



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase__       =	logging.get_logger(__name__)

UpperCAmelCase__       =	{
    "andreasmadsen/efficient_mlm_m0.40": (
        "https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json"
    ),
}







class       __lowerCAmelCase   (      A						):
			UpperCamelCase        =					'''roberta-prelayernorm'''



			def __init__(						self       :  Union[str, Any]			,		A       :  List[Any]=5_02_65			,		A       :  Optional[int]=7_68			,		A       :  List[str]=12			,		A       :  List[str]=12			,		A       :  Tuple=30_72			,		A       :  int="gelu"			,		A       :  Optional[int]=0.1			,		A       :  Optional[Any]=0.1			,		A       :  Dict=5_12			,		A       :  List[Any]=2			,		A       :  Any=0.0_2			,		A       :  Tuple=1E-12			,		A       :  Tuple=1			,		A       :  Union[str, Any]=0			,		A       :  List[str]=2			,		A       :  Optional[int]="absolute"			,		A       :  Tuple=True			,		A       :  List[Any]=None			,		**A       :  Any			,		)       ->   Union[str, Any]:



						"""simple docstring"""






						super().__init__(pad_token_id=A			,		bos_token_id=A			,		eos_token_id=A			,		**A)

						_UpperCAmelCase			=       vocab_size
						_UpperCAmelCase			=       hidden_size
						_UpperCAmelCase			=       num_hidden_layers
						_UpperCAmelCase			=       num_attention_heads
						_UpperCAmelCase			=       hidden_act
						_UpperCAmelCase			=       intermediate_size
						_UpperCAmelCase			=       hidden_dropout_prob
						_UpperCAmelCase			=       attention_probs_dropout_prob
						_UpperCAmelCase			=       max_position_embeddings
						_UpperCAmelCase			=       type_vocab_size
						_UpperCAmelCase			=       initializer_range
						_UpperCAmelCase			=       layer_norm_eps
						_UpperCAmelCase			=       position_embedding_type
						_UpperCAmelCase			=       use_cache
						_UpperCAmelCase			=       classifier_dropout







class       __lowerCAmelCase   (      A						):



			@property
			def    _lowerCamelCase	(						self       :  int)       ->   Mapping[str, Mapping[int, str]]:



						"""simple docstring"""






						if self.task == "multiple-choice":
									_UpperCAmelCase			=       {0: 'batch', 1: 'choice', 2: 'sequence'}
						else:
									_UpperCAmelCase			=       {0: 'batch', 1: 'sequence'}
						return OrderedDict(
						    [
						        ('input_ids', dynamic_axis),
						        ('attention_mask', dynamic_axis),
						    ])





def 							A     (					_UpperCAmelCase    :       int   )    ->			"list[int]":







			'''simple docstring'''
			if upper_limit < 0:
						raise ValueError('Limit for the Catalan sequence must be ≥ 0'   )

			_UpperCAmelCase			=       [0] * (upper_limit + 1)

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