





'''simple docstring'''


from ...configuration_utils import PretrainedConfig
from ...utils import logging


a__			:					List[str]       						=						logging.get_logger(__name__)

a__			:					Union[str, Any]       						=						{
    'facebook/vit-mae-base': 'https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json',
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}






class     lowerCAmelCase__ (				UpperCAmelCase_    ):

       '''simple docstring'''
       _lowerCamelCase								="vit_mae"

       def __init__( self					:				Any       ,     a__					:				Any=768       ,     a__					:				List[Any]=12       ,     a__					:				Union[str, Any]=12       ,     a__					:				Optional[Any]=3072       ,     a__					:				Dict="gelu"       ,     a__					:				List[Any]=0.0       ,     a__					:				int=0.0       ,     a__					:				int=0.02       ,     a__					:				Any=1e-1_2       ,     a__					:				Any=224       ,     a__					:				List[str]=16       ,     a__					:				List[str]=3       ,     a__					:				Optional[int]=True       ,     a__					:				str=16       ,     a__					:				Union[str, Any]=512       ,     a__					:				Dict=8       ,     a__					:				int=2048       ,     a__					:				List[str]=0.75       ,     a__					:				Dict=False       ,     **a__					:				Optional[int]       ,     ):
              super().__init__(**a__						)

              UpperCAmelCase  =						hidden_size
              UpperCAmelCase  =						num_hidden_layers
              UpperCAmelCase  =						num_attention_heads
              UpperCAmelCase  =						intermediate_size
              UpperCAmelCase  =						hidden_act
              UpperCAmelCase  =						hidden_dropout_prob
              UpperCAmelCase  =						attention_probs_dropout_prob
              UpperCAmelCase  =						initializer_range
              UpperCAmelCase  =						layer_norm_eps
              UpperCAmelCase  =						image_size
              UpperCAmelCase  =						patch_size
              UpperCAmelCase  =						num_channels
              UpperCAmelCase  =						qkv_bias
              UpperCAmelCase  =						decoder_num_attention_heads
              UpperCAmelCase  =						decoder_hidden_size
              UpperCAmelCase  =						decoder_num_hidden_layers
              UpperCAmelCase  =						decoder_intermediate_size
              UpperCAmelCase  =						mask_ratio
              UpperCAmelCase  =						norm_pix_loss










'''simple docstring'''



import copy
import os
from typing import TYPE_CHECKING, List, Union


if TYPE_CHECKING:
 pass

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCamelCase   :							int         =   logging.get_logger(__name__)

__UpperCamelCase   :							int         =   {
    """kakaobrain/align-base""": """https://huggingface.co/kakaobrain/align-base/resolve/main/config.json""",
}
class 				__SCREAMING_SNAKE_CASE							(				_lowerCAmelCase  ):
      __a	       ="align_text_model"




      def __init__(	self			, lowerCamelCase=3_0522			, lowerCamelCase=768			, lowerCamelCase=12			, lowerCamelCase=12			, lowerCamelCase=3072			, lowerCamelCase="gelu"			, lowerCamelCase=0.1			, lowerCamelCase=0.1			, lowerCamelCase=512			, lowerCamelCase=2			, lowerCamelCase=0.02			, lowerCamelCase=1e-12			, lowerCamelCase=0			, lowerCamelCase="absolute"			, lowerCamelCase=True			, **lowerCamelCase			, )				->List[Any]:



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

         __a					  =     vocab_size
         __a					  =     hidden_size
         __a					  =     num_hidden_layers
         __a					  =     num_attention_heads
         __a					  =     hidden_act
         __a					  =     intermediate_size
         __a					  =     hidden_dropout_prob
         __a					  =     attention_probs_dropout_prob
         __a					  =     max_position_embeddings
         __a					  =     type_vocab_size
         __a					  =     initializer_range
         __a					  =     layer_norm_eps
         __a					  =     position_embedding_type
         __a					  =     use_cache
         __a					  =     pad_token_id






      @classmethod
      def 			__UpperCamelCase				(	cls			, lowerCamelCase			, **lowerCamelCase   )				->"PretrainedConfig":



