

import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING


_UpperCamelCase     			=     logging.get_logger(__name__)

_UpperCamelCase     			=     {
    '''Salesforce/instruct-blip-flan-t5''': '''https://huggingface.co/Salesforce/instruct-blip-flan-t5/resolve/main/config.json''',
}



class        lowercase		(			A_   ):



 '''simple docstring'''


 __SCREAMING_SNAKE_CASE   				=							"instructblip_vision_model"




 def __init__(self			,			__a=1408			,			__a=6144			,			__a=39			,			__a=16			,			__a=224			,			__a=14			,			__a="gelu"			,			__a=1E-6			,			__a=0.0			,			__a=1E-1_0			,			__a=True			,			**__a			,			)					->   str:






  """simple docstring"""





  super().__init__(**snake_case__					)

  UpperCAmelCase__     							=							hidden_size
  UpperCAmelCase__     							=							intermediate_size
  UpperCAmelCase__     							=							num_hidden_layers
  UpperCAmelCase__     							=							num_attention_heads
  UpperCAmelCase__     							=							patch_size
  UpperCAmelCase__     							=							image_size
  UpperCAmelCase__     							=							initializer_range
  UpperCAmelCase__     							=							attention_dropout
  UpperCAmelCase__     							=							layer_norm_eps
  UpperCAmelCase__     							=							hidden_act
  UpperCAmelCase__     							=							qkv_bias




 @classmethod
 def     UpperCamelCase__				(cls			,			__a			,			**__a					)					->   "PretrainedConfig":






  """simple docstring"""





  cls._set_token_in_kwargs(snake_case__					)

  UpperCAmelCase__     							=							cls.get_config_dict(snake_case__			,			**snake_case__					)

  # get the vision config dict if we are loading from InstructBlipConfig
  if config_dict.get('model_type'					) == "instructblip":
   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(snake_case__			,			**snake_case__					)







class        lowercase		(			A_   ):



 '''simple docstring'''


 __SCREAMING_SNAKE_CASE   				=							"instructblip_qformer"




 def __init__(self			,			__a=30522			,			__a=768			,			__a=12			,			__a=12			,			__a=3072			,			__a="gelu"			,			__a=0.1			,			__a=0.1			,			__a=512			,			__a=0.02			,			__a=1E-1_2			,			__a=0			,			__a="absolute"			,			__a=2			,			__a=1408			,			**__a			,			)					->   Union[str, Any]:






  """simple docstring"""





  super().__init__(pad_token_id=snake_case__			,			**snake_case__					)

  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__     							=							initializer_range
  UpperCAmelCase__     							=							layer_norm_eps
  UpperCAmelCase__     							=							position_embedding_type
  UpperCAmelCase__     							=							cross_attention_frequency
  UpperCAmelCase__     							=							encoder_hidden_size




 @classmethod
 def     UpperCamelCase__				(cls			,			__a			,			**__a					)					->   "PretrainedConfig":






  """simple docstring"""





  cls._set_token_in_kwargs(snake_case__					)

  UpperCAmelCase__     							=							cls.get_config_dict(snake_case__			,			**snake_case__					)

  # get the qformer config dict if we are loading from InstructBlipConfig
  if config_dict.get('model_type'					) == "instructblip":
   UpperCAmelCase__     							=							config_dict["qformer_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(snake_case__			,			**snake_case__					)







class        lowercase		(			A_   ):



 '''simple docstring'''


 __SCREAMING_SNAKE_CASE   				=							"instructblip"
 __SCREAMING_SNAKE_CASE   				=							True




 def __init__(self			,			__a=None			,			__a=None			,			__a=None			,			__a=32			,			**__a					)					->   Union[str, Any]:






  """simple docstring"""





  super().__init__(**snake_case__					)

  if vision_config is None:
   UpperCAmelCase__     							=							{}
   logger.info('vision_config is None. initializing the InstructBlipVisionConfig with default values.'					)

  if qformer_config is None:
   UpperCAmelCase__     							=							{}
   logger.info('qformer_config is None. Initializing the InstructBlipQFormerConfig with default values.'					)

  if text_config is None:
   UpperCAmelCase__     							=							{}
   logger.info('text_config is None. Initializing the text config with default values (`OPTConfig`).'					)

