
'''simple docstring'''
import copy
import os
from typing import Union

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


lowercase__											=logging.get_logger(__name__)

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







class   a_ (      UpperCamelCase__					):
			lowerCamelCase__	:			Optional[int]       =    'pix2struct_text_model'
			lowerCamelCase__	:			List[str]       =    ['past_key_values']
			lowerCamelCase__	:			Dict       =    {
			    'hidden_size': 'hidden_size',
			    'num_attention_heads': 'num_heads',
			    'num_hidden_layers': 'num_layers',
			}




			def __init__(       self					,   UpperCAmelCase=5_02_44					,   UpperCAmelCase=7_68					,   UpperCAmelCase=64					,   UpperCAmelCase=20_48					,   UpperCAmelCase=12					,   UpperCAmelCase=12					,   UpperCAmelCase=32					,   UpperCAmelCase=1_28					,   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					,   ):
				a_      				=						vocab_size
				a_      				=						hidden_size
				a_      				=						d_kv
				a_      				=						d_ff
				a_      				=						num_layers
				a_      				=						num_heads
				a_      				=						relative_attention_num_buckets
				a_      				=						relative_attention_max_distance
				a_      				=						dropout_rate
				a_      				=						layer_norm_epsilon
				a_      				=						initializer_factor
				a_      				=						use_cache

				a_      				=						eos_token_id
				a_      				=						decoder_start_token_id

				# for backwards compatibility
				a_      				=						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 					lowerCAmelCase__					(       cls					,   UpperCAmelCase					,   **UpperCAmelCase	):
				cls._set_token_in_kwargs(UpperCAmelCase	)

				a_				,  a_      				=						cls.get_config_dict(UpperCAmelCase					,   **UpperCAmelCase	)

				# get the text config dict if we are loading from Pix2StructConfig
				if config_dict.get("""model_type"""	) == "pix2struct":
					a_      				=						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   a_ (      UpperCamelCase__					):
			lowerCamelCase__	:			Optional[Any]       =    'pix2struct_vision_model'




			def __init__(       self					,   UpperCAmelCase=7_68					,   UpperCAmelCase=7_68					,   UpperCAmelCase=20_48					,   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=40_96					,   UpperCAmelCase=32					,   UpperCAmelCase=1_28					,   **UpperCAmelCase					,   ):
				super().__init__(**UpperCAmelCase	)

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






			@classmethod
			def 					lowerCAmelCase__					(       cls					,   UpperCAmelCase					,   **UpperCAmelCase	):
				cls._set_token_in_kwargs(UpperCAmelCase	)

				a_				,  a_      				=						cls.get_config_dict(UpperCAmelCase					,   **UpperCAmelCase	)

				# get the vision config dict if we are loading from Pix2StructConfig
				if config_dict.get("""model_type"""	) == "pix2struct":
					a_      				=						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   a_ (      UpperCamelCase__					):
			lowerCamelCase__	:			int       =    'pix2struct'
			lowerCamelCase__	:			int       =    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:
					a_      				=						{}
					logger.info("""text_config is None. Initializing the Pix2StructTextConfig with default values."""	)

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

				a_      				=						PixaStructTextConfig(**UpperCAmelCase	)
				a_      				=						PixaStructVisionConfig(**UpperCAmelCase	)

				a_      				=						self.text_config.decoder_start_token_id
				a_      				=						self.text_config.pad_token_id
				a_      				=						self.text_config.eos_token_id

				a_      				=						initializer_factor
				a_      				=						initializer_range

				a_      				=						self.initializer_range
				a_      				=						self.initializer_range

				a_      				=						is_vqa




			@classmethod
			def 					lowerCAmelCase__					(       cls					,   UpperCAmelCase					,   UpperCAmelCase					,   **UpperCAmelCase	):
				return cls(text_config=text_config.to_dict()					,   vision_config=vision_config.to_dict()					,   **UpperCAmelCase	)






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


'''simple docstring'''
import math






def      UpperCamelCase_				(      A__						):
	return math.sqrt(A__						) * math.sqrt(A__						) == num






def      UpperCamelCase_				(      A__						):
	a_      				=						0
	a_      				=						n
	while left <= right:
		a_      				=						(left + right) // 2
		if mid**2 == n:
			return True
		elif mid**2 > n:
			a_      				=						mid - 1
		else:
			a_      				=						mid + 1
	return False


if __name__ == "__main__":
		import doctest

		doctest.testmod()
