




"""simple docstring"""






import copy
import os
from typing import TYPE_CHECKING, List, Union


if TYPE_CHECKING:
				pass

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


UpperCamelCase__						=			logging.get_logger(__name__)

UpperCamelCase__						=			{
    'kakaobrain/align-base': 'https://huggingface.co/kakaobrain/align-base/resolve/main/config.json',
}




class   a__			(       UpperCamelCase_  ):
						snake_case__             = '''align_text_model'''





						def __init__(							self      :	Tuple     ,a__      :	Union[str, Any]=3_0522     ,a__      :	Any=768     ,a__      :	Any=12     ,a__      :	Optional[Any]=12     ,a__      :	Any=3072     ,a__      :	Any="gelu"     ,a__      :	Tuple=0.1     ,a__      :	Union[str, Any]=0.1     ,a__      :	List[str]=512     ,a__      :	Dict=2     ,a__      :	Optional[Any]=0.02     ,a__      :	Any=1E-12     ,a__      :	List[str]=0     ,a__      :	Optional[int]="absolute"     ,a__      :	Optional[int]=True     ,**a__      :	List[Any]     ,)						->       Optional[int]:




											"""simple docstring"""







											super().__init__(**_lowerCAmelCase)

											_lowerCAmelCase:Optional[Any]									=  vocab_size
											_lowerCAmelCase:Optional[int]									=  hidden_size
											_lowerCAmelCase:Optional[Any]									=  num_hidden_layers
											_lowerCAmelCase:Optional[Any]									=  num_attention_heads
											_lowerCAmelCase:Dict									=  hidden_act
											_lowerCAmelCase:List[str]									=  intermediate_size
											_lowerCAmelCase:List[Any]									=  hidden_dropout_prob
											_lowerCAmelCase:Dict									=  attention_probs_dropout_prob
											_lowerCAmelCase:Any									=  max_position_embeddings
											_lowerCAmelCase:Dict									=  type_vocab_size
											_lowerCAmelCase:Tuple									=  initializer_range
											_lowerCAmelCase:Tuple									=  layer_norm_eps
											_lowerCAmelCase:Any									=  position_embedding_type
											_lowerCAmelCase:Optional[Any]									=  use_cache
											_lowerCAmelCase:Union[str, Any]									=  pad_token_id







						@classmethod
						def       __UpperCamelCase     (							cls      :	int     ,a__      :	Union[str, Any]     ,**a__      :	List[str])						->       Tuple:




											"""simple docstring"""







											cls._set_token_in_kwargs(_lowerCAmelCase)

											_lowerCAmelCase							,   _lowerCAmelCase:List[Any]									=  cls.get_config_dict(_lowerCAmelCase     ,**_lowerCAmelCase)

											# get the text config dict if we are loading from AlignConfig
											if config_dict.get('''model_type''') == "align":
																_lowerCAmelCase:Tuple									=  config_dict['''text_config''']

											if "model_type" in config_dict and hasattr(cls     ,'''model_type''') and config_dict["model_type"] != cls.model_type:
																logger.warning(
																    F'You are using a model of type {config_dict["model_type"]} to instantiate a model of type '
																    F'{cls.model_type}. This is not supported for all configurations of models and can yield errors.')

											return cls.from_dict(_lowerCAmelCase     ,**_lowerCAmelCase)




class   a__			(       UpperCamelCase_  ):
						snake_case__             = '''align_vision_model'''





						def __init__(							self      :	List[Any]     ,a__      :	List[Any] = 3     ,a__      :	Optional[Any] = 600     ,a__      :	str = 2.0     ,a__      :	int = 3.1     ,a__      :	Tuple = 8     ,a__      :	Any = [3, 3, 5, 3, 5, 5, 3]     ,a__      :	Optional[int] = [32, 16, 24, 40, 80, 112, 192]     ,a__      :	int = [16, 24, 40, 80, 112, 192, 320]     ,a__      :	Any = []     ,a__      :	List[Any] = [1, 2, 2, 2, 1, 2, 1]     ,a__      :	List[str] = [1, 2, 2, 3, 3, 4, 1]     ,a__      :	Union[str, Any] = [1, 6, 6, 6, 6, 6, 6]     ,a__      :	List[str] = 0.25     ,a__      :	Union[str, Any] = "swish"     ,a__      :	List[str] = 2560     ,a__      :	List[Any] = "mean"     ,a__      :	Optional[Any] = 0.02     ,a__      :	Optional[Any] = 0.001     ,a__      :	str = 0.99     ,a__      :	Optional[Any] = 0.2     ,**a__      :	List[str]     ,)						->       Dict:




											"""simple docstring"""







											super().__init__(**_lowerCAmelCase)

											_lowerCAmelCase:List[Any]									=  num_channels
											_lowerCAmelCase:Union[str, Any]									=  image_size
											_lowerCAmelCase:Tuple									=  width_coefficient
											_lowerCAmelCase:Optional[int]									=  depth_coefficient
											_lowerCAmelCase:str									=  depth_divisor
											_lowerCAmelCase:str									=  kernel_sizes
											_lowerCAmelCase:str									=  in_channels
											_lowerCAmelCase:Optional[Any]									=  out_channels
											_lowerCAmelCase:Any									=  depthwise_padding
											_lowerCAmelCase:Dict									=  strides
											_lowerCAmelCase:Any									=  num_block_repeats
											_lowerCAmelCase:str									=  expand_ratios
											_lowerCAmelCase:int									=  squeeze_expansion_ratio
											_lowerCAmelCase:Any									=  hidden_act
											_lowerCAmelCase:str									=  hidden_dim
											_lowerCAmelCase:List[str]									=  pooling_type
											_lowerCAmelCase:int									=  initializer_range
											_lowerCAmelCase:List[Any]									=  batch_norm_eps
											_lowerCAmelCase:Optional[Any]									=  batch_norm_momentum
											_lowerCAmelCase:Optional[int]									=  drop_connect_rate
											_lowerCAmelCase:List[Any]									=  sum(_lowerCAmelCase) * 4







