




from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


SCREAMING_SNAKE_CASE__       :      Tuple  =   {
    'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
    'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/config.json',
    'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/config.json',
    'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json',
    'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/config.json',
    'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/config.json',
    'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/config.json',
    'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json',
}




class 		UpperCamelCase__	(lowerCAmelCase__     ):

    '''simple docstring'''



    lowerCamelCase_      :	Union[str, Any]	     =      """albert"""







    def __init__(    self     ,  UpperCamelCase__=3_0000     ,  UpperCamelCase__=128     ,  UpperCamelCase__=4096     ,  UpperCamelCase__=12     ,  UpperCamelCase__=1     ,  UpperCamelCase__=64     ,  UpperCamelCase__=1_6384     ,  UpperCamelCase__=1     ,  UpperCamelCase__="gelu_new"     ,  UpperCamelCase__=0     ,  UpperCamelCase__=0     ,  UpperCamelCase__=512     ,  UpperCamelCase__=2     ,  UpperCamelCase__=0.02     ,  UpperCamelCase__=1e-12     ,  UpperCamelCase__=0.1     ,  UpperCamelCase__="absolute"     ,  UpperCamelCase__=0     ,  UpperCamelCase__=2     ,  UpperCamelCase__=3     ,  **UpperCamelCase__     ,  )     ->      Dict:
           super().__init__(pad_token_id=UpperCamelCase__     ,  bos_token_id=UpperCamelCase__     ,  eos_token_id=UpperCamelCase__     ,  **UpperCamelCase__     )

           lowerCamelCase   :      Dict			 =					vocab_size
           lowerCamelCase   :      Union[str, Any]			 =					embedding_size
           lowerCamelCase   :      Optional[Any]			 =					hidden_size
           lowerCamelCase   :      Tuple			 =					num_hidden_layers
           lowerCamelCase   :      str			 =					num_hidden_groups
           lowerCamelCase   :      str			 =					num_attention_heads
           lowerCamelCase   :      str			 =					inner_group_num
           lowerCamelCase   :      Any			 =					hidden_act
           lowerCamelCase   :      Tuple			 =					intermediate_size
           lowerCamelCase   :      Optional[Any]			 =					hidden_dropout_prob
           lowerCamelCase   :      Dict			 =					attention_probs_dropout_prob
           lowerCamelCase   :      Dict			 =					max_position_embeddings
           lowerCamelCase   :      Union[str, Any]			 =					type_vocab_size
           lowerCamelCase   :      int			 =					initializer_range
           lowerCamelCase   :      int			 =					layer_norm_eps
           lowerCamelCase   :      List[Any]			 =					classifier_dropout_prob
           lowerCamelCase   :      Dict			 =					position_embedding_type




class 		UpperCamelCase__	(lowerCAmelCase__     ):

    '''simple docstring'''



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












def      A      (      _SCREAMING_SNAKE_CASE    )	-> list:
       if n_term == "":
              return []
       lowerCamelCase   :      list			 =					[]
       for temp in range(int(_SCREAMING_SNAKE_CASE    )    ):
              series.append(f'''1/{temp + 1}''' if series else "1"    )
       return series


if __name__ == "__main__":
       SCREAMING_SNAKE_CASE__       :      Dict  =   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))






