



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



class    UpperCAmelCase__(				__lowercase						):

   '''simple docstring'''




   A     :	Union[str, Any]												=     "pix2struct_text_model"
   A     :	str												=     ["past_key_values"]
   A     :	str												=     {
       "hidden_size": "hidden_size",
       "num_attention_heads": "num_heads",
       "num_hidden_layers": "num_layers",
   }


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




         """simple docstring"""

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

         lowercase__  =	eos_token_id
         lowercase__  =	decoder_start_token_id

         # for backwards compatibility
         lowercase__  =	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       UpperCAmelCase		(    cls	:      Any      ,					lowerCAmelCase	:      Tuple      ,					**lowerCAmelCase	:      List[Any])						->					"PretrainedConfig":




         """simple docstring"""

         cls._set_token_in_kwargs(lowerCAmelCase)

         lowercase__,						lowercase__  =	cls.get_config_dict(lowerCAmelCase      ,					**lowerCAmelCase)

         # get the text config dict if we are loading from Pix2StructConfig
         if config_dict.get('model_type') == "pix2struct":
               lowercase__  =	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    UpperCAmelCase__(				__lowercase						):

   '''simple docstring'''




   A     :	int												=     "pix2struct_vision_model"


   def __init__(    self	:      Union[str, Any]      ,					lowerCAmelCase	:      Tuple=7_68      ,					lowerCAmelCase	:      List[str]=7_68      ,					lowerCAmelCase	:      Tuple=20_48      ,					lowerCAmelCase	:      str=64      ,					lowerCAmelCase	:      Optional[int]=12      ,					lowerCAmelCase	:      Dict=12      ,					lowerCAmelCase	:      List[Any]="gelu_new"      ,					lowerCAmelCase	:      Any=1E-6      ,					lowerCAmelCase	:      Union[str, Any]=0.0      ,					lowerCAmelCase	:      Optional[int]=0.0      ,					lowerCAmelCase	:      int=1E-1_0      ,					lowerCAmelCase	:      Optional[Any]=1.0      ,					lowerCAmelCase	:      int=40_96      ,					lowerCAmelCase	:      Union[str, Any]=32      ,					lowerCAmelCase	:      Union[str, Any]=1_28      ,					**lowerCAmelCase	:      Dict      ,					)						->					Tuple:




         """simple docstring"""

         super().__init__(**lowerCAmelCase)

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



   @classmethod
   def       UpperCAmelCase		(    cls	:      List[str]      ,					lowerCAmelCase	:      Dict      ,					**lowerCAmelCase	:      Dict)						->					"PretrainedConfig":




         """simple docstring"""

         cls._set_token_in_kwargs(lowerCAmelCase)

         lowercase__,						lowercase__  =	cls.get_config_dict(lowerCAmelCase      ,					**lowerCAmelCase)

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

   '''simple docstring'''




   A     :	Dict												=     "pix2struct"
   A     :	int												=     True


   def __init__(    self	:      Tuple      ,					lowerCAmelCase	:      Tuple=None      ,					lowerCAmelCase	:      Any=None      ,					lowerCAmelCase	:      List[Any]=1.0      ,					lowerCAmelCase	:      Tuple=0.02      ,					lowerCAmelCase	:      int=False      ,					lowerCAmelCase	:      List[Any]=False      ,					lowerCAmelCase	:      Optional[Any]=True      ,					**lowerCAmelCase	:      Dict      ,					)						->					Optional[Any]:




         """simple docstring"""

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

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

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

         lowercase__  =	PixaStructTextConfig(**lowerCAmelCase)
         lowercase__  =	PixaStructVisionConfig(**lowerCAmelCase)

         lowercase__  =	self.text_config.decoder_start_token_id
         lowercase__  =	self.text_config.pad_token_id
         lowercase__  =	self.text_config.eos_token_id

         lowercase__  =	initializer_factor
         lowercase__  =	initializer_range

         lowercase__  =	self.initializer_range
         lowercase__  =	self.initializer_range

         lowercase__  =	is_vqa


   @classmethod
   def       UpperCAmelCase		(    cls	:      List[str]      ,					lowerCAmelCase	:      List[str]      ,					lowerCAmelCase	:      Tuple      ,					**lowerCAmelCase	:      str)						->					str:




         """simple docstring"""

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



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




         """simple docstring"""

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


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase__						=				{
    "configuration_upernet": ["UperNetConfig"],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCamelCase__						=				[
		    "UperNetForSemanticSegmentation",
		    "UperNetPreTrainedModel",
		]


if TYPE_CHECKING:
		from .configuration_upernet import UperNetConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_upernet import UperNetForSemanticSegmentation, UperNetPreTrainedModel


else:
		import sys

		lowerCamelCase__						=				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



