



'''simple docstring'''




import copy
import os
from typing import Union

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


UpperCamelCase__       :	Any    = logging.get_logger(__name__)

UpperCamelCase__       :	Union[str, Any]    = {
    '''BAAI/AltCLIP''': '''https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json''',
    # See all AltCLIP models at https://huggingface.co/models?filter=altclip
}






class 						_UpperCamelCase  (							lowerCamelCase__    ):


			'''simple docstring'''

			_A      :		Tuple			    =		'''altclip_text_model'''

			def __init__(							self     : List[Any]							,     lowerCAmelCase__     : Any=2_5_0_0_0_2							,     lowerCAmelCase__     : int=1_0_2_4							,     lowerCAmelCase__     : str=2_4							,     lowerCAmelCase__     : Union[str, Any]=1_6							,     lowerCAmelCase__     : List[str]=4_0_9_6							,     lowerCAmelCase__     : Dict="gelu"							,     lowerCAmelCase__     : List[Any]=0.1							,     lowerCAmelCase__     : Union[str, Any]=0.1							,     lowerCAmelCase__     : List[str]=5_1_4							,     lowerCAmelCase__     : List[str]=1							,     lowerCAmelCase__     : List[str]=0.02							,     lowerCAmelCase__     : Optional[Any]=0.02							,     lowerCAmelCase__     : Optional[Any]=1E-05							,     lowerCAmelCase__     : Optional[Any]=1							,     lowerCAmelCase__     : List[str]=0							,     lowerCAmelCase__     : List[str]=2							,     lowerCAmelCase__     : Optional[int]="absolute"							,     lowerCAmelCase__     : int=True							,     lowerCAmelCase__     : int=7_6_8							,     **lowerCAmelCase__     : int							,     ):





					"""simple docstring"""






					super().__init__(pad_token_id=lowerCAmelCase__							,     bos_token_id=lowerCAmelCase__							,     eos_token_id=lowerCAmelCase__							,     **lowerCAmelCase__						)

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






class 						_UpperCamelCase  (							lowerCamelCase__    ):


			'''simple docstring'''

			_A      :		Dict			    =		'''altclip_vision_model'''

			def __init__(							self     : Union[str, Any]							,     lowerCAmelCase__     : str=7_6_8							,     lowerCAmelCase__     : Dict=3_0_7_2							,     lowerCAmelCase__     : str=5_1_2							,     lowerCAmelCase__     : str=1_2							,     lowerCAmelCase__     : Dict=1_2							,     lowerCAmelCase__     : List[Any]=3							,     lowerCAmelCase__     : int=2_2_4							,     lowerCAmelCase__     : Union[str, Any]=3_2							,     lowerCAmelCase__     : Any="quick_gelu"							,     lowerCAmelCase__     : Tuple=1E-5							,     lowerCAmelCase__     : List[Any]=0.0							,     lowerCAmelCase__     : Tuple=0.02							,     lowerCAmelCase__     : List[Any]=1.0							,     **lowerCAmelCase__     : List[str]							,     ):





					"""simple docstring"""






					super().__init__(**lowerCAmelCase__						)

					__SCREAMING_SNAKE_CASE       :		List[str]           =		hidden_size
					__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		intermediate_size
					__SCREAMING_SNAKE_CASE       :		Any           =		projection_dim
					__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		num_hidden_layers
					__SCREAMING_SNAKE_CASE       :		str           =		num_attention_heads
					__SCREAMING_SNAKE_CASE       :		Dict           =		num_channels
					__SCREAMING_SNAKE_CASE       :		int           =		patch_size
					__SCREAMING_SNAKE_CASE       :		int           =		image_size
					__SCREAMING_SNAKE_CASE       :		List[Any]           =		initializer_range
					__SCREAMING_SNAKE_CASE       :		Tuple           =		initializer_factor
					__SCREAMING_SNAKE_CASE       :		Dict           =		attention_dropout
					__SCREAMING_SNAKE_CASE       :		Any           =		layer_norm_eps
					__SCREAMING_SNAKE_CASE       :		Dict           =		hidden_act



			@classmethod
			def UpperCamelCase__					(							cls     : str							,     lowerCAmelCase__     : Union[str, os.PathLike]							,     **lowerCAmelCase__     : Optional[int]						):





					"""simple docstring"""






					cls._set_token_in_kwargs(lowerCAmelCase__						)

					__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		List[str]           =		cls.get_config_dict(lowerCAmelCase__							,     **lowerCAmelCase__						)

					# get the vision config dict if we are loading from AltCLIPConfig
					if config_dict.get("""model_type"""						) == "altclip":
							__SCREAMING_SNAKE_CASE       :		List[str]           =		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 						_UpperCamelCase  (							lowerCamelCase__    ):


			'''simple docstring'''

			_A      :		Any			    =		'''altclip'''
			_A      :		Union[str, Any]			    =		True

			def __init__(							self     : Any							,     lowerCAmelCase__     : Optional[int]=None							,     lowerCAmelCase__     : List[str]=None							,     lowerCAmelCase__     : List[str]=7_6_8							,     lowerCAmelCase__     : List[Any]=2.65_92							,     **lowerCAmelCase__     : Union[str, Any]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Tuple           =		kwargs.pop("""text_config_dict"""							,     lowerCAmelCase__						)
					__SCREAMING_SNAKE_CASE       :		Any           =		kwargs.pop("""vision_config_dict"""							,     lowerCAmelCase__						)

					super().__init__(**lowerCAmelCase__						)

