



from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


__snake_case     :Tuple			       ={
    'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
    'susnato/ernie-m-large_pytorch': 'https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json',
}



class        lowerCAmelCase__					(  _lowerCamelCase       ):
				A_   :     Optional[int]								=     'ernie_m'
				A_   :     Dict[str, str]								=     {"dropout": "classifier_dropout", "num_classes": "num_labels"}


				def __init__(							self      :  Tuple						, __UpperCamelCase      :  int = 250_002						, __UpperCamelCase      :  int = 768						, __UpperCamelCase      :  int = 12						, __UpperCamelCase      :  int = 12						, __UpperCamelCase      :  int = 3_072						, __UpperCamelCase      :  str = "gelu"						, __UpperCamelCase      :  float = 0.1						, __UpperCamelCase      :  float = 0.1						, __UpperCamelCase      :  int = 514						, __UpperCamelCase      :  float = 0.0_2						, __UpperCamelCase      :  int = 1						, __UpperCamelCase      :  float = 1e-05						, __UpperCamelCase      :  Union[str, Any]=None						, __UpperCamelCase      :  Optional[int]=False						, __UpperCamelCase      :  int=0.0						, **__UpperCamelCase      :  Optional[int]						, )		->     Union[str, Any]:
											super().__init__(pad_token_id=__UpperCamelCase						, **__UpperCamelCase       )
											A      						=    vocab_size
											A      						=    hidden_size
											A      						=    num_hidden_layers
											A      						=    num_attention_heads
											A      						=    intermediate_size
											A      						=    hidden_act
											A      						=    hidden_dropout_prob
											A      						=    attention_probs_dropout_prob
											A      						=    max_position_embeddings
											A      						=    initializer_range
											A      						=    layer_norm_eps
											A      						=    classifier_dropout
											A      						=    is_decoder
											A      						=    act_dropout






def  __magic_name__  (				lowercase				)				-> list:

							"""simple docstring"""



							if n_term == "":
														return []
							lowercase_	:   list  				=     []
							for temp in range(int(lowercase				)				):
														series.append(f"""1/{temp + 1}""" if series else """1"""				)
							return series


if __name__ == "__main__":
							UpperCAmelCase_							=				input("""Enter the last number (nth term) of the Harmonic Series""")
							print("""Formula of Harmonic Series => 1+1/2+1/3 ..... 1/n""")
							print(harmonic_series(nth_term))