'''simple docstring'''




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


_a   :	Any 							=   logging.get_logger(__name__)

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






class 		__A       (__magic_name__   ):
       snake_case       :Any				    =					"instructblip_vision_model"






       def __init__(      self				,     UpperCamelCase_=14_08				,     UpperCamelCase_=61_44				,     UpperCamelCase_=39				,     UpperCamelCase_=16				,     UpperCamelCase_=2_24				,     UpperCamelCase_=14				,     UpperCamelCase_="gelu"				,     UpperCamelCase_=1E-6				,     UpperCamelCase_=0.0				,     UpperCamelCase_=1E-10				,     UpperCamelCase_=True				,     **UpperCamelCase_				,     ):
              super().__init__(**UpperCamelCase_      )

              __UpperCAmelCase  :				List[Any]       				=		hidden_size
              __UpperCAmelCase  :				Optional[int]       				=		intermediate_size
              __UpperCAmelCase  :				Tuple       				=		num_hidden_layers
              __UpperCAmelCase  :				List[str]       				=		num_attention_heads
              __UpperCAmelCase  :				Union[str, Any]       				=		patch_size
              __UpperCAmelCase  :				Dict       				=		image_size
              __UpperCAmelCase  :				List[Any]       				=		initializer_range
              __UpperCAmelCase  :				Tuple       				=		attention_dropout
              __UpperCAmelCase  :				Tuple       				=		layer_norm_eps
              __UpperCAmelCase  :				Union[str, Any]       				=		hidden_act
              __UpperCAmelCase  :				Tuple       				=		qkv_bias







       @classmethod
       def 			_snake_case						(      cls				,     UpperCamelCase_				,     **UpperCamelCase_      ):
              cls._set_token_in_kwargs(UpperCamelCase_      )

              __UpperCAmelCase				, __UpperCAmelCase  :				Any       				=		cls.get_config_dict(UpperCamelCase_				,     **UpperCamelCase_      )

              # get the vision config dict if we are loading from InstructBlipConfig
              if config_dict.get("model_type"      ) == "instructblip":
                     __UpperCAmelCase  :				Any       				=		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 		__A       (__magic_name__   ):
       snake_case       :Any				    =					"instructblip_qformer"






       def __init__(      self				,     UpperCamelCase_=3_05_22				,     UpperCamelCase_=7_68				,     UpperCamelCase_=12				,     UpperCamelCase_=12				,     UpperCamelCase_=30_72				,     UpperCamelCase_="gelu"				,     UpperCamelCase_=0.1				,     UpperCamelCase_=0.1				,     UpperCamelCase_=5_12				,     UpperCamelCase_=0.0_2				,     UpperCamelCase_=1E-12				,     UpperCamelCase_=0				,     UpperCamelCase_="absolute"				,     UpperCamelCase_=2				,     UpperCamelCase_=14_08				,     **UpperCamelCase_				,     ):
              super().__init__(pad_token_id=UpperCamelCase_				,     **UpperCamelCase_      )

              __UpperCAmelCase  :				List[Any]       				=		vocab_size
              __UpperCAmelCase  :				str       				=		hidden_size
              __UpperCAmelCase  :				List[Any]       				=		num_hidden_layers
              __UpperCAmelCase  :				List[Any]       				=		num_attention_heads
              __UpperCAmelCase  :				List[Any]       				=		hidden_act
              __UpperCAmelCase  :				Any       				=		intermediate_size
              __UpperCAmelCase  :				Dict       				=		hidden_dropout_prob
              __UpperCAmelCase  :				List[str]       				=		attention_probs_dropout_prob
              __UpperCAmelCase  :				int       				=		max_position_embeddings
              __UpperCAmelCase  :				Any       				=		initializer_range
              __UpperCAmelCase  :				Any       				=		layer_norm_eps
              __UpperCAmelCase  :				str       				=		position_embedding_type
              __UpperCAmelCase  :				Optional[Any]       				=		cross_attention_frequency
              __UpperCAmelCase  :				int       				=		encoder_hidden_size







       @classmethod
       def 			_snake_case						(      cls				,     UpperCamelCase_				,     **UpperCamelCase_      ):
              cls._set_token_in_kwargs(UpperCamelCase_      )

              __UpperCAmelCase				, __UpperCAmelCase  :				List[str]       				=		cls.get_config_dict(UpperCamelCase_				,     **UpperCamelCase_      )

