




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 a (     __SCREAMING_SNAKE_CASE  ):
						"""simple docstring"""

						UpperCamelCase_	:       Any       	=		'pix2struct_text_model'
						UpperCamelCase_	:       Tuple       	=		['past_key_values']
						UpperCamelCase_	:       str       	=		{
						    'hidden_size': 'hidden_size',
						    'num_attention_heads': 'num_heads',
						    'num_hidden_layers': 'num_layers',
						}






						def __init__( self :     List[str]				,							lowerCamelCase__ :     int=50_244				,							lowerCamelCase__ :     Union[str, Any]=768				,							lowerCamelCase__ :     List[str]=64				,							lowerCamelCase__ :     Dict=2_048				,							lowerCamelCase__ :     List[Any]=12				,							lowerCamelCase__ :     List[Any]=12				,							lowerCamelCase__ :     List[str]=32				,							lowerCamelCase__ :     List[str]=128				,							lowerCamelCase__ :     Any=0.1				,							lowerCamelCase__ :     int=1e-6				,							lowerCamelCase__ :     Union[str, Any]=1.0				,							lowerCamelCase__ :     str="gelu_new"				,							lowerCamelCase__ :     Optional[int]=0				,							lowerCamelCase__ :     int=False				,							lowerCamelCase__ :     str=0				,							lowerCamelCase__ :     Optional[Any]=1				,							lowerCamelCase__ :     str=False				,							lowerCamelCase__ :     str=True				,							**lowerCamelCase__ :     Dict				,							)    ->						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 :     str				,							lowerCamelCase__ :     Union[str, os.PathLike]				,							**lowerCamelCase__ :     Tuple				)    ->						"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 a (     __SCREAMING_SNAKE_CASE  ):
						"""simple docstring"""

						UpperCamelCase_	:       Optional[int]       	=		'pix2struct_vision_model'






						def __init__( self :     Tuple				,							lowerCamelCase__ :     str=768				,							lowerCamelCase__ :     List[Any]=768				,							lowerCamelCase__ :     List[Any]=2_048				,							lowerCamelCase__ :     Tuple=64				,							lowerCamelCase__ :     List[str]=12				,							lowerCamelCase__ :     Any=12				,							lowerCamelCase__ :     List[Any]="gelu_new"				,							lowerCamelCase__ :     List[str]=1e-6				,							lowerCamelCase__ :     Optional[Any]=0.0				,							lowerCamelCase__ :     Dict=0.0				,							lowerCamelCase__ :     str=1e-1_0				,							lowerCamelCase__ :     str=1.0				,							lowerCamelCase__ :     Union[str, Any]=4_096				,							lowerCamelCase__ :     Union[str, Any]=32				,							lowerCamelCase__ :     Dict=128				,							**lowerCamelCase__ :     Dict				,							)    ->						Dict:
													"""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__ :     Union[str, os.PathLike]				,							**lowerCamelCase__ :     List[str]				)    ->						"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 a (     __SCREAMING_SNAKE_CASE  ):
						"""simple docstring"""

						UpperCamelCase_	:       List[Any]       	=		'pix2struct'
						UpperCamelCase_	:       Dict       	=		True






						def __init__( self :     List[str]				,							lowerCamelCase__ :     int=None				,							lowerCamelCase__ :     Any=None				,							lowerCamelCase__ :     Optional[int]=1.0				,							lowerCamelCase__ :     str=0.0_2				,							lowerCamelCase__ :     Optional[int]=False				,							lowerCamelCase__ :     int=False				,							lowerCamelCase__ :     int=True				,							**lowerCamelCase__ :     Optional[Any]				,							)    ->						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 :     Optional[Any]				,							lowerCamelCase__ :     PixaStructTextConfig				,							lowerCamelCase__ :     PixaStructVisionConfig				,							**lowerCamelCase__ :     Union[str, Any]				)    ->						Optional[int]:
													"""simple docstring"""


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






						def     UpperCAmelCase_      ( self :     Dict				)    ->						List[str]:
													"""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 .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceClassificationProcessor
from .xnli import xnli_output_modes, xnli_processors, xnli_tasks_num_labels






