


import copy
import os
from typing import Union

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


__lowerCAmelCase     							=			logging.get_logger(__name__)

__lowerCAmelCase     							=			{
    '''BAAI/AltCLIP''': '''https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json''',
    # See all AltCLIP models at https://huggingface.co/models?filter=altclip
}


class  __SCREAMING_SNAKE_CASE       (						lowercase):
     __SCREAMING_SNAKE_CASE  : int     =			"""altclip_text_model"""


     def __init__(			self      :		Optional[int]       ,  __UpperCamelCase      :		Tuple=250_002       ,  __UpperCamelCase      :		Optional[Any]=1_024       ,  __UpperCamelCase      :		List[Any]=24       ,  __UpperCamelCase      :		Union[str, Any]=16       ,  __UpperCamelCase      :		Optional[Any]=4_096       ,  __UpperCamelCase      :		Tuple="gelu"       ,  __UpperCamelCase      :		Any=0.1       ,  __UpperCamelCase      :		List[str]=0.1       ,  __UpperCamelCase      :		int=514       ,  __UpperCamelCase      :		Optional[int]=1       ,  __UpperCamelCase      :		str=0.02       ,  __UpperCamelCase      :		Optional[int]=0.02       ,  __UpperCamelCase      :		Tuple=1e-0_5       ,  __UpperCamelCase      :		Tuple=1       ,  __UpperCamelCase      :		Optional[Any]=0       ,  __UpperCamelCase      :		List[Any]=2       ,  __UpperCamelCase      :		Tuple="absolute"       ,  __UpperCamelCase      :		List[str]=True       ,  __UpperCamelCase      :		List[Any]=768       ,  **__UpperCamelCase      :		Dict       ,  ):
       super().__init__(pad_token_id=UpperCamelCase_       ,  bos_token_id=UpperCamelCase_       ,  eos_token_id=UpperCamelCase_       ,  **UpperCamelCase_ )

       _UpperCAmelCase												=     vocab_size
       _UpperCAmelCase												=     hidden_size
       _UpperCAmelCase												=     num_hidden_layers
       _UpperCAmelCase												=     num_attention_heads
       _UpperCAmelCase												=     hidden_act
       _UpperCAmelCase												=     intermediate_size
       _UpperCAmelCase												=     hidden_dropout_prob
       _UpperCAmelCase												=     attention_probs_dropout_prob
       _UpperCAmelCase												=     max_position_embeddings
       _UpperCAmelCase												=     type_vocab_size
       _UpperCAmelCase												=     initializer_range
       _UpperCAmelCase												=     initializer_factor
       _UpperCAmelCase												=     layer_norm_eps
       _UpperCAmelCase												=     position_embedding_type
       _UpperCAmelCase												=     use_cache
       _UpperCAmelCase												=     project_dim





class  __SCREAMING_SNAKE_CASE       (						lowercase):
     __SCREAMING_SNAKE_CASE  : Optional[Any]     =			"""altclip_vision_model"""


     def __init__(			self      :		str       ,  __UpperCamelCase      :		List[str]=768       ,  __UpperCamelCase      :		str=3_072       ,  __UpperCamelCase      :		Any=512       ,  __UpperCamelCase      :		Any=12       ,  __UpperCamelCase      :		Optional[int]=12       ,  __UpperCamelCase      :		List[Any]=3       ,  __UpperCamelCase      :		int=224       ,  __UpperCamelCase      :		str=32       ,  __UpperCamelCase      :		List[Any]="quick_gelu"       ,  __UpperCamelCase      :		Tuple=1e-5       ,  __UpperCamelCase      :		Any=0.0       ,  __UpperCamelCase      :		Optional[Any]=0.02       ,  __UpperCamelCase      :		Optional[Any]=1.0       ,  **__UpperCamelCase      :		Tuple       ,  ):
       super().__init__(**UpperCamelCase_ )

       _UpperCAmelCase												=     hidden_size
       _UpperCAmelCase												=     intermediate_size
       _UpperCAmelCase												=     projection_dim
       _UpperCAmelCase												=     num_hidden_layers
       _UpperCAmelCase												=     num_attention_heads
       _UpperCAmelCase												=     num_channels
       _UpperCAmelCase												=     patch_size
       _UpperCAmelCase												=     image_size
       _UpperCAmelCase												=     initializer_range
       _UpperCAmelCase												=     initializer_factor
       _UpperCAmelCase												=     attention_dropout
       _UpperCAmelCase												=     layer_norm_eps
       _UpperCAmelCase												=     hidden_act