					# Instead of simply assigning `[text|vision]_config_dict` to `[text|vision]_config`, we use the values in
					# `[text|vision]_config_dict` to update the values in `[text|vision]_config`. The values should be same in most
					# cases, but we don't want to break anything regarding `_config_dict` that existed before commit `8827e1b2`.
					if text_config_dict is not None:
							if text_config is None:
									__SCREAMING_SNAKE_CASE       :		Optional[int]           =		{}

							# This is the complete result when using `text_config_dict`.
							__SCREAMING_SNAKE_CASE       :		Dict           =		AltCLIPTextConfig(**lowerCAmelCase__						).to_dict()

							# Give a warning if the values exist in both `_text_config_dict` and `text_config` but being different.
							for key, value in _text_config_dict.items():
									if key in text_config and value != text_config[key] and key not in ["transformers_version"]:
											# If specified in `text_config_dict`
											if key in text_config_dict:
													__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		(
													    F"`{key}` is found in both `text_config_dict` and `text_config` but with different values. "
													    F"The value `text_config_dict[\"{key}\"]` will be used instead."
													)
											# If inferred from default argument values (just to be super careful)
											else:
													__SCREAMING_SNAKE_CASE       :		Any           =		(
													    F"`text_config_dict` is provided which will be used to initialize `AltCLIPTextConfig`. The "
													    F"value `text_config[\"{key}\"]` will be overriden."
													)
											logger.warning(lowerCAmelCase__						)

            # Update all values in `text_config` with the ones in `_text_config_dict`.
							text_config.update(_text_config_dict						)

					if vision_config_dict is not None:
							if vision_config is None:
									__SCREAMING_SNAKE_CASE       :		Dict           =		{}

							# This is the complete result when using `vision_config_dict`.
							__SCREAMING_SNAKE_CASE       :		List[str]           =		AltCLIPVisionConfig(**lowerCAmelCase__						).to_dict()
							# convert keys to string instead of integer
							if "id2label" in _vision_config_dict:
									__SCREAMING_SNAKE_CASE       :		Any           =		{
									    str(lowerCAmelCase__						): value for key, value in _vision_config_dict["""id2label"""].items()
									}

							# Give a warning if the values exist in both `_vision_config_dict` and `vision_config` but being different.
							for key, value in _vision_config_dict.items():
									if key in vision_config and value != vision_config[key] and key not in ["transformers_version"]:
											# If specified in `vision_config_dict`
											if key in vision_config_dict:
													__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		(
													    F"`{key}` is found in both `vision_config_dict` and `vision_config` but with different "
													    F"values. The value `vision_config_dict[\"{key}\"]` will be used instead."
													)
											# If inferred from default argument values (just to be super careful)
											else:
													__SCREAMING_SNAKE_CASE       :		Tuple           =		(
													    F"`vision_config_dict` is provided which will be used to initialize `AltCLIPVisionConfig`. "
													    F"The value `vision_config[\"{key}\"]` will be overriden."
													)
											logger.warning(lowerCAmelCase__						)

            # Update all values in `vision_config` with the ones in `_vision_config_dict`.
							vision_config.update(_vision_config_dict						)

					if text_config is None:
							__SCREAMING_SNAKE_CASE       :		Dict           =		{}
							logger.info("""`text_config` is `None`. Initializing the `AltCLIPTextConfig` with default values."""						)

					if vision_config is None:
							__SCREAMING_SNAKE_CASE       :		List[Any]           =		{}
							logger.info("""`vision_config` is `None`. initializing the `AltCLIPVisionConfig` with default values."""						)

					__SCREAMING_SNAKE_CASE       :		List[Any]           =		AltCLIPTextConfig(**lowerCAmelCase__						)
					__SCREAMING_SNAKE_CASE       :		Union[str, Any]           =		AltCLIPVisionConfig(**lowerCAmelCase__						)

					__SCREAMING_SNAKE_CASE       :		List[str]           =		projection_dim
					__SCREAMING_SNAKE_CASE       :		Tuple           =		logit_scale_init_value
					__SCREAMING_SNAKE_CASE       :		Union[str, Any]           =		1.0

			@classmethod
			def UpperCamelCase__					(							cls     : int							,     lowerCAmelCase__     : AltCLIPTextConfig							,     lowerCAmelCase__     : AltCLIPVisionConfig							,     **lowerCAmelCase__     : Dict						):





					"""simple docstring"""






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



			def UpperCamelCase__					(							self     : Tuple						):





					"""simple docstring"""






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




'''simple docstring'''




def 				lowerCAmelCase_   (	_lowerCamelCase:   list					):
		if any(not isinstance(_lowerCamelCase       ,      _lowerCamelCase					) or x < 0 for x in sequence					):
				raise TypeError("""Sequence must be list of non-negative integers"""					)
		for _ in range(len(_lowerCamelCase					)					):
				for i, (rod_upper, rod_lower) in enumerate(zip(_lowerCamelCase       ,      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]