"""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


_UpperCamelCase  :		Optional[int]           =       logging.get_logger(__name__)

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


class 	UpperCAmelCase_      (       __A):
      lowerCamelCase__						:       List[Any]					    =    "instructblip_vision_model"


      def __init__(  self						,     a=1_4_0_8						,     a=6_1_4_4						,     a=3_9						,     a=1_6						,     a=2_2_4						,     a=1_4						,     a="gelu"						,     a=1e-6						,     a=0.0						,     a=1e-10						,     a=True						,     **a						,     )			->   Union[str, Any]:
             super().__init__(**a				)

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


      @classmethod
      def 						_UpperCAmelCase			(  cls						,     a						,     **a				)			->   "PretrainedConfig":
             cls._set_token_in_kwargs(a				)

             lowercase__     :						Union[str, Any]         =      cls.get_config_dict(a						,     **a				)

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





class 	UpperCAmelCase_      (       __A):
      lowerCamelCase__						:       str					    =    "instructblip_qformer"


      def __init__(  self						,     a=3_0_5_2_2						,     a=7_6_8						,     a=1_2						,     a=1_2						,     a=3_0_7_2						,     a="gelu"						,     a=0.1						,     a=0.1						,     a=5_1_2						,     a=0.02						,     a=1e-12						,     a=0						,     a="absolute"						,     a=2						,     a=1_4_0_8						,     **a						,     )			->   str:
             super().__init__(pad_token_id=a						,     **a				)

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


      @classmethod
      def 						_UpperCAmelCase			(  cls						,     a						,     **a				)			->   "PretrainedConfig":
             cls._set_token_in_kwargs(a				)

             lowercase__     :						Optional[Any]         =      cls.get_config_dict(a						,     **a				)

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





class 	UpperCAmelCase_      (       __A):
      lowerCamelCase__						:       Any					    =    "instructblip"
      lowerCamelCase__						:       Dict					    =    True


      def __init__(  self						,     a=None						,     a=None						,     a=None						,     a=3_2						,     **a				)			->   List[str]:
             super().__init__(**a				)

             if vision_config is None:
                    lowercase__     :						Optional[int]         =      {}
                    logger.info('vision_config is None. initializing the InstructBlipVisionConfig with default values.'				)

             if qformer_config is None:
                    lowercase__     :						Union[str, Any]         =      {}
                    logger.info('qformer_config is None. Initializing the InstructBlipQFormerConfig with default values.'				)

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

             lowercase__     :						int         =      InstructBlipVisionConfig(**a				)
             lowercase__     :						Union[str, Any]         =      InstructBlipQFormerConfig(**a				)
             lowercase__     :						Union[str, Any]         =      text_config["model_type"] if "model_type" in text_config else "opt"
             lowercase__     :						Optional[Any]         =      CONFIG_MAPPING[text_model_type](**a				)

             lowercase__     :						Union[str, Any]         =      self.text_config.tie_word_embeddings
             lowercase__     :						Union[str, Any]         =      self.text_config.is_encoder_decoder

             lowercase__     :						str         =      num_query_tokens
             lowercase__     :						Optional[Any]         =      self.vision_config.hidden_size
             lowercase__     :						Optional[Any]         =      self.text_config.model_type in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
             lowercase__     :						Optional[Any]         =      1.0
             lowercase__     :						Tuple         =      0.02


      @classmethod
      def 						_UpperCAmelCase			(  cls						,     a						,     a						,     a						,     **a						,     )			->   List[str]:
             return cls(
                 vision_config=vision_config.to_dict()						,     qformer_config=qformer_config.to_dict()						,     text_config=text_config.to_dict()						,     **a						,     )


      def 						_UpperCAmelCase			(  self				)			->   Tuple:
             lowercase__     :						Union[str, Any]         =      copy.deepcopy(self.__dict__				)
             lowercase__     :						Any         =      self.vision_config.to_dict()
             lowercase__     :						Union[str, Any]         =      self.qformer_config.to_dict()
             lowercase__     :						Tuple         =      self.text_config.to_dict()
             lowercase__     :						int         =      self.__class__.model_type
             return output




def 			lowerCamelCase__			(       _a):
	if not isinstance(_a				,      _a):
		SCREAMING_SNAKE_CASE :   Tuple					  =							f"Input value of [number={number}] must be an integer"
		raise TypeError(_a)
	if number < 0:
		return False
	SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							number * number
	while number > 0:
		if number % 10 != number_square % 10:
			return False
		number //= 10
		number_square //= 10
	return True


if __name__ == "__main__":
			import doctest

			doctest.testmod()