






"""simple docstring"""
import copy
import os
from typing import Union

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


_lowerCAmelCase       =				logging.get_logger(__name__)

_lowerCAmelCase       =				{
    "BridgeTower/bridgetower-base": "https://huggingface.co/BridgeTower/bridgetower-base/blob/main/config.json",
    "BridgeTower/bridgetower-base-itm-mlm": (
        "https://huggingface.co/BridgeTower/bridgetower-base-itm-mlm/blob/main/config.json"
    ),
}



class   SCREAMING_SNAKE_CASE	(					_SCREAMING_SNAKE_CASE    ):





	"""simple docstring"""




	_A							:					int 			=					"""bridgetower_vision_model"""





	def __init__(self  ,  lowerCAmelCase_=768  ,  lowerCAmelCase_=12  ,  lowerCAmelCase_=3  ,  lowerCAmelCase_=16  ,  lowerCAmelCase_=288  ,  lowerCAmelCase_=1  ,  lowerCAmelCase_=1e-0_5  ,  lowerCAmelCase_=False  ,  lowerCAmelCase_=True  ,  lowerCAmelCase_=False  ,  **lowerCAmelCase_  ,  ):
		super().__init__(**lowerCAmelCase_				)
		A_		:    List[str]						     = hidden_size
		A_		:    List[Any]						     = num_hidden_layers
		A_		:    Optional[Any]						     = num_channels
		A_		:    Any						     = patch_size
		A_		:    str						     = image_size
		A_		:    int						     = initializer_factor
		A_		:    Optional[Any]						     = layer_norm_eps
		A_		:    List[str]						     = stop_gradient
		A_		:    int						     = share_layernorm
		A_		:    Tuple						     = remove_last_layer





	@classmethod
	def  lowerCamelCase(cls  ,  lowerCAmelCase_  ,  **lowerCAmelCase_				):
		A_     ,  A_		:    List[str]						     = cls.get_config_dict(lowerCAmelCase_  ,  **lowerCAmelCase_				)

		if config_dict.get("""model_type"""				) == "bridgetower":
			A_		:    Union[str, Any]						     = 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   SCREAMING_SNAKE_CASE	(					_SCREAMING_SNAKE_CASE    ):





	"""simple docstring"""




	_A							:					int 			=					"""bridgetower_text_model"""





	def __init__(self  ,  lowerCAmelCase_=50265  ,  lowerCAmelCase_=768  ,  lowerCAmelCase_=12  ,  lowerCAmelCase_=12  ,  lowerCAmelCase_=1  ,  lowerCAmelCase_=3072  ,  lowerCAmelCase_="gelu"  ,  lowerCAmelCase_=0.1  ,  lowerCAmelCase_=0.1  ,  lowerCAmelCase_=514  ,  lowerCAmelCase_=1  ,  lowerCAmelCase_=1e-0_5  ,  lowerCAmelCase_=1  ,  lowerCAmelCase_=0  ,  lowerCAmelCase_=2  ,  lowerCAmelCase_="absolute"  ,  lowerCAmelCase_=True  ,  **lowerCAmelCase_  ,  ):
		super().__init__(**lowerCAmelCase_				)

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





	@classmethod
	def  lowerCamelCase(cls  ,  lowerCAmelCase_  ,  **lowerCAmelCase_				):
		A_     ,  A_		:    Dict						     = cls.get_config_dict(lowerCAmelCase_  ,  **lowerCAmelCase_				)

		if config_dict.get("""model_type"""				) == "bridgetower":
			A_		:    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(lowerCAmelCase_  ,  **lowerCAmelCase_				)






class   SCREAMING_SNAKE_CASE	(					_SCREAMING_SNAKE_CASE    ):





	"""simple docstring"""




	_A							:					List[str] 			=					"""bridgetower"""





	def __init__(self  ,  lowerCAmelCase_=True  ,  lowerCAmelCase_="gelu"  ,  lowerCAmelCase_=768  ,  lowerCAmelCase_=1  ,  lowerCAmelCase_=1e-0_5  ,  lowerCAmelCase_=False  ,  lowerCAmelCase_="add"  ,  lowerCAmelCase_=12  ,  lowerCAmelCase_=6  ,  lowerCAmelCase_=False  ,  lowerCAmelCase_=False  ,  lowerCAmelCase_=None  ,  lowerCAmelCase_=None  ,  **lowerCAmelCase_  ,  ):
		# TODO: remove this once the Hub files are updated.
		A_		:    List[str]						     = kwargs.pop("""text_config_dict"""  ,  lowerCAmelCase_				)
		A_		:    List[str]						     = kwargs.pop("""vision_config_dict"""  ,  lowerCAmelCase_				)

		super().__init__(**lowerCAmelCase_				)
		A_		:    str						     = share_cross_modal_transformer_layers
		A_		:    Union[str, Any]						     = hidden_act
		A_		:    List[Any]						     = hidden_size
		A_		:    Dict						     = initializer_factor
		A_		:    Tuple						     = layer_norm_eps
		A_		:    Optional[Any]						     = share_link_tower_layers
		A_		:    Dict						     = link_tower_type
		A_		:    Optional[Any]						     = num_attention_heads
		A_		:    Union[str, Any]						     = num_hidden_layers
		A_		:    str						     = tie_word_embeddings
		A_		:    Union[str, Any]						     = init_layernorm_from_vision_encoder

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

		if vision_config is None:
			A_		:    List[str]						     = {}
			logger.info("""`vision_config` is `None`. Initializing the `BridgeTowerVisionConfig` with default values."""				)

		A_		:    str						     = BridgeTowerTextConfig(**lowerCAmelCase_				)
		A_		:    List[str]						     = BridgeTowerVisionConfig(**lowerCAmelCase_				)