  UpperCAmelCase__     							=							InstructBlipVisionConfig(**snake_case__					)
  UpperCAmelCase__     							=							InstructBlipQFormerConfig(**snake_case__					)
  UpperCAmelCase__     							=							text_config["model_type"] if "model_type" in text_config else "opt"
  UpperCAmelCase__     							=							CONFIG_MAPPING[text_model_type](**snake_case__					)

  UpperCAmelCase__     							=							self.text_config.tie_word_embeddings
  UpperCAmelCase__     							=							self.text_config.is_encoder_decoder

  UpperCAmelCase__     							=							num_query_tokens
  UpperCAmelCase__     							=							self.vision_config.hidden_size
  UpperCAmelCase__     							=							self.text_config.model_type in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
  UpperCAmelCase__     							=							1.0
  UpperCAmelCase__     							=							0.02




 @classmethod
 def     UpperCamelCase__				(cls			,			__a			,			__a			,			__a			,			**__a			,			)					->   Dict:






  """simple docstring"""





  return cls(
      vision_config=vision_config.to_dict()			,			qformer_config=qformer_config.to_dict()			,			text_config=text_config.to_dict()			,			**snake_case__			,			)




 def     UpperCamelCase__				(self					)					->   Dict:






  """simple docstring"""





  UpperCAmelCase__     							=							copy.deepcopy(self.__dict__					)
  UpperCAmelCase__     							=							self.vision_config.to_dict()
  UpperCAmelCase__     							=							self.qformer_config.to_dict()
  UpperCAmelCase__     							=							self.text_config.to_dict()
  UpperCAmelCase__     							=							self.__class__.model_type
  return output





class     UpperCAmelCase						:



   def __init__(self						:   Optional[Any]       ,		snake_case__						:   str = ""       ,		snake_case__						:   bool = False					)						->      None:


          '''simple docstring'''


          snake_case			:  dict[str, RadixNode]     							= {}

          # A node will be a leaf if the tree contains its word
          snake_case			:  int     							= is_leaf

          snake_case			:  Dict     							= prefix



   def 							_SCREAMING_SNAKE_CASE  (self						:   Union[str, Any]       ,		snake_case__						:   str					)						->      tuple[str, str, str]:


          '''simple docstring'''


          snake_case			:  Any     							= 0
          for q, w in zip(self.prefix       ,		snake_case__					):
                 if q != w:
                        break

                 x += 1

          return self.prefix[:x], self.prefix[x:], word[x:]



   def 							_SCREAMING_SNAKE_CASE  (self						:   Tuple       ,		snake_case__						:   list[str]					)						->      None:


          '''simple docstring'''


          for word in words:
                 self.insert(snake_case__					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   int       ,		snake_case__						:   str					)						->      None:


          '''simple docstring'''


          if self.prefix == word:
                 snake_case			:  str     							= True

          # Case 2: The node has no edges that have a prefix to the word
          # Solution: We create an edge from the current node to a new one
          # containing the word
          elif word[0] not in self.nodes:
                 snake_case			:  Optional[int]     							= RadixNode(prefix=snake_case__       ,		is_leaf=snake_case__					)

          else:
                 snake_case			:  Dict     							= self.nodes[word[0]]
                 snake_case							,   snake_case							,   snake_case			:  int     							= incoming_node.match(
                     snake_case__					)

                 # Case 3: The node prefix is equal to the matching
                 # Solution: We insert remaining word on the next node
                 if remaining_prefix == "":
                        self.nodes[matching_string[0]].insert(snake_case__					)

                 # Case 4: The word is greater equal to the matching
                 # Solution: Create a node in between both nodes, change
                 # prefixes and add the new node for the remaining word
                 else:
                        snake_case			:  Tuple     							= remaining_prefix

                        snake_case			:  Dict     							= self.nodes[matching_string[0]]
                        snake_case			:  Tuple     							= RadixNode(snake_case__       ,		snake_case__					)
                        snake_case			:  List[str]     							= aux_node

