


'''simple docstring'''

import copy
import os
from typing import Union

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


lowerCAmelCase				:int        =      logging.get_logger(__name__)

lowerCAmelCase				:Optional[int]        =      {
    '''google/pix2struct-textcaps-base''': (
        '''https://huggingface.co/google/pix2struct-textcaps-base/resolve/main/config.json'''
    ),
}
class _lowerCamelCase	(						lowercase__							):



		'''simple docstring'''







		A_     :      Optional[Any]				   =    """pix2struct_text_model"""
		A_     :      Optional[Any]				   =    ["""past_key_values"""]
		A_     :      Optional[Any]				   =    {
		    """hidden_size""": """hidden_size""",
		    """num_attention_heads""": """num_heads""",
		    """num_hidden_layers""": """num_layers""",
		}







		def __init__( self		:						Dict  ,					_A		:						Any=50244  ,					_A		:						Tuple=768  ,					_A		:						Dict=64  ,					_A		:						Tuple=2048  ,					_A		:						Union[str, Any]=12  ,					_A		:						List[str]=12  ,					_A		:						Union[str, Any]=32  ,					_A		:						Union[str, Any]=128  ,					_A		:						Optional[int]=0.1  ,					_A		:						Any=1E-6  ,					_A		:						Optional[int]=1.0  ,					_A		:						Optional[Any]="gelu_new"  ,					_A		:						Optional[Any]=0  ,					_A		:						Dict=False  ,					_A		:						Tuple=0  ,					_A		:						List[Any]=1  ,					_A		:						Optional[int]=False  ,					_A		:						Dict=True  ,					**_A		:						List[str]  ,					)  ->			Union[str, Any]:
			__magic_name__	:   str					     =					vocab_size
			__magic_name__	:   Tuple					     =					hidden_size
			__magic_name__	:   List[str]					     =					d_kv
			__magic_name__	:   List[str]					     =					d_ff
			__magic_name__	:   Dict					     =					num_layers
			__magic_name__	:   Dict					     =					num_heads
			__magic_name__	:   str					     =					relative_attention_num_buckets
			__magic_name__	:   int					     =					relative_attention_max_distance
			__magic_name__	:   Union[str, Any]					     =					dropout_rate
			__magic_name__	:   List[str]					     =					layer_norm_epsilon
			__magic_name__	:   Optional[Any]					     =					initializer_factor
			__magic_name__	:   List[Any]					     =					use_cache

			__magic_name__	:   List[str]					     =					eos_token_id
			__magic_name__	:   Optional[Any]					     =					decoder_start_token_id

			# for backwards compatibility
			__magic_name__	:   int					     =					dense_act_fn

			super().__init__(
			    pad_token_id=_A  ,					eos_token_id=_A  ,					decoder_start_token_id=_A  ,					tie_word_embeddings=_A  ,					is_decoder=_A  ,					**_A  ,					)







		@classmethod
		def        __lowerCAmelCase		( cls		:						Dict  ,					_A		:						Union[str, os.PathLike]  ,					**_A		:						Dict      )  ->			"PretrainedConfig":
			cls._set_token_in_kwargs(_A      )

			__magic_name__     ,    __magic_name__	:   Any					     =					cls.get_config_dict(_A  ,					**_A      )

			# get the text config dict if we are loading from Pix2StructConfig
			if config_dict.get('model_type'      ) == "pix2struct":
				__magic_name__	:   List[str]					     =					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(_A  ,					**_A      )







class _lowerCamelCase	(						lowercase__							):



		'''simple docstring'''







		A_     :      List[Any]				   =    """pix2struct_vision_model"""







		def __init__( self		:						Dict  ,					_A		:						Dict=768  ,					_A		:						int=768  ,					_A		:						Optional[int]=2048  ,					_A		:						Tuple=64  ,					_A		:						str=12  ,					_A		:						Optional[Any]=12  ,					_A		:						int="gelu_new"  ,					_A		:						Dict=1E-6  ,					_A		:						str=0.0  ,					_A		:						List[str]=0.0  ,					_A		:						int=1E-10  ,					_A		:						Any=1.0  ,					_A		:						Optional[int]=4096  ,					_A		:						int=32  ,					_A		:						Tuple=128  ,					**_A		:						Union[str, Any]  ,					)  ->			Optional[int]:
			super().__init__(**_A      )