              # get the qformer config dict if we are loading from InstructBlipConfig
              if config_dict.get("model_type"      ) == "instructblip":
                     __UpperCAmelCase  :				int       				=		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(UpperCamelCase_				,     **UpperCamelCase_      )






class 		__A       (__magic_name__   ):
       snake_case       :Optional[int]				    =					"instructblip"
       snake_case       :Union[str, Any]				    =					True






       def __init__(      self				,     UpperCamelCase_=None				,     UpperCamelCase_=None				,     UpperCamelCase_=None				,     UpperCamelCase_=32				,     **UpperCamelCase_      ):
              super().__init__(**UpperCamelCase_      )

              if vision_config is None:
                     __UpperCAmelCase  :				Optional[Any]       				=		{}
                     logger.info("vision_config is None. initializing the InstructBlipVisionConfig with default values."      )

              if qformer_config is None:
                     __UpperCAmelCase  :				Dict       				=		{}
                     logger.info("qformer_config is None. Initializing the InstructBlipQFormerConfig with default values."      )

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

              __UpperCAmelCase  :				Any       				=		InstructBlipVisionConfig(**UpperCamelCase_      )
              __UpperCAmelCase  :				List[str]       				=		InstructBlipQFormerConfig(**UpperCamelCase_      )
              __UpperCAmelCase  :				Union[str, Any]       				=		text_config["model_type"] if "model_type" in text_config else "opt"
              __UpperCAmelCase  :				Union[str, Any]       				=		CONFIG_MAPPING[text_model_type](**UpperCamelCase_      )

              __UpperCAmelCase  :				Tuple       				=		self.text_config.tie_word_embeddings
              __UpperCAmelCase  :				str       				=		self.text_config.is_encoder_decoder

              __UpperCAmelCase  :				List[Any]       				=		num_query_tokens
              __UpperCAmelCase  :				str       				=		self.vision_config.hidden_size
              __UpperCAmelCase  :				Optional[Any]       				=		self.text_config.model_type in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
              __UpperCAmelCase  :				Optional[int]       				=		1.0
              __UpperCAmelCase  :				List[str]       				=		0.0_2






       @classmethod
       def 			_snake_case						(      cls				,     UpperCamelCase_				,     UpperCamelCase_				,     UpperCamelCase_				,     **UpperCamelCase_				,     ):
              return cls(
                  vision_config=vision_config.to_dict()				,     qformer_config=qformer_config.to_dict()				,     text_config=text_config.to_dict()				,     **UpperCamelCase_				,     )







       def 			_snake_case						(      self      ):
              __UpperCAmelCase  :				int       				=		copy.deepcopy(self.__dict__      )
              __UpperCAmelCase  :				int       				=		self.vision_config.to_dict()
              __UpperCAmelCase  :				Optional[int]       				=		self.qformer_config.to_dict()
              __UpperCAmelCase  :				List[Any]       				=		self.text_config.to_dict()
              __UpperCAmelCase  :				List[Any]       				=		self.__class__.model_type
              return output







'''simple docstring'''




class 		__A       :






       def __init__(      self				,     UpperCamelCase_      ):
              __UpperCAmelCase  :				Any       				=		set_counts
              __UpperCAmelCase  :				int       				=		max(UpperCamelCase_      )
              __UpperCAmelCase  :				List[str]       				=		len(UpperCamelCase_      )
              __UpperCAmelCase  :				Any       				=		[1] * num_sets
              __UpperCAmelCase  :				Any       				=		list(range(UpperCamelCase_      )      )






       def 			_snake_case						(      self				,     UpperCamelCase_				,     UpperCamelCase_      ):
              __UpperCAmelCase  :				Optional[int]       				=		self.get_parent(UpperCamelCase_      )
              __UpperCAmelCase  :				List[Any]       				=		self.get_parent(UpperCamelCase_      )

              if src_parent == dst_parent:
                     return False

              if self.ranks[dst_parent] >= self.ranks[src_parent]:
                     self.set_counts[dst_parent] += self.set_counts[src_parent]
                     __UpperCAmelCase  :				Optional[Any]       				=		0
                     __UpperCAmelCase  :				List[Any]       				=		dst_parent
                     if self.ranks[dst_parent] == self.ranks[src_parent]:
                            self.ranks[dst_parent] += 1
                     __UpperCAmelCase  :				Union[str, Any]       				=		self.set_counts[dst_parent]
              else:
                     self.set_counts[src_parent] += self.set_counts[dst_parent]
                     __UpperCAmelCase  :				Union[str, Any]       				=		0
                     __UpperCAmelCase  :				Dict       				=		src_parent
                     __UpperCAmelCase  :				Dict       				=		self.set_counts[src_parent]

              __UpperCAmelCase  :				Dict       				=		max(self.max_set				,     UpperCamelCase_      )
              return True







       def 			_snake_case						(      self				,     UpperCamelCase_      ):
              if self.parents[disj_set] == disj_set:
                     return disj_set
              __UpperCAmelCase  :				str       				=		self.get_parent(self.parents[disj_set]      )
              return self.parents[disj_set]