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

         __a  ,      __a					  =     cls.get_config_dict(lowerCamelCase			, **lowerCamelCase   )

         # get the text config dict if we are loading from AlignConfig
         if config_dict.get('model_type'   ) == "align":
            __a					  =     config_dict['text_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 				__SCREAMING_SNAKE_CASE							(				_lowerCAmelCase  ):
      __a	       ="align_vision_model"




      def __init__(	self			, lowerCamelCase = 3			, lowerCamelCase = 600			, lowerCamelCase = 2.0			, lowerCamelCase = 3.1			, lowerCamelCase = 8			, lowerCamelCase = [3, 3, 5, 3, 5, 5, 3]			, lowerCamelCase = [32, 16, 24, 40, 80, 112, 192]			, lowerCamelCase = [16, 24, 40, 80, 112, 192, 320]			, lowerCamelCase = []			, lowerCamelCase = [1, 2, 2, 2, 1, 2, 1]			, lowerCamelCase = [1, 2, 2, 3, 3, 4, 1]			, lowerCamelCase = [1, 6, 6, 6, 6, 6, 6]			, lowerCamelCase = 0.25			, lowerCamelCase = "swish"			, lowerCamelCase = 2560			, lowerCamelCase = "mean"			, lowerCamelCase = 0.02			, lowerCamelCase = 0.001			, lowerCamelCase = 0.99			, lowerCamelCase = 0.2			, **lowerCamelCase			, )				->Dict:



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

         __a					  =     num_channels
         __a					  =     image_size
         __a					  =     width_coefficient
         __a					  =     depth_coefficient
         __a					  =     depth_divisor
         __a					  =     kernel_sizes
         __a					  =     in_channels
         __a					  =     out_channels
         __a					  =     depthwise_padding
         __a					  =     strides
         __a					  =     num_block_repeats
         __a					  =     expand_ratios
         __a					  =     squeeze_expansion_ratio
         __a					  =     hidden_act
         __a					  =     hidden_dim
         __a					  =     pooling_type
         __a					  =     initializer_range
         __a					  =     batch_norm_eps
         __a					  =     batch_norm_momentum
         __a					  =     drop_connect_rate
         __a					  =     sum(lowerCamelCase   ) * 4






      @classmethod
      def 			__UpperCamelCase				(	cls			, lowerCamelCase			, **lowerCamelCase   )				->"PretrainedConfig":



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

         __a  ,      __a					  =     cls.get_config_dict(lowerCamelCase			, **lowerCamelCase   )

         # get the vision config dict if we are loading from AlignConfig
         if config_dict.get('model_type'   ) == "align":
            __a					  =     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 				__SCREAMING_SNAKE_CASE							(				_lowerCAmelCase  ):
      __a	       ="align"
      __a	       =True




      def __init__(	self			, lowerCamelCase=None			, lowerCamelCase=None			, lowerCamelCase=640			, lowerCamelCase=1.0			, lowerCamelCase=0.02			, **lowerCamelCase			, )				->Union[str, Any]:



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

         if text_config is None:
            __a					  =     {}
            logger.info('text_config is None. Initializing the AlignTextConfig with default values.'   )

         if vision_config is None:
            __a					  =     {}
            logger.info('vision_config is None. Initializing the AlignVisionConfig with default values.'   )

         __a					  =     AlignTextConfig(**lowerCamelCase   )
         __a					  =     AlignVisionConfig(**lowerCamelCase   )

         __a					  =     projection_dim
         __a					  =     temperature_init_value
         __a					  =     initializer_range




      @classmethod
      def 			__UpperCamelCase				(	cls			, lowerCamelCase			, lowerCamelCase			, **lowerCamelCase   )				->int:



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






      def 			__UpperCamelCase				(	self   )				->Tuple:



         '''simple docstring'''
         __a					  =     copy.deepcopy(self.__dict__   )
         __a					  =     self.text_config.to_dict()
         __a					  =     self.vision_config.to_dict()
         __a					  =     self.__class__.model_type
         return output