






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						:			str     	=					logging.get_logger(__name__)

a						:			Any     	=					{
    "Salesforce/instruct-blip-flan-t5": "https://huggingface.co/Salesforce/instruct-blip-flan-t5/resolve/main/config.json",
}
class        a       (					lowercase__  ):



      """simple docstring"""


      a    :					Tuple							=      'instructblip_vision_model'
      def __init__( self   :     Tuple						, __lowercase   :     List[str]=1408						, __lowercase   :     List[Any]=6144						, __lowercase   :     Optional[int]=39						, __lowercase   :     Optional[int]=16						, __lowercase   :     List[Any]=224						, __lowercase   :     int=14						, __lowercase   :     Optional[int]="gelu"						, __lowercase   :     List[Any]=1e-6						, __lowercase   :     Optional[Any]=0.0						, __lowercase   :     int=1e-1_0						, __lowercase   :     Optional[Any]=True						, **__lowercase   :     str						, )				-> List[Any]:
        super().__init__(**__lowercase   )

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




      @classmethod
      def       UpperCAmelCase ( cls   :     Tuple						, __lowercase   :     Tuple						, **__lowercase   :     Any   )				-> int:
        cls._set_token_in_kwargs(__lowercase   )

        __UpperCAmelCase				:      Dict	 =    cls.get_config_dict(__lowercase						, **__lowercase   )

        # get the vision config dict if we are loading from InstructBlipConfig
        if config_dict.get("""model_type"""   ) == "instructblip":
          __UpperCAmelCase				:      Optional[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(__lowercase						, **__lowercase   )


class        a       (					lowercase__  ):



      """simple docstring"""


      a    :					str							=      'instructblip_qformer'
      def __init__( self   :     List[Any]						, __lowercase   :     List[Any]=30522						, __lowercase   :     int=768						, __lowercase   :     Tuple=12						, __lowercase   :     Union[str, Any]=12						, __lowercase   :     Optional[int]=3072						, __lowercase   :     str="gelu"						, __lowercase   :     List[Any]=0.1						, __lowercase   :     Tuple=0.1						, __lowercase   :     int=512						, __lowercase   :     List[Any]=0.02						, __lowercase   :     str=1e-1_2						, __lowercase   :     Union[str, Any]=0						, __lowercase   :     Tuple="absolute"						, __lowercase   :     List[Any]=2						, __lowercase   :     List[Any]=1408						, **__lowercase   :     Dict						, )				-> Tuple:
        super().__init__(pad_token_id=__lowercase						, **__lowercase   )

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




      @classmethod
      def       UpperCAmelCase ( cls   :     Union[str, Any]						, __lowercase   :     Optional[int]						, **__lowercase   :     Dict   )				-> Optional[Any]:
        cls._set_token_in_kwargs(__lowercase   )

        __UpperCAmelCase				:      Union[str, Any]	 =    cls.get_config_dict(__lowercase						, **__lowercase   )

        # 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(__lowercase						, **__lowercase   )


class        a       (					lowercase__  ):



      """simple docstring"""


      a    :					int							=      'instructblip'
      a    :					List[Any]							=      True
      def __init__( self   :     Optional[int]						, __lowercase   :     Union[str, Any]=None						, __lowercase   :     List[str]=None						, __lowercase   :     Dict=None						, __lowercase   :     Union[str, Any]=32						, **__lowercase   :     int   )				-> int:
        super().__init__(**__lowercase   )

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

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

        if text_config is None:
          __UpperCAmelCase				:      Union[str, Any]	 =    {}
          logger.info("""text_config is None. Initializing the text config with default values (`OPTConfig`)."""   )

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

        __UpperCAmelCase				:      Any	 =    self.text_config.tie_word_embeddings
        __UpperCAmelCase				:      Optional[Any]	 =    self.text_config.is_encoder_decoder