						@classmethod
						def       __UpperCamelCase     (							cls      :	str     ,a__      :	Any     ,**a__      :	Dict)						->       Optional[Any]:




											"""simple docstring"""







											cls._set_token_in_kwargs(_lowerCAmelCase)

											_lowerCAmelCase							,   _lowerCAmelCase:Optional[int]									=  cls.get_config_dict(_lowerCAmelCase     ,**_lowerCAmelCase)

											# get the vision config dict if we are loading from AlignConfig
											if config_dict.get('''model_type''') == "align":
																_lowerCAmelCase:int									=  config_dict['''vision_config''']

											if "model_type" in config_dict and hasattr(cls     ,'''model_type''') and config_dict["model_type"] != cls.model_type:
																logger.warning(
																    F'You are using a model of type {config_dict["model_type"]} to instantiate a model of type '
																    F'{cls.model_type}. This is not supported for all configurations of models and can yield errors.')

											return cls.from_dict(_lowerCAmelCase     ,**_lowerCAmelCase)




class   a__			(       UpperCamelCase_  ):
						snake_case__             = '''align'''
						snake_case__             = True





						def __init__(							self      :	str     ,a__      :	Tuple=None     ,a__      :	int=None     ,a__      :	int=640     ,a__      :	Any=1.0     ,a__      :	Optional[int]=0.02     ,**a__      :	List[str]     ,)						->       str:




											"""simple docstring"""







											super().__init__(**_lowerCAmelCase)

											if text_config is None:
																_lowerCAmelCase:Optional[int]									=  {}
																logger.info('''text_config is None. Initializing the AlignTextConfig with default values.''')

											if vision_config is None:
																_lowerCAmelCase:Tuple									=  {}
																logger.info('''vision_config is None. Initializing the AlignVisionConfig with default values.''')

											_lowerCAmelCase:Optional[int]									=  AlignTextConfig(**_lowerCAmelCase)
											_lowerCAmelCase:int									=  AlignVisionConfig(**_lowerCAmelCase)

											_lowerCAmelCase:Union[str, Any]									=  projection_dim
											_lowerCAmelCase:Optional[int]									=  temperature_init_value
											_lowerCAmelCase:Tuple									=  initializer_range





						@classmethod
						def       __UpperCamelCase     (							cls      :	Dict     ,a__      :	Optional[int]     ,a__      :	int     ,**a__      :	str)						->       Any:




											"""simple docstring"""







											return cls(text_config=text_config.to_dict()     ,vision_config=vision_config.to_dict()     ,**_lowerCAmelCase)







						def       __UpperCamelCase     (							self      :	Union[str, Any])						->       Union[str, Any]:




											"""simple docstring"""







											_lowerCAmelCase:Union[str, Any]									=  copy.deepcopy(self.__dict__)
											_lowerCAmelCase:Dict									=  self.text_config.to_dict()
											_lowerCAmelCase:Union[str, Any]									=  self.vision_config.to_dict()
											_lowerCAmelCase:List[Any]									=  self.__class__.model_type
											return output












"""simple docstring"""






def 							UpperCAmelCase		(		snake_case			:					str      ,       snake_case			:					str    ):
					assert x is not None
					assert y is not None

					_lowerCAmelCase:Optional[Any]									=  len(snake_case    )
					_lowerCAmelCase:Tuple									=  len(snake_case    )

					# declaring the array for storing the dp values
					_lowerCAmelCase:Optional[Any]									=  [[0] * (n + 1) for _ in range(m + 1    )]  # noqa: E741

					for i in range(1      ,       m + 1    ):
										for j in range(1      ,       n + 1    ):
															_lowerCAmelCase:Optional[int]									=  1 if x[i - 1] == y[j - 1] else 0

															_lowerCAmelCase:int									=  max(l[i - 1][j]      ,       l[i][j - 1]      ,       l[i - 1][j - 1] + match    )

					_lowerCAmelCase:List[Any]									=  ''''''
					_lowerCAmelCase							,   _lowerCAmelCase:Dict									=  m, n
					while i > 0 and j > 0:
										_lowerCAmelCase:Any									=  1 if x[i - 1] == y[j - 1] else 0

										if l[i][j] == l[i - 1][j - 1] + match:
															if match == 1:
																				_lowerCAmelCase:Any									=  x[i - 1] + seq
															i -= 1
															j -= 1
										elif l[i][j] == l[i - 1][j]:
															i -= 1
										else:
															j -= 1

					return l[m][n], seq


if __name__ == "__main__":
				UpperCamelCase__						=			'''AGGTAB'''
				UpperCamelCase__						=			'''GXTXAYB'''
				UpperCamelCase__						=			4
				UpperCamelCase__						=			'''GTAB'''

				UpperCamelCase__						,							UpperCamelCase__						=			longest_common_subsequence(a, b)
				print('''len =''', ln, ''', sub-sequence =''', subseq)
				import doctest

				doctest.testmod()






