

def    __UpperCAmelCase (	__a      :			int	)			->     "list[int]":

					"""simple docstring"""

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

					_a	:    Optional[Any]         =		[0] * (upper_limit + 1)

					# Base case: C(0) = C(1) = 1
					_a	:    List[str]         =		1
					if upper_limit > 0:
										_a	:    Dict         =		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(__a	):
															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:
									a__				=		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()






from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


a__				=		logging.get_logger(__name__)

a__				=		{
    '''google/bit-50''': '''https://huggingface.co/google/bit-50/resolve/main/config.json''',
}

class 				UpperCAmelCase_		(			__lowercase				,       __lowercase   ):
							"""simple docstring"""







							UpperCAmelCase__       :						Any	    =    "bit"
							UpperCAmelCase__       :						Optional[int]	    =    ["preactivation", "bottleneck"]
							UpperCAmelCase__       :						Optional[Any]	    =    ["SAME", "VALID"]


							def __init__(			self       ,							_a=3       ,							_a=6_4       ,							_a=[2_5_6, 5_1_2, 1_0_2_4, 2_0_4_8]       ,							_a=[3, 4, 6, 3]       ,							_a="preactivation"       ,							_a="relu"       ,							_a=None       ,							_a=3_2       ,							_a=0.0       ,							_a=False       ,							_a=3_2       ,							_a=1       ,							_a=None       ,							_a=None       ,							**_a       ,							)    ->    Union[str, Any]:
												super().__init__(**_a       )
												if layer_type not in self.layer_types:
																	raise ValueError(F"""layer_type={layer_type} is not one of {','.join(self.layer_types       )}"""       )
												if global_padding is not None:
																	if global_padding.upper() in self.supported_padding:
																						_a	:    Any         =		global_padding.upper()
																	else:
																						raise ValueError(F"""Padding strategy {global_padding} not supported"""       )
												_a	:    Optional[int]         =		num_channels
												_a	:    List[Any]         =		embedding_size
												_a	:    Any         =		hidden_sizes
												_a	:    int         =		depths
												_a	:    Dict         =		layer_type
												_a	:    int         =		hidden_act
												_a	:    Optional[Any]         =		global_padding
												_a	:    Optional[Any]         =		num_groups
												_a	:    Union[str, Any]         =		drop_path_rate
												_a	:    Tuple         =		embedding_dynamic_padding
												_a	:    Union[str, Any]         =		output_stride
												_a	:    Any         =		width_factor

												_a	:    Any         =		['''stem'''] + [F"""stage{idx}""" for idx in range(1       ,							len(_a       ) + 1       )]
												_a      ,					_a	:    List[str]         =		get_aligned_output_features_output_indices(
												    out_features=_a       ,							out_indices=_a       ,							stage_names=self.stage_names       )