        __UpperCAmelCase				:      str	 =    num_query_tokens
        __UpperCAmelCase				:      Dict	 =    self.vision_config.hidden_size
        __UpperCAmelCase				:      List[Any]	 =    self.text_config.model_type in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
        __UpperCAmelCase				:      List[str]	 =    1.0
        __UpperCAmelCase				:      str	 =    0.02
      @classmethod
      def       UpperCAmelCase ( cls   :     str						, __lowercase   :     Any						, __lowercase   :     Tuple						, __lowercase   :     Optional[int]						, **__lowercase   :     Any						, )				-> Optional[int]:
        return cls(
            vision_config=vision_config.to_dict()						, qformer_config=qformer_config.to_dict()						, text_config=text_config.to_dict()						, **__lowercase						, )




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






'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_UpperCamelCase 							=  logging.get_logger(__name__)

_UpperCamelCase 							=  {
    """microsoft/beit-base-patch16-224-pt22k""": (
        """https://huggingface.co/microsoft/beit-base-patch16-224-pt22k/resolve/main/config.json"""
    ),
    # See all BEiT models at https://huggingface.co/models?filter=beit
}







class 							__magic_name__	(       lowerCAmelCase ):

     """simple docstring"""






     lowerCamelCase__       						=				'beit'


     def __init__(   self			,     lowerCamelCase=8192			,     lowerCamelCase=768			,     lowerCamelCase=12			,     lowerCamelCase=12			,     lowerCamelCase=3072			,     lowerCamelCase="gelu"			,     lowerCamelCase=0.0			,     lowerCamelCase=0.0			,     lowerCamelCase=0.02			,     lowerCamelCase=1E-12			,     lowerCamelCase=224			,     lowerCamelCase=16			,     lowerCamelCase=3			,     lowerCamelCase=False			,     lowerCamelCase=False			,     lowerCamelCase=False			,     lowerCamelCase=False			,     lowerCamelCase=0.1			,     lowerCamelCase=0.1			,     lowerCamelCase=True			,     lowerCamelCase=[3, 5, 7, 11]			,     lowerCamelCase=[1, 2, 3, 6]			,     lowerCamelCase=True			,     lowerCamelCase=0.4			,     lowerCamelCase=256			,     lowerCamelCase=1			,     lowerCamelCase=False			,     lowerCamelCase=255			,     **lowerCamelCase			,     ):


          '''simple docstring'''





          super().__init__(**lowerCamelCase		)

          __A	:       int      =							vocab_size
          __A	:       Tuple      =							hidden_size
          __A	:       List[str]      =							num_hidden_layers
          __A	:       Optional[int]      =							num_attention_heads
          __A	:       Dict      =							intermediate_size
          __A	:       Optional[int]      =							hidden_act
          __A	:       str      =							hidden_dropout_prob
          __A	:       Dict      =							attention_probs_dropout_prob
          __A	:       int      =							initializer_range
          __A	:       List[str]      =							layer_norm_eps

          __A	:       str      =							image_size
          __A	:       Optional[int]      =							patch_size
          __A	:       List[Any]      =							num_channels
          __A	:       List[str]      =							use_mask_token
          __A	:       Union[str, Any]      =							use_absolute_position_embeddings
          __A	:       Optional[int]      =							use_relative_position_bias
          __A	:       int      =							use_shared_relative_position_bias
          __A	:       int      =							layer_scale_init_value
          __A	:       Union[str, Any]      =							drop_path_rate
          __A	:       Dict      =							use_mean_pooling
          # decode head attributes (semantic segmentation)
          __A	:       List[str]      =							out_indices
          __A	:       str      =							pool_scales
          # auxiliary head attributes (semantic segmentation)
          __A	:       List[str]      =							use_auxiliary_head
          __A	:       Tuple      =							auxiliary_loss_weight
          __A	:       Dict      =							auxiliary_channels
          __A	:       Tuple      =							auxiliary_num_convs
          __A	:       List[str]      =							auxiliary_concat_input
          __A	:       int      =							semantic_loss_ignore_index







class 							__magic_name__	(       lowerCAmelCase ):

     """simple docstring"""






     lowerCamelCase__       						=				version.parse('1.11' )


     @property
     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          return OrderedDict(
              [
                  ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
              ]		)


     @property
     def lowerCAmelCase__  (   self		):


          '''simple docstring'''





          return 1E-4