			__magic_name__	:   Any					     =					hidden_size
			__magic_name__	:   Dict					     =					patch_embed_hidden_size
			__magic_name__	:   Optional[Any]					     =					d_ff
			__magic_name__	:   Optional[int]					     =					dropout_rate
			__magic_name__	:   List[Any]					     =					num_hidden_layers
			__magic_name__	:   Union[str, Any]					     =					num_attention_heads
			__magic_name__	:   int					     =					initializer_range
			__magic_name__	:   Optional[int]					     =					initializer_factor
			__magic_name__	:   List[str]					     =					attention_dropout
			__magic_name__	:   List[Any]					     =					layer_norm_eps
			__magic_name__	:   int					     =					dense_act_fn
			__magic_name__	:   List[Any]					     =					seq_len
			__magic_name__	:   int					     =					relative_attention_num_buckets
			__magic_name__	:   Any					     =					relative_attention_max_distance
			__magic_name__	:   Tuple					     =					d_kv







		@classmethod
		def        __lowerCAmelCase		( cls		:						Union[str, Any]  ,					_A		:						Union[str, os.PathLike]  ,					**_A		:						Union[str, Any]      )  ->			"PretrainedConfig":
			cls._set_token_in_kwargs(_A      )

			__magic_name__     ,    __magic_name__	:   List[str]					     =					cls.get_config_dict(_A  ,					**_A      )

			# get the vision config dict if we are loading from Pix2StructConfig
			if config_dict.get('model_type'      ) == "pix2struct":
				__magic_name__	:   int					     =					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 _lowerCamelCase	(						lowercase__							):



		'''simple docstring'''







		A_     :      Optional[Any]				   =    """pix2struct"""
		A_     :      str				   =    True







		def __init__( self		:						Any  ,					_A		:						int=None  ,					_A		:						int=None  ,					_A		:						List[str]=1.0  ,					_A		:						int=0.02  ,					_A		:						Optional[Any]=False  ,					_A		:						Tuple=False  ,					_A		:						Dict=True  ,					**_A		:						str  ,					)  ->			int:
			super().__init__(tie_word_embeddings=_A  ,					is_encoder_decoder=_A  ,					**_A      )

			if text_config is None:
				__magic_name__	:   List[str]					     =					{}
				logger.info('text_config is None. Initializing the Pix2StructTextConfig with default values.'      )

			if vision_config is None:
				__magic_name__	:   Optional[int]					     =					{}
				logger.info('vision_config is None. Initializing the Pix2StructVisionConfig with default values.'      )

			__magic_name__	:   str					     =					PixaStructTextConfig(**_A      )
			__magic_name__	:   List[str]					     =					PixaStructVisionConfig(**_A      )

			__magic_name__	:   int					     =					self.text_config.decoder_start_token_id
			__magic_name__	:   Union[str, Any]					     =					self.text_config.pad_token_id
			__magic_name__	:   List[str]					     =					self.text_config.eos_token_id

			__magic_name__	:   Tuple					     =					initializer_factor
			__magic_name__	:   Tuple					     =					initializer_range

			__magic_name__	:   List[str]					     =					self.initializer_range
			__magic_name__	:   Union[str, Any]					     =					self.initializer_range

			__magic_name__	:   Tuple					     =					is_vqa







		@classmethod
		def        __lowerCAmelCase		( cls		:						Tuple  ,					_A		:						PixaStructTextConfig  ,					_A		:						PixaStructVisionConfig  ,					**_A		:						Dict      )  ->			Union[str, Any]:
			return cls(text_config=text_config.to_dict()  ,					vision_config=vision_config.to_dict()  ,					**_A      )







		def        __lowerCAmelCase		( self		:						Any      )  ->			str:
			__magic_name__	:   Tuple					     =					copy.deepcopy(self.__dict__      )
			__magic_name__	:   Tuple					     =					self.text_config.to_dict()
			__magic_name__	:   Tuple					     =					self.vision_config.to_dict()
			__magic_name__	:   Any					     =					self.__class__.model_type
			return output



'''simple docstring'''

def lowerCamelCase      (      lowerCAmelCase    :     str		):





	"""simple docstring"""







	return "".join(chr(ord(lowerCAmelCase		) - 32		) if 'a' <= char <= 'z' else char for char in word		)


if __name__ == "__main__":
							from doctest import testmod

							testmod()