




'''simple docstring'''


class      A       :







							def __init__(    self			:    int				,     lowerCAmelCase_			:    Union[str, Any]				,     lowerCAmelCase_			:    Dict				,     lowerCAmelCase_			:    List[str]   )     ->				Dict:


														"""simple docstring"""


														_a      	=							name
														_a      	=							value
														_a      	=							weight







							def __repr__(    self			:    Dict   )     ->				int:


														"""simple docstring"""


														return F'{self.__class__.__name__}({self.name}, {self.value}, {self.weight})'







							def   __lowerCAmelCase     (    self			:    Any   )     ->				Optional[Any]:


														"""simple docstring"""


														return self.value







							def   __lowerCAmelCase     (    self			:    Any   )     ->				List[Any]:


														"""simple docstring"""


														return self.name







							def   __lowerCAmelCase     (    self			:    Optional[Any]   )     ->				Union[str, Any]:


														"""simple docstring"""


														return self.weight







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


														"""simple docstring"""


														return self.value / self.weight



def 						snake_case_       (UpperCamelCase			:    Tuple					,		UpperCamelCase			:    Optional[int]					,		UpperCamelCase			:    Optional[int] ):





							'''simple docstring'''


							_a      	=							[]
							for i in range(len(UpperCamelCase ) ):
														menu.append(Things(name[i]					,		value[i]					,		weight[i] ) )
							return menu
def 						snake_case_       (UpperCamelCase			:    Union[str, Any]					,		UpperCamelCase			:    List[str]					,		UpperCamelCase			:    List[Any] ):





							'''simple docstring'''


							_a      	=							sorted(UpperCamelCase					,		key=UpperCamelCase					,		reverse=UpperCamelCase )
							_a      	=							[]
							_a	,				_a      	=							0.0, 0.0
							for i in range(len(UpperCamelCase ) ):
														if (total_cost + items_copy[i].get_weight()) <= max_cost:
																					result.append(items_copy[i] )
																					total_cost += items_copy[i].get_weight()
																					total_value += items_copy[i].get_value()
							return (result, total_value)
def 						snake_case_       ():





							'''simple docstring'''




if __name__ == "__main__":
				import doctest

				doctest.testmod()



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__   ( __lowercase						):
						UpperCamelCase_				:			Union[str, Any]						=		"pix2struct_text_model"
						UpperCamelCase_				:			str						=		["past_key_values"]
						UpperCamelCase_				:			str						=		{
						    "hidden_size": "hidden_size",
						    "num_attention_heads": "num_heads",
						    "num_hidden_layers": "num_layers",
						}

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


								'''simple docstring'''

								_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=a							,				eos_token_id=a							,				decoder_start_token_id=a							,				tie_word_embeddings=a							,				is_decoder=a							,				**a							,				)







						@classmethod
						def 			A_					(      cls							,				a							,				**a					)       ->   "PretrainedConfig":


								'''simple docstring'''

								cls._set_token_in_kwargs(a					)

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

								# 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(a							,				**a					)







class 							lowerCAmelCase__   ( __lowercase						):
						UpperCamelCase_				:			int						=		"pix2struct_vision_model"

						def __init__(      self							,				a=7_68							,				a=7_68							,				a=20_48							,				a=64							,				a=12							,				a=12							,				a="gelu_new"							,				a=1e-6							,				a=0.0							,				a=0.0							,				a=1e-10							,				a=1.0							,				a=40_96							,				a=32							,				a=1_28							,				**a							,				)       ->   Tuple:


								'''simple docstring'''

								super().__init__(**a					)

								_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 			A_					(      cls							,				a							,				**a					)       ->   "PretrainedConfig":


								'''simple docstring'''

								cls._set_token_in_kwargs(a					)

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

								# 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(a							,				**a					)







class 							lowerCAmelCase__   ( __lowercase						):
						UpperCamelCase_				:			Dict						=		"pix2struct"
						UpperCamelCase_				:			int						=		True

						def __init__(      self							,				a=None							,				a=None							,				a=1.0							,				a=0.02							,				a=False							,				a=False							,				a=True							,				**a							,				)       ->   Optional[Any]:


								'''simple docstring'''

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

								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(**a					)
								_UpperCamelCase         =						PixaStructVisionConfig(**a					)

								_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 			A_					(      cls							,				a							,				a							,				**a					)       ->   str:


								'''simple docstring'''

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







						def 			A_					(      self					)       ->   Union[str, Any]:


								'''simple docstring'''

								_UpperCamelCase         =						copy.deepcopy(self.__dict__					)
								_UpperCamelCase         =						self.text_config.to_dict()
								_UpperCamelCase         =						self.vision_config.to_dict()
								_UpperCamelCase         =						self.__class__.model_type
								return output



