





import copy
import os
from typing import Union

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


UpperCAmelCase_           =	logging.get_logger(__name__)

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




class 			__UpperCamelCase    (							A__    ):
     __A	:  Tuple							  =   """pix2struct_text_model"""
     __A	:  Any							  =   ["""past_key_values"""]
     __A	:  str							  =   {
         """hidden_size""": """hidden_size""",
         """num_attention_heads""": """num_heads""",
         """num_hidden_layers""": """num_layers""",
     }





     def __init__(     self				,							_UpperCamelCase=50244				,							_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				,							):
        _UpperCAmelCase           =   vocab_size
        _UpperCAmelCase           =   hidden_size
        _UpperCAmelCase           =   d_kv
        _UpperCAmelCase           =   d_ff
        _UpperCAmelCase           =   num_layers
        _UpperCAmelCase           =   num_heads
        _UpperCAmelCase           =   relative_attention_num_buckets
        _UpperCAmelCase           =   relative_attention_max_distance
        _UpperCAmelCase           =   dropout_rate
        _UpperCAmelCase           =   layer_norm_epsilon
        _UpperCAmelCase           =   initializer_factor
        _UpperCAmelCase           =   use_cache

        _UpperCAmelCase           =   eos_token_id
        _UpperCAmelCase           =   decoder_start_token_id

        # for backwards compatibility
        _UpperCAmelCase           =   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					):
        cls._set_token_in_kwargs(_UpperCamelCase					)

        _UpperCAmelCase       ,      _UpperCAmelCase           =   cls.get_config_dict(_UpperCamelCase				,							**_UpperCamelCase					)

        # get the text config dict if we are loading from Pix2StructConfig
        if config_dict.get('''model_type'''					) == "pix2struct":
           _UpperCAmelCase           =   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 			__UpperCamelCase    (							A__    ):
     __A	:  List[Any]							  =   """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				,							):
        super().__init__(**_UpperCamelCase					)

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





     @classmethod
     def 		UpperCamelCase(     cls				,							_UpperCamelCase				,							**_UpperCamelCase					):
        cls._set_token_in_kwargs(_UpperCamelCase					)

        _UpperCAmelCase       ,      _UpperCAmelCase           =   cls.get_config_dict(_UpperCamelCase				,							**_UpperCamelCase					)

        # get the vision config dict if we are loading from Pix2StructConfig
        if config_dict.get('''model_type'''					) == "pix2struct":
           _UpperCAmelCase           =   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 			__UpperCamelCase    (							A__    ):
     __A	:  int							  =   """pix2struct"""
     __A	:  List[str]							  =   True





     def __init__(     self				,							_UpperCamelCase=None				,							_UpperCamelCase=None				,							_UpperCamelCase=1.0				,							_UpperCamelCase=0.02				,							_UpperCamelCase=False				,							_UpperCamelCase=False				,							_UpperCamelCase=True				,							**_UpperCamelCase				,							):
        super().__init__(tie_word_embeddings=_UpperCamelCase				,							is_encoder_decoder=_UpperCamelCase				,							**_UpperCamelCase					)

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

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

        _UpperCAmelCase           =   PixaStructTextConfig(**_UpperCamelCase					)
        _UpperCAmelCase           =   PixaStructVisionConfig(**_UpperCamelCase					)

        _UpperCAmelCase           =   self.text_config.decoder_start_token_id
        _UpperCAmelCase           =   self.text_config.pad_token_id
        _UpperCAmelCase           =   self.text_config.eos_token_id

        _UpperCAmelCase           =   initializer_factor
        _UpperCAmelCase           =   initializer_range

        _UpperCAmelCase           =   self.initializer_range
        _UpperCAmelCase           =   self.initializer_range

        _UpperCAmelCase           =   is_vqa





     @classmethod
     def 		UpperCamelCase(     cls				,							_UpperCamelCase				,							_UpperCamelCase				,							**_UpperCamelCase					):
        return cls(text_config=text_config.to_dict()				,							vision_config=vision_config.to_dict()				,							**_UpperCamelCase					)





     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   copy.deepcopy(self.__dict__					)
        _UpperCAmelCase           =   self.text_config.to_dict()
        _UpperCAmelCase           =   self.vision_config.to_dict()
        _UpperCAmelCase           =   self.__class__.model_type
        return output






import baseaa
def      A__       (    SCREAMING_SNAKE_CASE_   :      str						)  ->  bytes:






   """simple docstring"""







   return baseaa.baaencode(string.encode('''utf-8'''						)						)
def      A__       (    SCREAMING_SNAKE_CASE_   :      bytes						)  ->  str:






   """simple docstring"""







   return baseaa.baadecode(SCREAMING_SNAKE_CASE_						).decode('''utf-8'''						)


if __name__ == "__main__":
   UpperCAmelCase_           =	"Hello World!"
   UpperCAmelCase_           =	baseaa_encode(test)
   print(encoded)

   UpperCAmelCase_           =	baseaa_decode(encoded)
   print(decoded)