                        if remaining_word == "":
                               snake_case			:  Tuple     							= True
                        else:
                               self.nodes[matching_string[0]].insert(snake_case__					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   Tuple       ,		snake_case__						:   str					)						->      bool:


          '''simple docstring'''


          snake_case			:  Union[str, Any]     							= self.nodes.get(word[0]       ,		snake_case__					)
          if not incoming_node:
                 return False
          else:
                 snake_case							,   snake_case							,   snake_case			:  Optional[int]     							= incoming_node.match(
                     snake_case__					)
                 # If there is remaining prefix, the word can't be on the tree
                 if remaining_prefix != "":
                        return False
                 # This applies when the word and the prefix are equal
                 elif remaining_word == "":
                        return incoming_node.is_leaf
                 # We have word remaining so we check the next node
                 else:
                        return incoming_node.find(snake_case__					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   Optional[Any]       ,		snake_case__						:   str					)						->      bool:


          '''simple docstring'''


          snake_case			:  Optional[Any]     							= self.nodes.get(word[0]       ,		snake_case__					)
          if not incoming_node:
                 return False
          else:
                 snake_case							,   snake_case							,   snake_case			:  Optional[Any]     							= incoming_node.match(
                     snake_case__					)
                 # If there is remaining prefix, the word can't be on the tree
                 if remaining_prefix != "":
                        return False
                 # We have word remaining so we check the next node
                 elif remaining_word != "":
                        return incoming_node.delete(snake_case__					)
                 else:
                        # If it is not a leaf, we don't have to delete
                        if not incoming_node.is_leaf:
                               return False
                        else:
                               # We delete the nodes if no edges go from it
                               if len(incoming_node.nodes					) == 0:
                                      del self.nodes[word[0]]
                                      # We merge the current node with its only child
                                      if len(self.nodes					) == 1 and not self.is_leaf:
                                             snake_case			:  List[Any]     							= list(self.nodes.values()					)[0]
                                             snake_case			:  Optional[int]     							= merging_node.is_leaf
                                             self.prefix += merging_node.prefix
                                             snake_case			:  str     							= merging_node.nodes
                    # If there is more than 1 edge, we just mark it as non-leaf
                               elif len(incoming_node.nodes					) > 1:
                                      snake_case			:  List[Any]     							= False
                               # If there is 1 edge, we merge it with its child
                               else:
                                      snake_case			:  Any     							= list(incoming_node.nodes.values()					)[0]
                                      snake_case			:  Any     							= merging_node.is_leaf
                                      incoming_node.prefix += merging_node.prefix
                                      snake_case			:  Union[str, Any]     							= merging_node.nodes

                               return True



   def 							_SCREAMING_SNAKE_CASE  (self						:   Any       ,		snake_case__						:   int = 0					)						->      None:


          '''simple docstring'''


          if self.prefix != "":
                 print("-" * height       ,		self.prefix       ,		"  (leaf)" if self.is_leaf else ""					)

          for value in self.nodes.values():
                 value.print_tree(height + 1					)



def      UpperCamelCase   (       ):
       snake_case			:  Dict     							= "banana bananas bandana band apple all beast".split()
       snake_case			:  Tuple     							= RadixNode()
       root.insert_many(__lowerCamelCase       )

       assert all(root.find(__lowerCamelCase       ) for word in words       )
       assert not root.find("bandanas"       )
       assert not root.find("apps"       )
       root.delete("all"       )
       assert not root.find("all"       )
       root.delete("banana"       )
       assert not root.find("banana"       )
       assert root.find("bananas"       )

       return True


def      UpperCamelCase   (       ):
       assert test_trie()


def      UpperCamelCase   (       ):
       snake_case			:  Union[str, Any]     							= RadixNode()
       snake_case			:  List[str]     							= "banana bananas bandanas bandana band apple all beast".split()
       root.insert_many(__lowerCamelCase       )

       print("Words:"							,   __lowerCamelCase       )
       print("Tree:"       )
       root.print_tree()


if __name__ == "__main__":
   main()





