerCamelCase		:     Dict          =				decoder_intermediate_size
							lowerCamelCase		:     str          =				norm_pix_loss






from collections import defaultdict





def    _a (						lowerCamelCase							):
 lowerCamelCase		:     defaultdict[str, int]          =				defaultdict(lowerCamelCase							)
 # Creating a dictionary containing count of each word
 for word in sentence.split():
  occurrence[word] += 1
 return occurrence


if __name__ == "__main__":
      for word, count in word_occurrence("""INPUT STRING""").items():
            print(f'''{word}: {count}''')




