





def 			SCREAMING_SNAKE_CASE__							(    UpperCamelCase__:							Any      ):
		SCREAMING_SNAKE_CASE__								= word.upper()
		SCREAMING_SNAKE_CASE__								= 0
		SCREAMING_SNAKE_CASE__								= {}
		SCREAMING_SNAKE_CASE__								= []

		for letter in word:
				if letter not in letter_nums:
						SCREAMING_SNAKE_CASE__								= str(snake_case__      )
						next_num += 1
				word_pattern.append(letter_nums[letter]      )
		return ".".join(snake_case__      )


if __name__ == "__main__":
	import pprint
	import time

	_lowerCamelCase				 =     time.time()
	with open('dictionary.txt') as in_file:
		_lowerCamelCase				 =     in_file.read().splitlines()

	_lowerCamelCase				 =     {}
	for word in word_list:
		_lowerCamelCase				 =     get_word_pattern(word)
		if pattern in all_patterns:
			all_patterns[pattern].append(word)
		else:
			_lowerCamelCase				 =     [word]

	with open('word_patterns.txt', 'w') as out_file:
		out_file.write(pprint.pformat(all_patterns))

	_lowerCamelCase				 =     round(time.time() - start_time, 2)
	print(F'''Done!  {len(all_patterns):,} word patterns found in {total_time} seconds.''')
	# Done!  9,581 word patterns found in 0.58 seconds.






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 					UpperCamelCase_    (       UpperCamelCase__      ):
							lowerCamelCase_          =   "videomae"


							def __init__(							self      :Dict							,			__A      :List[str]=224							,			__A      :List[Any]=16							,			__A      :int=3							,			__A      :Optional[Any]=16							,			__A      :Optional[int]=2							,			__A      :Optional[Any]=768							,			__A      :List[str]=12							,			__A      :Optional[Any]=12							,			__A      :List[str]=3072							,			__A      :Tuple="gelu"							,			__A      :Optional[int]=0.0							,			__A      :Union[str, Any]=0.0							,			__A      :int=0.0_2							,			__A      :Union[str, Any]=1E-12							,			__A      :Optional[Any]=True							,			__A      :Union[str, Any]=True							,			__A      :Optional[int]=6							,			__A      :Tuple=384							,			__A      :str=4							,			__A      :List[str]=1536							,			__A      :Dict=True							,			**__A      :int							,			)				->				Optional[int]:



									"""simple docstring"""



									super().__init__(**__A						)

									SCREAMING_SNAKE_CASE__								= image_size
									SCREAMING_SNAKE_CASE__								= patch_size
									SCREAMING_SNAKE_CASE__								= num_channels
									SCREAMING_SNAKE_CASE__								= num_frames
									SCREAMING_SNAKE_CASE__								= tubelet_size

									SCREAMING_SNAKE_CASE__								= hidden_size
									SCREAMING_SNAKE_CASE__								= num_hidden_layers
									SCREAMING_SNAKE_CASE__								= num_attention_heads
									SCREAMING_SNAKE_CASE__								= intermediate_size
									SCREAMING_SNAKE_CASE__								= hidden_act
									SCREAMING_SNAKE_CASE__								= hidden_dropout_prob
									SCREAMING_SNAKE_CASE__								= attention_probs_dropout_prob
									SCREAMING_SNAKE_CASE__								= initializer_range
									SCREAMING_SNAKE_CASE__								= layer_norm_eps
									SCREAMING_SNAKE_CASE__								= qkv_bias
									SCREAMING_SNAKE_CASE__								= use_mean_pooling

									SCREAMING_SNAKE_CASE__								= decoder_num_attention_heads
									SCREAMING_SNAKE_CASE__								= decoder_hidden_size
									SCREAMING_SNAKE_CASE__								= decoder_num_hidden_layers
									SCREAMING_SNAKE_CASE__								= decoder_intermediate_size
									SCREAMING_SNAKE_CASE__								= norm_pix_loss