     @classmethod
     def 							UpperCAmelCase__  (			cls      :		List[str]       ,  __UpperCamelCase      :		str       ,  **__UpperCamelCase      :		Tuple ):
       cls._set_token_in_kwargs(UpperCamelCase_ )

       _UpperCAmelCase						,		_UpperCAmelCase												=     cls.get_config_dict(UpperCamelCase_       ,  **UpperCamelCase_ )

       # get the vision config dict if we are loading from AltCLIPConfig
       if config_dict.get("model_type" ) == "altclip":
         _UpperCAmelCase												=     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(UpperCamelCase_       ,  **UpperCamelCase_ )





class  __SCREAMING_SNAKE_CASE       (						lowercase):
     __SCREAMING_SNAKE_CASE  : List[str]     =			"""altclip"""
     __SCREAMING_SNAKE_CASE  : Optional[Any]     =			True


     def __init__(			self      :		Any       ,  __UpperCamelCase      :		Tuple=None       ,  __UpperCamelCase      :		List[Any]=None       ,  __UpperCamelCase      :		Optional[Any]=768       ,  __UpperCamelCase      :		Tuple=2.6592       ,  **__UpperCamelCase      :		List[Any] ):
       # If `_config_dict` exist, we use them for the backward compatibility.
       # We pop out these 2 attributes before calling `super().__init__` to avoid them being saved (which causes a lot
       # of confusion!).
       _UpperCAmelCase												=     kwargs.pop("text_config_dict"       ,  UpperCamelCase_ )
       _UpperCAmelCase												=     kwargs.pop("vision_config_dict"       ,  UpperCamelCase_ )

       super().__init__(**UpperCamelCase_ )

       # 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:
           _UpperCAmelCase												=     {}

         # This is the complete result when using `text_config_dict`.
         _UpperCAmelCase												=     AltCLIPTextConfig(**UpperCamelCase_ ).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:
               _UpperCAmelCase												=     (
                   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:
               _UpperCAmelCase												=     (
                   F'''`text_config_dict` is provided which will be used to initialize `AltCLIPTextConfig`. The '''
                   F'''value `text_config["{key}"]` will be overriden.'''
               )
             logger.warning(UpperCamelCase_ )

            # 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:
           _UpperCAmelCase												=     {}

         # This is the complete result when using `vision_config_dict`.
         _UpperCAmelCase												=     AltCLIPVisionConfig(**UpperCamelCase_ ).to_dict()
         # convert keys to string instead of integer
         if "id2label" in _vision_config_dict:
           _UpperCAmelCase												=     {
               str(UpperCamelCase_ ): 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:
               _UpperCAmelCase												=     (
                   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:
               _UpperCAmelCase												=     (
                   F'''`vision_config_dict` is provided which will be used to initialize `AltCLIPVisionConfig`. '''
                   F'''The value `vision_config["{key}"]` will be overriden.'''
               )
             logger.warning(UpperCamelCase_ )

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

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

       if vision_config is None:
         _UpperCAmelCase												=     {}
         logger.info("`vision_config` is `None`. initializing the `AltCLIPVisionConfig` with default values." )

       _UpperCAmelCase												=     AltCLIPTextConfig(**UpperCamelCase_ )
       _UpperCAmelCase												=     AltCLIPVisionConfig(**UpperCamelCase_ )

       _UpperCAmelCase												=     projection_dim
       _UpperCAmelCase												=     logit_scale_init_value
       _UpperCAmelCase												=     1.0


     @classmethod
     def 							UpperCAmelCase__  (			cls      :		Optional[int]       ,  __UpperCamelCase      :		List[Any]       ,  __UpperCamelCase      :		Optional[int]       ,  **__UpperCamelCase      :		Tuple ):
       return cls(text_config=text_config.to_dict()       ,  vision_config=vision_config.to_dict()       ,  **UpperCamelCase_ )



     def 							UpperCAmelCase__  (			self      :		str ):
       _UpperCAmelCase												=     copy.deepcopy(self.__dict__ )
       _UpperCAmelCase												=     self.text_config.to_dict()
       _UpperCAmelCase												=     self.vision_config.to_dict()
       _UpperCAmelCase												=     self.__class__.model_type
       return output










