"""simple docstring"""





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


__A  =				logging.get_logger(__name__)

__A  =				{
    '''microsoft/trocr-base-handwritten''': (
        '''https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'''
    ),
    # See all TrOCR models at https://huggingface.co/models?filter=trocr
}






class  _snake_case     (					a__		):
						snake_case__			  =			"trocr"
						snake_case__			  =			["past_key_values"]
						snake_case__			  =			{
						    "num_attention_heads": "decoder_attention_heads",
						    "hidden_size": "d_model",
						    "num_hidden_layers": "decoder_layers",
						}






						def __init__(       self      :			Optional[Any]							,					UpperCAmelCase      :			List[str]=50265							,					UpperCAmelCase      :			Optional[int]=1024							,					UpperCAmelCase      :			List[str]=12							,					UpperCAmelCase      :			Any=16							,					UpperCAmelCase      :			Tuple=4096							,					UpperCAmelCase      :			Dict="gelu"							,					UpperCAmelCase      :			int=512							,					UpperCAmelCase      :			int=0.1							,					UpperCAmelCase      :			Union[str, Any]=0.0							,					UpperCAmelCase      :			List[Any]=0.0							,					UpperCAmelCase      :			Optional[Any]=2							,					UpperCAmelCase      :			int=0.0_2							,					UpperCAmelCase      :			str=0.0							,					UpperCAmelCase      :			Optional[Any]=True							,					UpperCAmelCase      :			int=False							,					UpperCAmelCase      :			List[Any]=True							,					UpperCAmelCase      :			Tuple=True							,					UpperCAmelCase      :			List[str]=1							,					UpperCAmelCase      :			Union[str, Any]=0							,					UpperCAmelCase      :			Tuple=2							,					**UpperCAmelCase      :			List[Any]							,					):
													__lowerCamelCase					:		Optional[Any]		   =     vocab_size
													__lowerCamelCase					:		List[str]		   =     d_model
													__lowerCamelCase					:		Union[str, Any]		   =     decoder_layers
													__lowerCamelCase					:		Optional[Any]		   =     decoder_attention_heads
													__lowerCamelCase					:		Optional[Any]		   =     decoder_ffn_dim
													__lowerCamelCase					:		Optional[int]		   =     activation_function
													__lowerCamelCase					:		Optional[int]		   =     max_position_embeddings
													__lowerCamelCase					:		Dict		   =     dropout
													__lowerCamelCase					:		str		   =     attention_dropout
													__lowerCamelCase					:		List[Any]		   =     activation_dropout
													__lowerCamelCase					:		Optional[Any]		   =     init_std
													__lowerCamelCase					:		Union[str, Any]		   =     decoder_layerdrop
													__lowerCamelCase					:		Dict		   =     use_cache
													__lowerCamelCase					:		List[Any]		   =     scale_embedding
													__lowerCamelCase					:		str		   =     use_learned_position_embeddings
													__lowerCamelCase					:		Union[str, Any]		   =     layernorm_embedding

													super().__init__(
													    pad_token_id=UpperCAmelCase							,					bos_token_id=UpperCAmelCase							,					eos_token_id=UpperCAmelCase							,					decoder_start_token_id=UpperCAmelCase							,					**UpperCAmelCase							,					)
"""simple docstring"""





import math


def    lowercase_   (   _lowerCamelCase:	int      ) ->      bool:



							'''simple docstring'''

							if 1 < number < 4:
														# 2 and 3 are primes
														return True
							elif number < 2 or number % 2 == 0 or number % 3 == 0:
														# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
														return False

							# All primes number are in format of 6k +/- 1
							for i in range(5						,   int(math.sqrt(_lowerCamelCase      ) + 1      )						,   6      ):
														if number % i == 0 or number % (i + 2) == 0:
																					return False
							return True


def    lowercase_   (   _lowerCamelCase:	int = 10001      ) ->      int:



							'''simple docstring'''

							try:
														__lowerCamelCase					:		Optional[int]		   =     int(_lowerCamelCase      )
							except (TypeError, ValueError):
														raise TypeError("Parameter nth must be int or castable to int."      ) from None
							if nth <= 0:
														raise ValueError("Parameter nth must be greater than or equal to one."      )
							__lowerCamelCase					:		list[int]		   =     []
							__lowerCamelCase					:		Tuple		   =     2
							while len(_lowerCamelCase      ) < nth:
														if is_prime(_lowerCamelCase      ):
																					primes.append(_lowerCamelCase      )
																					num += 1
														else:
																					num += 1
							return primes[len(_lowerCamelCase      ) - 1]


if __name__ == "__main__":
				print(F"""{solution() = }""")