





import copy
import os
from typing import Union

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


A   : Optional[Any]			=				logging.get_logger(__name__)

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


class   A      (_lowerCamelCase   ):
			'''simple docstring'''




			__lowerCamelCase     :	List[str]          =   '''pix2struct_text_model'''
			__lowerCamelCase     :	Union[str, Any]          =   ['''past_key_values''']
			__lowerCamelCase     :	Optional[Any]          =   {
			    '''hidden_size''': '''hidden_size''',
			    '''num_attention_heads''': '''num_heads''',
			    '''num_hidden_layers''': '''num_layers''',
			}






			def __init__(      self       :   List[Any]							,     __lowerCAmelCase       :   int=5_02_44							,     __lowerCAmelCase       :   Optional[int]=7_68							,     __lowerCAmelCase       :   str=64							,     __lowerCAmelCase       :   int=20_48							,     __lowerCAmelCase       :   Tuple=12							,     __lowerCAmelCase       :   Dict=12							,     __lowerCAmelCase       :   Optional[int]=32							,     __lowerCAmelCase       :   Optional[Any]=1_28							,     __lowerCAmelCase       :   List[str]=0.1							,     __lowerCAmelCase       :   str=1e-6							,     __lowerCAmelCase       :   Union[str, Any]=1.0							,     __lowerCAmelCase       :   Optional[Any]="gelu_new"							,     __lowerCAmelCase       :   int=0							,     __lowerCAmelCase       :   Union[str, Any]=False							,     __lowerCAmelCase       :   str=0							,     __lowerCAmelCase       :   Any=1							,     __lowerCAmelCase       :   Any=False							,     __lowerCAmelCase       :   Optional[int]=True							,     **__lowerCAmelCase       :   List[str]							,     )     ->     Tuple:







					"""simple docstring"""






					A__  				=       vocab_size
					A__  				=       hidden_size
					A__  				=       d_kv
					A__  				=       d_ff
					A__  				=       num_layers
					A__  				=       num_heads
					A__  				=       relative_attention_num_buckets
					A__  				=       relative_attention_max_distance
					A__  				=       dropout_rate
					A__  				=       layer_norm_epsilon
					A__  				=       initializer_factor
					A__  				=       use_cache

					A__  				=       eos_token_id
					A__  				=       decoder_start_token_id

					# for backwards compatibility
					A__  				=       dense_act_fn

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







			@classmethod
			def        a_	(      cls       :   Any							,     __lowerCAmelCase       :   Union[str, os.PathLike]							,     **__lowerCAmelCase       :   str       )     ->     List[str]:







					"""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 Pix2StructConfig
					if config_dict.get("""model_type"""       ) == "pix2struct":
							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   A      (_lowerCamelCase   ):
			'''simple docstring'''




			__lowerCamelCase     :	Optional[int]          =   '''pix2struct_vision_model'''






			def __init__(      self       :   Dict							,     __lowerCAmelCase       :   List[str]=7_68							,     __lowerCAmelCase       :   Dict=7_68							,     __lowerCAmelCase       :   Optional[Any]=20_48							,     __lowerCAmelCase       :   int=64							,     __lowerCAmelCase       :   Optional[Any]=12							,     __lowerCAmelCase       :   Any=12							,     __lowerCAmelCase       :   Union[str, Any]="gelu_new"							,     __lowerCAmelCase       :   str=1e-6							,     __lowerCAmelCase       :   List[str]=0.0							,     __lowerCAmelCase       :   str=0.0							,     __lowerCAmelCase       :   List[str]=1e-10							,     __lowerCAmelCase       :   Tuple=1.0							,     __lowerCAmelCase       :   Optional[int]=40_96							,     __lowerCAmelCase       :   Any=32							,     __lowerCAmelCase       :   Optional[int]=1_28							,     **__lowerCAmelCase       :   List[str]							,     )     ->     Any:







					"""simple docstring"""






					super().__init__(**__lowerCAmelCase       )

					A__  				=       hidden_size
					A__  				=       patch_embed_hidden_size
					A__  				=       d_ff
					A__  				=       dropout_rate
					A__  				=       num_hidden_layers
					A__  				=       num_attention_heads
					A__  				=       initializer_range
					A__  				=       initializer_factor
					A__  				=       attention_dropout
					A__  				=       layer_norm_eps
					A__  				=       dense_act_fn
					A__  				=       seq_len
					A__  				=       relative_attention_num_buckets
					A__  				=       relative_attention_max_distance
					A__  				=       d_kv







