



'''simple docstring'''





import copy
import os
from typing import Union

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


_lowerCAmelCase										=     logging.get_logger(__name__)

_lowerCAmelCase										=     {
    '''google/pix2struct-textcaps-base''': (
        '''https://huggingface.co/google/pix2struct-textcaps-base/resolve/main/config.json'''
    ),
}






class 	lowerCAmelCase_(    SCREAMING_SNAKE_CASE_					):
		'''simple docstring'''




		__lowercase							:				Union[str, Any]           =				'''pix2struct_text_model'''
		__lowercase							:				Any           =				['''past_key_values''']
		__lowercase							:				int           =				{
		    '''hidden_size''': '''hidden_size''',
		    '''num_attention_heads''': '''num_heads''',
		    '''num_hidden_layers''': '''num_layers''',
		}




		def __init__(   self  ,__UpperCAmelCase=5_0244  ,__UpperCAmelCase=768  ,__UpperCAmelCase=64  ,__UpperCAmelCase=2048  ,__UpperCAmelCase=12  ,__UpperCAmelCase=12  ,__UpperCAmelCase=32  ,__UpperCAmelCase=128  ,__UpperCAmelCase=0.1  ,__UpperCAmelCase=1E-6  ,__UpperCAmelCase=1.0  ,__UpperCAmelCase="gelu_new"  ,__UpperCAmelCase=0  ,__UpperCAmelCase=False  ,__UpperCAmelCase=0  ,__UpperCAmelCase=1  ,__UpperCAmelCase=False  ,__UpperCAmelCase=True  ,**__UpperCAmelCase  ,)   ->		Tuple:
						lowerCAmelCase__			:  Dict											= vocab_size
						lowerCAmelCase__			:  Any											= hidden_size
						lowerCAmelCase__			:  Union[str, Any]											= d_kv
						lowerCAmelCase__			:  Optional[int]											= d_ff
						lowerCAmelCase__			:  List[Any]											= num_layers
						lowerCAmelCase__			:  Any											= num_heads
						lowerCAmelCase__			:  Union[str, Any]											= relative_attention_num_buckets
						lowerCAmelCase__			:  Optional[Any]											= relative_attention_max_distance
						lowerCAmelCase__			:  Any											= dropout_rate
						lowerCAmelCase__			:  str											= layer_norm_epsilon
						lowerCAmelCase__			:  Optional[Any]											= initializer_factor
						lowerCAmelCase__			:  Dict											= use_cache

						lowerCAmelCase__			:  Optional[Any]											= eos_token_id
						lowerCAmelCase__			:  Dict											= decoder_start_token_id

						# for backwards compatibility
						lowerCAmelCase__			:  Any											= dense_act_fn

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






		@classmethod
		def 							UpperCAmelCase_     (   cls  ,__UpperCAmelCase  ,**__UpperCAmelCase				)   ->		"PretrainedConfig":
						cls._set_token_in_kwargs(__UpperCAmelCase				)

						lowerCAmelCase__			:  int											= cls.get_config_dict(__UpperCAmelCase  ,**__UpperCAmelCase				)

						# get the text config dict if we are loading from Pix2StructConfig
						if config_dict.get("""model_type"""				) == "pix2struct":
										lowerCAmelCase__			:  Optional[int]											= 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(__UpperCAmelCase  ,**__UpperCAmelCase				)







class 	lowerCAmelCase_(    SCREAMING_SNAKE_CASE_					):
		'''simple docstring'''




		__lowercase							:				Tuple           =				'''pix2struct_vision_model'''




		def __init__(   self  ,__UpperCAmelCase=768  ,__UpperCAmelCase=768  ,__UpperCAmelCase=2048  ,__UpperCAmelCase=64  ,__UpperCAmelCase=12  ,__UpperCAmelCase=12  ,__UpperCAmelCase="gelu_new"  ,__UpperCAmelCase=1E-6  ,__UpperCAmelCase=0.0  ,__UpperCAmelCase=0.0  ,__UpperCAmelCase=1E-10  ,__UpperCAmelCase=1.0  ,__UpperCAmelCase=4096  ,__UpperCAmelCase=32  ,__UpperCAmelCase=128  ,**__UpperCAmelCase  ,)   ->		int:
						super().__init__(**__UpperCAmelCase				)