'''simple docstring'''




from __future__ import annotations

a__					:			Optional[int]          =     list[tuple[int, int]]

a__					:			List[Any]          =     [
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

a__					:			Optional[int]          =     ([-1, 0], [0, -1], [1, 0], [0, 1])  # up, left, down, right






class 				__snake_case     :





	def __init__(		self      ,       UpperCamelCase_      ,       UpperCamelCase_      ,       UpperCamelCase_      ,       UpperCamelCase_      ,       UpperCamelCase_      ,       UpperCamelCase_      ,       )      ->		Any:
		snake_case__	       =   pos_x
		snake_case__	       =   pos_y
		snake_case__	       =   (pos_y, pos_x)
		snake_case__	       =   goal_x
		snake_case__	       =   goal_y
		snake_case__	       =   g_cost
		snake_case__	       =   parent
		snake_case__	       =   self.calculate_heuristic()





	def   _snake_case   (		self		)      ->		float:
		snake_case__	       =   abs(self.pos_x - self.goal_x		)
		snake_case__	       =   abs(self.pos_y - self.goal_y		)
		return dx + dy





	def __lt__(		self      ,       UpperCamelCase_		)      ->		bool:
		return self.f_cost < other.f_cost






class 				__snake_case     :





	def __init__(		self      ,       UpperCamelCase_      ,       UpperCamelCase_		)      ->		Any:
		snake_case__	       =   Node(start[1]      ,       start[0]      ,       goal[1]      ,       goal[0]      ,       0      ,       UpperCamelCase_		)
		snake_case__	       =   Node(goal[1]      ,       goal[0]      ,       goal[1]      ,       goal[0]      ,       9_9999      ,       UpperCamelCase_		)

		snake_case__	       =   [self.start]
		snake_case__	       =   []

		snake_case__	       =   False





	def   _snake_case   (		self		)      ->		Path | None:
		while self.open_nodes:
			# Open Nodes are sorted using __lt__
			self.open_nodes.sort()
			snake_case__	       =   self.open_nodes.pop(0		)

			if current_node.pos == self.target.pos:
				snake_case__	       =   True
				return self.retrace_path(UpperCamelCase_		)

			self.closed_nodes.append(UpperCamelCase_		)
			snake_case__	       =   self.get_successors(UpperCamelCase_		)

			for child_node in successors:
				if child_node in self.closed_nodes:
					continue

				if child_node not in self.open_nodes:
					self.open_nodes.append(UpperCamelCase_		)
				else:
					# retrieve the best current path
					snake_case__	       =   self.open_nodes.pop(self.open_nodes.index(UpperCamelCase_		)		)

					if child_node.g_cost < better_node.g_cost:
						self.open_nodes.append(UpperCamelCase_		)
					else:
						self.open_nodes.append(UpperCamelCase_		)

		if not self.reached:
			return [self.start.pos]
		return None





	def   _snake_case   (		self      ,       UpperCamelCase_		)      ->		list[Node]:
		snake_case__	       =   []
		for action in delta:
			snake_case__	       =   parent.pos_x + action[1]
			snake_case__	       =   parent.pos_y + action[0]

			if not (0 <= pos_x <= len(grid[0]		) - 1 and 0 <= pos_y <= len(UpperCamelCase_		) - 1):
				continue

			if grid[pos_y][pos_x] != 0:
				continue

			successors.append(
			    Node(
			        UpperCamelCase_      ,       UpperCamelCase_      ,       self.target.pos_y      ,       self.target.pos_x      ,       parent.g_cost + 1      ,       UpperCamelCase_      ,       )		)
		return successors





	def   _snake_case   (		self      ,       UpperCamelCase_		)      ->		Path:
		snake_case__	       =   node
		snake_case__	       =   []
		while current_node is not None:
			path.append((current_node.pos_y, current_node.pos_x)		)
			snake_case__	       =   current_node.parent
		path.reverse()
		return path


if __name__ == "__main__":
			a__					:			List[str]          =     (0, 0)
			a__					:			Dict          =     (len(grid) - 1, len(grid[0]) - 1)
			for elem in grid:
						print(elem)

			print('''------''')

			a__					:			Optional[int]          =     GreedyBestFirst(init, goal)
			a__					:			Optional[int]          =     greedy_bf.search()
			if path:
						for pos_x, pos_y in path:
									a__					:			Tuple          =     2

						for elem in grid:
									print(elem)