			@classmethod
			def        a_	(      cls       :   str							,     __lowerCAmelCase       :   Union[str, os.PathLike]							,     **__lowerCAmelCase       :   Tuple       )     ->     str:







					"""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 Pix2StructConfig
					if config_dict.get("""model_type"""       ) == "pix2struct":
							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   A      (_lowerCamelCase   ):
			'''simple docstring'''




			__lowerCamelCase     :	List[str]          =   '''pix2struct'''
			__lowerCamelCase     :	Union[str, Any]          =   True






			def __init__(      self       :   Optional[Any]							,     __lowerCAmelCase       :   Any=None							,     __lowerCAmelCase       :   Optional[int]=None							,     __lowerCAmelCase       :   Optional[Any]=1.0							,     __lowerCAmelCase       :   Any=0.0_2							,     __lowerCAmelCase       :   Dict=False							,     __lowerCAmelCase       :   Optional[Any]=False							,     __lowerCAmelCase       :   Dict=True							,     **__lowerCAmelCase       :   Optional[int]							,     )     ->     List[Any]:







					"""simple docstring"""






					super().__init__(tie_word_embeddings=__lowerCAmelCase							,     is_encoder_decoder=__lowerCAmelCase							,     **__lowerCAmelCase       )

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

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

					A__  				=       PixaStructTextConfig(**__lowerCAmelCase       )
					A__  				=       PixaStructVisionConfig(**__lowerCAmelCase       )

					A__  				=       self.text_config.decoder_start_token_id
					A__  				=       self.text_config.pad_token_id
					A__  				=       self.text_config.eos_token_id

					A__  				=       initializer_factor
					A__  				=       initializer_range

					A__  				=       self.initializer_range
					A__  				=       self.initializer_range

					A__  				=       is_vqa






			@classmethod
			def        a_	(      cls       :   List[str]							,     __lowerCAmelCase       :   PixaStructTextConfig							,     __lowerCAmelCase       :   PixaStructVisionConfig							,     **__lowerCAmelCase       :   Optional[int]       )     ->     List[str]:







					"""simple docstring"""






					return cls(text_config=text_config.to_dict()							,     vision_config=vision_config.to_dict()							,     **__lowerCAmelCase       )







			def        a_	(      self       :   int       )     ->     Optional[Any]:







					"""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













from string import ascii_uppercase

A   : List[str]			=				{str(ord(c) - 5_5): c for c in ascii_uppercase}







def        __lowerCamelCase (							__a       :int   ,					__a       :int   )		->    str:






		"""simple docstring"""

		if isinstance(__a   ,					__a   ):
				raise TypeError("""int() can't convert non-string with explicit base"""   )
		if num < 0:
				raise ValueError("""parameter must be positive int"""   )
		if isinstance(__a   ,					__a   ):
				raise TypeError("""'str' object cannot be interpreted as an integer"""   )
		if isinstance(__a   ,					__a   ):
				raise TypeError("""'float' object cannot be interpreted as an integer"""   )
		if base in (0, 1):
				raise ValueError("""base must be >= 2"""   )
		if base > 3_6:
				raise ValueError("""base must be <= 36"""   )
		A__  				=       """"""
		A__  				=       0
		A__  				=       0
		while div != 1:
				A__				,      A__  				=       divmod(__a   ,					__a   )
				if base >= 1_1 and 9 < mod < 3_6:
						A__  				=       ALPHABET_VALUES[str(__a   )]
				else:
						A__  				=       str(__a   )
				new_value += actual_value
				A__  				=       num // base
				A__  				=       div
				if div == 0:
						return str(new_value[::-1]   )
				elif div == 1:
						new_value += str(__a   )
						return str(new_value[::-1]   )

		return new_value[::-1]


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					for base in range(2, 3_7):
										for num in range(1_0_0_0):
															assert int(decimal_to_any(num, base), base) == num, (
															    num,
															    base,
															    decimal_to_any(num, base),
															    int(decimal_to_any(num, base), base),
															)



