






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







class 	_UpperCAmelCase  (  _A		):




    """simple docstring"""



    A          =    '''instructblip_vision_model'''
    def __init__(   self    ,	_lowerCAmelCase=1_408    ,	_lowerCAmelCase=6_144    ,	_lowerCAmelCase=39    ,	_lowerCAmelCase=16    ,	_lowerCAmelCase=224    ,	_lowerCAmelCase=14    ,	_lowerCAmelCase="gelu"    ,	_lowerCAmelCase=1e-6    ,	_lowerCAmelCase=0.0    ,	_lowerCAmelCase=1e-10    ,	_lowerCAmelCase=True    ,	**_lowerCAmelCase    ,	):



        '''simple docstring'''
        super().__init__(**_lowerCAmelCase		)

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



    @classmethod
    def 			snake_case_      (   cls    ,	_lowerCAmelCase    ,	**_lowerCAmelCase		):



        '''simple docstring'''
        cls._set_token_in_kwargs(_lowerCAmelCase		)

        lowerCAmelCase__   :Union[str, Any]      							=				cls.get_config_dict(_lowerCAmelCase    ,	**_lowerCAmelCase		)

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







class 	_UpperCAmelCase  (  _A		):




    """simple docstring"""



    A          =    '''instructblip_qformer'''
    def __init__(   self    ,	_lowerCAmelCase=30_522    ,	_lowerCAmelCase=768    ,	_lowerCAmelCase=12    ,	_lowerCAmelCase=12    ,	_lowerCAmelCase=3_072    ,	_lowerCAmelCase="gelu"    ,	_lowerCAmelCase=0.1    ,	_lowerCAmelCase=0.1    ,	_lowerCAmelCase=512    ,	_lowerCAmelCase=0.02    ,	_lowerCAmelCase=1e-12    ,	_lowerCAmelCase=0    ,	_lowerCAmelCase="absolute"    ,	_lowerCAmelCase=2    ,	_lowerCAmelCase=1_408    ,	**_lowerCAmelCase    ,	):



        '''simple docstring'''
        super().__init__(pad_token_id=_lowerCAmelCase    ,	**_lowerCAmelCase		)

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



    @classmethod
    def 			snake_case_      (   cls    ,	_lowerCAmelCase    ,	**_lowerCAmelCase		):



        '''simple docstring'''
        cls._set_token_in_kwargs(_lowerCAmelCase		)

        lowerCAmelCase__   :Union[str, Any]      							=				cls.get_config_dict(_lowerCAmelCase    ,	**_lowerCAmelCase		)

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







class 	_UpperCAmelCase  (  _A		):




    """simple docstring"""



    A          =    '''instructblip'''
    A          =    True
    def __init__(   self    ,	_lowerCAmelCase=None    ,	_lowerCAmelCase=None    ,	_lowerCAmelCase=None    ,	_lowerCAmelCase=32    ,	**_lowerCAmelCase		):



        '''simple docstring'''
        super().__init__(**_lowerCAmelCase		)

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

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

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

        lowerCAmelCase__   :Optional[int]      							=				InstructBlipVisionConfig(**_lowerCAmelCase		)
        lowerCAmelCase__   :str      							=				InstructBlipQFormerConfig(**_lowerCAmelCase		)
        lowerCAmelCase__   :int      							=				text_config["model_type"] if "model_type" in text_config else "opt"
        lowerCAmelCase__   :Optional[Any]      							=				CONFIG_MAPPING[text_model_type](**_lowerCAmelCase		)

        lowerCAmelCase__   :Optional[int]      							=				self.text_config.tie_word_embeddings
        lowerCAmelCase__   :Union[str, Any]      							=				self.text_config.is_encoder_decoder

        lowerCAmelCase__   :int      							=				num_query_tokens
        lowerCAmelCase__   :Optional[int]      							=				self.vision_config.hidden_size
        lowerCAmelCase__   :List[Any]      							=				self.text_config.model_type in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
        lowerCAmelCase__   :str      							=				1.0
        lowerCAmelCase__   :Union[str, Any]      							=				0.02
    @classmethod
    def 			snake_case_      (   cls    ,	_lowerCAmelCase    ,	_lowerCAmelCase    ,	_lowerCAmelCase    ,	**_lowerCAmelCase    ,	):



        '''simple docstring'''
        return cls(
            vision_config=vision_config.to_dict()    ,	qformer_config=qformer_config.to_dict()    ,	text_config=text_config.to_dict()    ,	**_lowerCAmelCase    ,	)



    def 			snake_case_      (   self		):



        '''simple docstring'''
        lowerCAmelCase__   :List[Any]      							=				copy.deepcopy(self.__dict__		)
        lowerCAmelCase__   :Optional[int]      							=				self.vision_config.to_dict()
        lowerCAmelCase__   :Optional[Any]      							=				self.qformer_config.to_dict()
        lowerCAmelCase__   :str      							=				self.text_config.to_dict()
        lowerCAmelCase__   :Union[str, Any]      							=				self.__class__.model_type
        return output











def 				snake_case__							(							UpperCAmelCase							:  Tuple       ):
    lowerCAmelCase__   :List[Any]      							=				len(UpperCAmelCase       )
    for i in range(length - 1       ):
        lowerCAmelCase__   :Union[str, Any]      							=				i
        for k in range(i + 1    ,			UpperCAmelCase       ):
            if collection[k] < collection[least]:
                lowerCAmelCase__   :Any      							=				k
        if least != i:
            lowerCAmelCase__							,lowerCAmelCase__   :int      							=				(collection[i], collection[least])
    return collection


if __name__ == "__main__":
 _a    :   Optional[int]        =			input("""Enter numbers separated by a comma:\n""").strip()
 _a    :   Any        =			[int(item) for item in user_input.split(""",""")]
 print(selection_sort(unsorted))



