'''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


_lowercase						: Any						=						logging.get_logger(__name__)

_lowercase						: Union[str, Any]						=						{
    "kakaobrain/align-base": "https://huggingface.co/kakaobrain/align-base/resolve/main/config.json",
}





class     __magic_name__						(    _UpperCAmelCase):
			UpperCamelCase__				=       '''align_text_model'''







			def __init__(	self				:  List[str]				,			lowercase_				:  Tuple=30522				,			lowercase_				:  Any=768				,			lowercase_				:  Dict=12				,			lowercase_				:  int=12				,			lowercase_				:  Optional[Any]=3072				,			lowercase_				:  Union[str, Any]="gelu"				,			lowercase_				:  Dict=0.1				,			lowercase_				:  Any=0.1				,			lowercase_				:  Dict=512				,			lowercase_				:  Any=2				,			lowercase_				:  List[str]=0.02				,			lowercase_				:  Tuple=1E-12				,			lowercase_				:  str=0				,			lowercase_				:  List[str]="absolute"				,			lowercase_				:  Union[str, Any]=True				,			**lowercase_				:  List[str]				,			):
										super().__init__(**lowercase_    )

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







			@classmethod
			def 	SCREAMING_SNAKE_CASE_     (	cls				:  Union[str, Any]				,			lowercase_				:  Union[str, os.PathLike]				,			**lowercase_				:  Optional[Any]    ):
										cls._set_token_in_kwargs(lowercase_    )

										lowercase_						,						lowercase_					:			Dict										=       cls.get_config_dict(lowercase_				,			**lowercase_    )

										# get the text config dict if we are loading from AlignConfig
										if config_dict.get("""model_type"""    ) == "align":
																	lowercase_					:			str										=       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(lowercase_				,			**lowercase_    )





class     __magic_name__						(    _UpperCAmelCase):
			UpperCamelCase__				=       '''align_vision_model'''







			def __init__(	self				:  List[Any]				,			lowercase_				:  int = 3				,			lowercase_				:  int = 600				,			lowercase_				:  float = 2.0				,			lowercase_				:  float = 3.1				,			lowercase_				:  int = 8				,			lowercase_				:  List[int] = [3, 3, 5, 3, 5, 5, 3]				,			lowercase_				:  List[int] = [32, 16, 24, 40, 80, 112, 192]				,			lowercase_				:  List[int] = [16, 24, 40, 80, 112, 192, 320]				,			lowercase_				:  List[int] = []				,			lowercase_				:  List[int] = [1, 2, 2, 2, 1, 2, 1]				,			lowercase_				:  List[int] = [1, 2, 2, 3, 3, 4, 1]				,			lowercase_				:  List[int] = [1, 6, 6, 6, 6, 6, 6]				,			lowercase_				:  float = 0.25				,			lowercase_				:  str = "swish"				,			lowercase_				:  int = 2560				,			lowercase_				:  str = "mean"				,			lowercase_				:  float = 0.02				,			lowercase_				:  float = 0.0_01				,			lowercase_				:  float = 0.99				,			lowercase_				:  float = 0.2				,			**lowercase_				:  List[str]				,			):
										super().__init__(**lowercase_    )

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







			@classmethod
			def 	SCREAMING_SNAKE_CASE_     (	cls				:  Any				,			lowercase_				:  Union[str, os.PathLike]				,			**lowercase_				:  int    ):
										cls._set_token_in_kwargs(lowercase_    )

										lowercase_						,						lowercase_					:			Any										=       cls.get_config_dict(lowercase_				,			**lowercase_    )

										# get the vision config dict if we are loading from AlignConfig
										if config_dict.get("""model_type"""    ) == "align":
																	lowercase_					:			Dict										=       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(lowercase_				,			**lowercase_    )





class     __magic_name__						(    _UpperCAmelCase):
			UpperCamelCase__				=       '''align'''
			UpperCamelCase__				=       True







			def __init__(	self				:  Dict				,			lowercase_				:  Optional[Any]=None				,			lowercase_				:  str=None				,			lowercase_				:  List[str]=640				,			lowercase_				:  str=1.0				,			lowercase_				:  List[Any]=0.02				,			**lowercase_				:  Optional[int]				,			):
										super().__init__(**lowercase_    )

										if text_config is None:
																	lowercase_					:			Any										=       {}
																	logger.info("""text_config is None. Initializing the AlignTextConfig with default values."""    )

										if vision_config is None:
																	lowercase_					:			Any										=       {}
																	logger.info("""vision_config is None. Initializing the AlignVisionConfig with default values."""    )

										lowercase_					:			List[Any]										=       AlignTextConfig(**lowercase_    )
										lowercase_					:			Union[str, Any]										=       AlignVisionConfig(**lowercase_    )

										lowercase_					:			Tuple										=       projection_dim
										lowercase_					:			Optional[int]										=       temperature_init_value
										lowercase_					:			List[str]										=       initializer_range







			@classmethod
			def 	SCREAMING_SNAKE_CASE_     (	cls				:  Dict				,			lowercase_				:  AlignTextConfig				,			lowercase_				:  AlignVisionConfig				,			**lowercase_				:  Tuple    ):
										return cls(text_config=text_config.to_dict()				,			vision_config=vision_config.to_dict()				,			**lowercase_    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Any    ):
										lowercase_					:			List[Any]										=       copy.deepcopy(self.__dict__    )
										lowercase_					:			str										=       self.text_config.to_dict()
										lowercase_					:			Dict										=       self.vision_config.to_dict()
										lowercase_					:			str										=       self.__class__.model_type
										return output






'''simple docstring'''




def 							lowerCamelCase	(      UpperCAmelCase__       :					list )			->      list:
							if any(not isinstance(UpperCAmelCase__      ,      UpperCAmelCase__ ) or x < 0 for x in sequence ):
														raise TypeError("""Sequence must be list of non-negative integers""" )
							for _ in range(len(UpperCAmelCase__ ) ):
														for i, (rod_upper, rod_lower) in enumerate(zip(UpperCAmelCase__      ,      sequence[1:] ) ):
																					if rod_upper > rod_lower:
																												sequence[i] -= rod_upper - rod_lower
																												sequence[i + 1] += rod_upper - rod_lower
							return sequence


if __name__ == "__main__":
						assert bead_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]
						assert bead_sort([7, 9, 4, 3, 5]) == [3, 4, 5, 7, 9]





