



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


lowercase_								=     logging.get_logger(__name__)

lowercase_								=     {
    """EleutherAI/gpt-neox-20b""": """https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json""",
    # See all GPTNeoX models at https://huggingface.co/models?filter=gpt_neox
}
class 				_snake_case			(					lowercase__):
				UpperCamelCase__				:					Union[str, Any]     		="""gpt_neox"""




				def __init__(						self					:						Optional[int],					__lowercase					:						int=5_0432,					__lowercase					:						Tuple=6144,					__lowercase					:						Optional[int]=44,					__lowercase					:						Any=64,					__lowercase					:						Dict=2_4576,					__lowercase					:						Any="gelu",					__lowercase					:						List[Any]=0.25,					__lowercase					:						Tuple=1_0000,					__lowercase					:						Optional[int]=0.0,					__lowercase					:						List[str]=0.0,					__lowercase					:						List[str]=0.1,					__lowercase					:						Tuple=2048,					__lowercase					:						str=0.02,					__lowercase					:						Union[str, Any]=1e-5,					__lowercase					:						Optional[int]=True,					__lowercase					:						Any=0,					__lowercase					:						Union[str, Any]=2,					__lowercase					:						Dict=False,					__lowercase					:						Dict=True,					__lowercase					:						Optional[Any]=None,					**__lowercase					:						int,					):
							super().__init__(bos_token_id=__lowercase,					eos_token_id=__lowercase,					**__lowercase						)
							lowercase__					  =				vocab_size
							lowercase__					  =				max_position_embeddings
							lowercase__					  =				hidden_size
							lowercase__					  =				num_hidden_layers
							lowercase__					  =				num_attention_heads
							lowercase__					  =				intermediate_size
							lowercase__					  =				hidden_act
							lowercase__					  =				rotary_pct
							lowercase__					  =				rotary_emb_base
							lowercase__					  =				attention_dropout
							lowercase__					  =				hidden_dropout
							lowercase__					  =				classifier_dropout
							lowercase__					  =				initializer_range
							lowercase__					  =				layer_norm_eps
							lowercase__					  =				use_cache
							lowercase__					  =				tie_word_embeddings
							lowercase__					  =				use_parallel_residual
							lowercase__					  =				rope_scaling
							self._rope_scaling_validation()

							if self.hidden_size % self.num_attention_heads != 0:
										raise ValueError(
										    "The hidden size is not divisble by the number of attention heads! Make sure to update them!"						)




				def 							A__      (						self					:						str						):
							if self.rope_scaling is None:
										return

							if not isinstance(self.rope_scaling,					__lowercase						) or len(self.rope_scaling						) != 2:
										raise ValueError(
										    "`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, "
										    F'''got {self.rope_scaling}'''						)
							lowercase__					  =				self.rope_scaling.get("type",					__lowercase						)
							lowercase__					  =				self.rope_scaling.get("factor",					__lowercase						)
							if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
										raise ValueError(
										    F'''`rope_scaling`\'s name field must be one of [\'linear\', \'dynamic\'], got {rope_scaling_type}'''						)
							if rope_scaling_factor is None or not isinstance(__lowercase,					__lowercase						) or rope_scaling_factor <= 1.0:
										raise ValueError(F'''`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'''						)









def __lowerCAmelCase (     SCREAMING_SNAKE_CASE_  ):
			if upper_limit < 0:
						raise ValueError("Limit for the Catalan sequence must be ≥ 0"  )

			lowercase__					  =				[0] * (upper_limit + 1)

			# Base case: C(0) = C(1) = 1
			lowercase__					  =				1
			if upper_limit > 0:
						lowercase__					  =				1

			# Recurrence relation: C(i) = sum(C(j).C(i-j-1)), from j = 0 to i
			for i in range(2						,  upper_limit + 1  ):
						for j in range(SCREAMING_SNAKE_CASE_  ):
									catalan_list[i] += catalan_list[j] * catalan_list[i - j - 1]

			return catalan_list


if __name__ == "__main__":
							print("""\n********* Catalan Numbers Using Dynamic Programming ************\n""")
							print("""\n*** Enter -1 at any time to quit ***""")
							print("""\nEnter the upper limit (≥ 0) for the Catalan number sequence: """, end="""""")
							try:
														while True:
																					lowercase_								=     int(input().strip())
																					if N < 0:
																												print("""\n********* Goodbye!! ************""")
																												break
																					else:
																												print(F'The Catalan numbers from 0 through {N} are:')
																												print(catalan_numbers(N))
																												print("""Try another upper limit for the sequence: """, end="""""")
							except (NameError, ValueError):
														print("""\n********* Invalid input, goodbye! ************\n""")

							import doctest

							doctest.testmod()




