



import copy
import os
from typing import Union

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


A__	      =       logging.get_logger(__name__)

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





class 					__lowerCAmelCase (     lowerCamelCase__       ):
				__lowerCamelCase =				'''pix2struct_text_model'''
				__lowerCamelCase =				['''past_key_values''']
				__lowerCamelCase =				{
				    '''hidden_size''': '''hidden_size''',
				    '''num_attention_heads''': '''num_heads''',
				    '''num_hidden_layers''': '''num_layers''',
				}




				def __init__(							self						,				_snake_case=50244						,				_snake_case=768						,				_snake_case=64						,				_snake_case=2048						,				_snake_case=12						,				_snake_case=12						,				_snake_case=32						,				_snake_case=128						,				_snake_case=0.1						,				_snake_case=1e-6						,				_snake_case=1.0						,				_snake_case="gelu_new"						,				_snake_case=0						,				_snake_case=False						,				_snake_case=0						,				_snake_case=1						,				_snake_case=False						,				_snake_case=True						,				**_snake_case						,				):



									"""simple docstring"""





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

									_lowerCAmelCase						=    eos_token_id
									_lowerCAmelCase						=    decoder_start_token_id

									# for backwards compatibility
									_lowerCAmelCase						=    dense_act_fn

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




				@classmethod
				def 							snake_case   (							cls						,				_snake_case						,				**_snake_case		):



									"""simple docstring"""





									cls._set_token_in_kwargs(_snake_case		)

									_lowerCAmelCase	,	_lowerCAmelCase						=    cls.get_config_dict(_snake_case						,				**_snake_case		)

									# get the text config dict if we are loading from Pix2StructConfig
									if config_dict.get("""model_type"""		) == "pix2struct":
														_lowerCAmelCase						=    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(_snake_case						,				**_snake_case		)





class 					__lowerCAmelCase (     lowerCamelCase__       ):
				__lowerCamelCase =				'''pix2struct_vision_model'''




				def __init__(							self						,				_snake_case=768						,				_snake_case=768						,				_snake_case=2048						,				_snake_case=64						,				_snake_case=12						,				_snake_case=12						,				_snake_case="gelu_new"						,				_snake_case=1e-6						,				_snake_case=0.0						,				_snake_case=0.0						,				_snake_case=1e-10						,				_snake_case=1.0						,				_snake_case=4096						,				_snake_case=32						,				_snake_case=128						,				**_snake_case						,				):



									"""simple docstring"""





									super().__init__(**_snake_case		)

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




				@classmethod
				def 							snake_case   (							cls						,				_snake_case						,				**_snake_case		):



									"""simple docstring"""





									cls._set_token_in_kwargs(_snake_case		)

									_lowerCAmelCase	,	_lowerCAmelCase						=    cls.get_config_dict(_snake_case						,				**_snake_case		)

									# get the vision config dict if we are loading from Pix2StructConfig
									if config_dict.get("""model_type"""		) == "pix2struct":
														_lowerCAmelCase						=    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(_snake_case						,				**_snake_case		)





class 					__lowerCAmelCase (     lowerCamelCase__       ):
				__lowerCamelCase =				'''pix2struct'''
				__lowerCamelCase =				True




				def __init__(							self						,				_snake_case=None						,				_snake_case=None						,				_snake_case=1.0						,				_snake_case=0.02						,				_snake_case=False						,				_snake_case=False						,				_snake_case=True						,				**_snake_case						,				):



									"""simple docstring"""





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

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

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

									_lowerCAmelCase						=    PixaStructTextConfig(**_snake_case		)
									_lowerCAmelCase						=    PixaStructVisionConfig(**_snake_case		)

									_lowerCAmelCase						=    self.text_config.decoder_start_token_id
									_lowerCAmelCase						=    self.text_config.pad_token_id
									_lowerCAmelCase						=    self.text_config.eos_token_id

									_lowerCAmelCase						=    initializer_factor
									_lowerCAmelCase						=    initializer_range

									_lowerCAmelCase						=    self.initializer_range
									_lowerCAmelCase						=    self.initializer_range

									_lowerCAmelCase						=    is_vqa




				@classmethod
				def 							snake_case   (							cls						,				_snake_case						,				_snake_case						,				**_snake_case		):



									"""simple docstring"""





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




				def 							snake_case   (							self		):



									"""simple docstring"""





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










class    _SCREAMING_SNAKE_CASE						:







 '''simple docstring'''

 def __init__(self				:   Optional[Any]       , UpperCAmelCase_				:   int)       ->Optional[int]:



   '''simple docstring'''



   lowerCamelCase__:      Any			  =n
   lowerCamelCase__:      Tuple			  =[None] * self.n
   lowerCamelCase__:      str			  =0  # index of the first element
   lowerCamelCase__:      Tuple			  =0
   lowerCamelCase__:      Optional[Any]			  =0

 def __len__(self				:   str)       ->int:



   '''simple docstring'''



   return self.size

 def 							SCREAMING_SNAKE_CASE_					(self				:   int)       ->bool:



   '''simple docstring'''



   return self.size == 0

 def 							SCREAMING_SNAKE_CASE_					(self				:   List[str])       ->str:



   '''simple docstring'''



   return False if self.is_empty() else self.array[self.front]

 def 							SCREAMING_SNAKE_CASE_					(self				:   int       , UpperCAmelCase_				:   Optional[int])       ->str:



   '''simple docstring'''



   if self.size >= self.n:
     raise Exception("QUEUE IS FULL")

   lowerCamelCase__:      List[Any]			  =data
   lowerCamelCase__:      Dict			  =(self.rear + 1) % self.n
   self.size += 1
   return self







 def 							SCREAMING_SNAKE_CASE_					(self				:   Tuple)       ->Tuple:



   '''simple docstring'''



   if self.size == 0:
     raise Exception("UNDERFLOW")

   lowerCamelCase__:      Optional[Any]			  =self.array[self.front]
   lowerCamelCase__:      Optional[int]			  =None
   lowerCamelCase__:      Dict			  =(self.front + 1) % self.n
   self.size -= 1
   return temp