	@classmethod
	def  lowerCamelCase(cls  ,  lowerCAmelCase_  ,  lowerCAmelCase_  ,  **lowerCAmelCase_				):
		return cls(text_config=text_config.to_dict()  ,  vision_config=vision_config.to_dict()  ,  **lowerCAmelCase_				)





	def  lowerCamelCase(self				):
		A_		:    int						     = copy.deepcopy(self.__dict__				)
		A_		:    Tuple						     = self.text_config.to_dict()
		A_		:    Dict						     = self.vision_config.to_dict()
		A_		:    Optional[Any]						     = self.__class__.model_type
		return output









"""simple docstring"""
class   SCREAMING_SNAKE_CASE	:





	"""simple docstring"""




	def __init__(self  ,  lowerCAmelCase_  ,  lowerCAmelCase_=None  ,  lowerCAmelCase_=None				):
		A_		:    Dict						     = data
		A_		:    Dict						     = previous
		A_		:    int						     = next_node





	def __str__(self				):
		return f"""{self.data}"""





	def  lowerCamelCase(self				):
		return self.data





	def  lowerCamelCase(self				):
		return self.next





	def  lowerCamelCase(self				):
		return self.previous






class   SCREAMING_SNAKE_CASE	:





	"""simple docstring"""




	def __init__(self  ,  lowerCAmelCase_				):
		A_		:    Optional[Any]						     = head





	def __iter__(self				):
		return self





	def  lowerCamelCase(self				):
		if not self.current:
			raise StopIteration
		else:
			A_		:    str						     = self.current.get_data()
			A_		:    List[str]						     = self.current.get_next()
			return value






class   SCREAMING_SNAKE_CASE	:





	"""simple docstring"""




	def __init__(self				):
		A_		:    str						     = None  # First node in list
		A_		:    Tuple						     = None  # Last node in list





	def __str__(self				):
		A_		:    int						     = self.head
		A_		:    str						     = []
		while current is not None:
			nodes.append(current.get_data()				)
			A_		:    Any						     = current.get_next()
		return " ".join(str(lowerCAmelCase_				) for node in nodes				)





	def __contains__(self  ,  lowerCAmelCase_				):
		A_		:    Union[str, Any]						     = self.head
		while current:
			if current.get_data() == value:
				return True
			A_		:    Union[str, Any]						     = current.get_next()
		return False





	def __iter__(self				):
		return LinkedListIterator(self.head				)





	def  lowerCamelCase(self				):
		if self.head:
			return self.head.get_data()
		return None





	def  lowerCamelCase(self				):
		if self.tail:
			return self.tail.get_data()
		return None





	def  lowerCamelCase(self  ,  lowerCAmelCase_				):
		if self.head is None:
			A_		:    str						     = node
			A_		:    Optional[int]						     = node
		else:
			self.insert_before_node(self.head  ,  lowerCAmelCase_				)





	def  lowerCamelCase(self  ,  lowerCAmelCase_				):
		if self.head is None:
			self.set_head(lowerCAmelCase_				)
		else:
			self.insert_after_node(self.tail  ,  lowerCAmelCase_				)





	def  lowerCamelCase(self  ,  lowerCAmelCase_				):
		A_		:    List[Any]						     = Node(lowerCAmelCase_				)
		if self.head is None:
			self.set_head(lowerCAmelCase_				)
		else:
			self.set_tail(lowerCAmelCase_				)





	def  lowerCamelCase(self  ,  lowerCAmelCase_  ,  lowerCAmelCase_				):
		A_		:    str						     = node
		A_		:    Union[str, Any]						     = node.previous

		if node.get_previous() is None:
			A_		:    Dict						     = node_to_insert
		else:
			A_		:    Optional[Any]						     = node_to_insert

		A_		:    Any						     = node_to_insert





	def  lowerCamelCase(self  ,  lowerCAmelCase_  ,  lowerCAmelCase_				):
		A_		:    Dict						     = node
		A_		:    Optional[Any]						     = node.next

		if node.get_next() is None:
			A_		:    Optional[int]						     = node_to_insert
		else:
			A_		:    List[Any]						     = node_to_insert

		A_		:    Optional[Any]						     = node_to_insert





	def  lowerCamelCase(self  ,  lowerCAmelCase_  ,  lowerCAmelCase_				):
		A_		:    str						     = 1
		A_		:    Tuple						     = Node(lowerCAmelCase_				)
		A_		:    Dict						     = self.head
		while node:
			if current_position == position:
				self.insert_before_node(lowerCAmelCase_  ,  lowerCAmelCase_				)
				return
			current_position += 1
			A_		:    List[str]						     = node.next
		self.insert_after_node(self.tail  ,  lowerCAmelCase_				)





	def  lowerCamelCase(self  ,  lowerCAmelCase_				):
		A_		:    Dict						     = self.head
		while node:
			if node.get_data() == item:
				return node
			A_		:    Optional[int]						     = node.get_next()
		raise Exception("""Node not found"""				)





	def  lowerCamelCase(self  ,  lowerCAmelCase_				):
		if (node := self.get_node(lowerCAmelCase_				)) is not None:
			if node == self.head:
				A_		:    Tuple						     = self.head.get_next()

			if node == self.tail:
				A_		:    Dict						     = self.tail.get_previous()

			self.remove_node_pointers(lowerCAmelCase_				)





	@staticmethod
	def  lowerCamelCase(lowerCAmelCase_				):
		if node.get_next():
			A_		:    Any						     = node.previous

		if node.get_previous():
			A_		:    int						     = node.next

		A_		:    str						     = None
		A_		:    int						     = None





	def  lowerCamelCase(self				):
		return self.head is None






def       __UpperCamelCase						(		):
	pass


if __name__ == "__main__":
							import doctest

							doctest.testmod()

