





import numpy as np
def     A__					(						SCREAMING_SNAKE_CASE_      :			List[Any]	)     ->     Optional[Any]:






   """simple docstring"""







   _UpperCAmelCase											=      np.exp(lowercase_	)

   # Add up the all the exponentials
   _UpperCAmelCase											=      np.sum(lowercase_	)

   # Divide every exponent by the sum of all exponents
   _UpperCAmelCase											=      exponent_vector / sum_of_exponents

   return softmax_vector


if __name__ == "__main__":
   print(softmax((0,)))






from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_											=  logging.get_logger(__name__)

UpperCAmelCase_											=  {
    "tau/splinter-base": "https://huggingface.co/tau/splinter-base/resolve/main/config.json",
    "tau/splinter-base-qass": "https://huggingface.co/tau/splinter-base-qass/resolve/main/config.json",
    "tau/splinter-large": "https://huggingface.co/tau/splinter-large/resolve/main/config.json",
    "tau/splinter-large-qass": "https://huggingface.co/tau/splinter-large-qass/resolve/main/config.json",
    # See all Splinter models at https://huggingface.co/models?filter=splinter
}




class  __UpperCamelCase						(       A__						):
     __A  :     Tuple            =      """splinter"""





     def __init__(    self							,       _UpperCamelCase=30522							,       _UpperCamelCase=768							,       _UpperCamelCase=12							,       _UpperCamelCase=12							,       _UpperCamelCase=3072							,       _UpperCamelCase="gelu"							,       _UpperCamelCase=0.1							,       _UpperCamelCase=0.1							,       _UpperCamelCase=512							,       _UpperCamelCase=2							,       _UpperCamelCase=0.02							,       _UpperCamelCase=1e-12							,       _UpperCamelCase=True							,       _UpperCamelCase=0							,       _UpperCamelCase=104							,       **_UpperCamelCase							,       ):
        super().__init__(pad_token_id=_UpperCamelCase							,       **_UpperCamelCase				)

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