



'''simple docstring'''



def 	_A							( _lowerCAmelCase       ):



							"""simple docstring"""



							__lowercase													=[[0 for _ in range(__lowerCAmelCase       )] for _ in range(m + 1       )]
							for i in range(m + 1       ):
														__lowercase													=1

							for n in range(m + 1       ):
														for k in range(1	, __lowerCAmelCase       ):
																					memo[n][k] += memo[n][k - 1]
																					if n - k > 0:
																												memo[n][k] += memo[n - k - 1][k]

							return memo[m][m - 1]


if __name__ == "__main__":
		import sys

		if len(sys.argv) == 1:
				try:
						lowerCamelCase									=							int(input("""Enter a number: """).strip())
						print(partition(n))
				except ValueError:
						print("""Please enter a number.""")
		else:
				try:
						lowerCamelCase									=							int(sys.argv[1])
						print(partition(n))
				except ValueError:
						print("""Please pass a number.""")





from collections import OrderedDict
from typing import Mapping

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


_A  =	logging.get_logger(__name__)

_A  =	{
    "kssteven/ibert-roberta-base": "https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json",
    "kssteven/ibert-roberta-large": "https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json",
    "kssteven/ibert-roberta-large-mnli": (
        "https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json"
    ),
}





class       _lowerCAmelCase   (      __a			):
				_lowercase     						='''ibert'''




				def __init__(   self							,							_UpperCamelCase=30_522							,							_UpperCamelCase=768							,							_UpperCamelCase=12							,							_UpperCamelCase=12							,							_UpperCamelCase=3_072							,							_UpperCamelCase="gelu"							,							_UpperCamelCase=0.1							,							_UpperCamelCase=0.1							,							_UpperCamelCase=512							,							_UpperCamelCase=2							,							_UpperCamelCase=0.02							,							_UpperCamelCase=1e-1_2							,							_UpperCamelCase=1							,							_UpperCamelCase=0							,							_UpperCamelCase=2							,							_UpperCamelCase="absolute"							,							_UpperCamelCase=False							,							_UpperCamelCase="none"							,							**_UpperCamelCase							,							)							-> List[str]:
							super().__init__(pad_token_id=_UpperCamelCase							,							bos_token_id=_UpperCamelCase							,							eos_token_id=_UpperCamelCase							,							**_UpperCamelCase	)

							lowerCAmelCase_         =      vocab_size
							lowerCAmelCase_         =      hidden_size
							lowerCAmelCase_         =      num_hidden_layers
							lowerCAmelCase_         =      num_attention_heads
							lowerCAmelCase_         =      hidden_act
							lowerCAmelCase_         =      intermediate_size
							lowerCAmelCase_         =      hidden_dropout_prob
							lowerCAmelCase_         =      attention_probs_dropout_prob
							lowerCAmelCase_         =      max_position_embeddings
							lowerCAmelCase_         =      type_vocab_size
							lowerCAmelCase_         =      initializer_range
							lowerCAmelCase_         =      layer_norm_eps
							lowerCAmelCase_         =      position_embedding_type
							lowerCAmelCase_         =      quant_mode
							lowerCAmelCase_         =      force_dequant





class       _lowerCAmelCase   (      __a			):




				@property
				def 	__a		(   self	)							-> Mapping[str, Mapping[int, str]]:
							if self.task == "multiple-choice":
										lowerCAmelCase_         =      {0: "batch", 1: "choice", 2: "sequence"}
							else:
										lowerCAmelCase_         =      {0: "batch", 1: "sequence"}
							return OrderedDict(
							    [
							        ("input_ids", dynamic_axis),
							        ("attention_mask", dynamic_axis),
							    ]	)