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






		@classmethod
		def 							UpperCAmelCase_     (   cls  ,__UpperCAmelCase  ,**__UpperCAmelCase				)   ->		"PretrainedConfig":
						cls._set_token_in_kwargs(__UpperCAmelCase				)

						lowerCAmelCase__			:  Tuple											= cls.get_config_dict(__UpperCAmelCase  ,**__UpperCAmelCase				)

						# get the vision config dict if we are loading from Pix2StructConfig
						if config_dict.get("""model_type"""				) == "pix2struct":
										lowerCAmelCase__			:  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(__UpperCAmelCase  ,**__UpperCAmelCase				)







class 	lowerCAmelCase_(    SCREAMING_SNAKE_CASE_					):
		'''simple docstring'''




		__lowercase							:				int           =				'''pix2struct'''
		__lowercase							:				Union[str, Any]           =				True




		def __init__(   self  ,__UpperCAmelCase=None  ,__UpperCAmelCase=None  ,__UpperCAmelCase=1.0  ,__UpperCAmelCase=0.0_2  ,__UpperCAmelCase=False  ,__UpperCAmelCase=False  ,__UpperCAmelCase=True  ,**__UpperCAmelCase  ,)   ->		List[Any]:
						super().__init__(tie_word_embeddings=__UpperCAmelCase  ,is_encoder_decoder=__UpperCAmelCase  ,**__UpperCAmelCase				)

						if text_config is None:
										lowerCAmelCase__			:  Any											= {}
										logger.info("""text_config is None. Initializing the Pix2StructTextConfig with default values."""				)

						if vision_config is None:
										lowerCAmelCase__			:  str											= {}
										logger.info("""vision_config is None. Initializing the Pix2StructVisionConfig with default values."""				)

						lowerCAmelCase__			:  Dict											= PixaStructTextConfig(**__UpperCAmelCase				)
						lowerCAmelCase__			:  str											= PixaStructVisionConfig(**__UpperCAmelCase				)

						lowerCAmelCase__			:  Optional[int]											= self.text_config.decoder_start_token_id
						lowerCAmelCase__			:  str											= self.text_config.pad_token_id
						lowerCAmelCase__			:  Union[str, Any]											= self.text_config.eos_token_id

						lowerCAmelCase__			:  Optional[Any]											= initializer_factor
						lowerCAmelCase__			:  Optional[Any]											= initializer_range

						lowerCAmelCase__			:  List[str]											= self.initializer_range
						lowerCAmelCase__			:  str											= self.initializer_range

						lowerCAmelCase__			:  Optional[Any]											= is_vqa




		@classmethod
		def 							UpperCAmelCase_     (   cls  ,__UpperCAmelCase  ,__UpperCAmelCase  ,**__UpperCAmelCase				)   ->		Dict:
						return cls(text_config=text_config.to_dict()  ,vision_config=vision_config.to_dict()  ,**__UpperCAmelCase				)






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







'''simple docstring'''





_lowerCAmelCase										=     '''Input must be a string of 8 numbers plus letter'''
_lowerCAmelCase										=     '''TRWAGMYFPDXBNJZSQVHLCKE'''
def        _SCREAMING_SNAKE_CASE  (	UpperCamelCase      ):



    """simple docstring"""





    if not isinstance(UpperCamelCase							,   UpperCamelCase      ):
        lowerCAmelCase__			:  List[Any]											= f"""Expected string as input, found {type(UpperCamelCase      ).__name__}"""
        raise TypeError(UpperCamelCase      )

    lowerCAmelCase__			:  Union[str, Any]											= spanish_id.replace("""-"""							,   """"""      ).upper()
    if len(UpperCamelCase      ) != 9:
        raise ValueError(UpperCamelCase      )

    try:
        lowerCAmelCase__			:  Optional[int]											= int(spanish_id_clean[0:8]      )
        lowerCAmelCase__			:  int											= spanish_id_clean[8]
    except ValueError as ex:
        raise ValueError(UpperCamelCase      ) from ex

    if letter.isdigit():
        raise ValueError(UpperCamelCase      )

    return letter == LOOKUP_LETTERS[number % 23]


if __name__ == "__main__":
 import doctest

 doctest.testmod()


