
"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

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


_A			:       Union[str, Any]   		=       logging.get_logger(__name__)

_A			:       Tuple   		=       {
    """junnyu/roformer_chinese_small""": """https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json""",
    """junnyu/roformer_chinese_base""": """https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json""",
    """junnyu/roformer_chinese_char_small""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json"""
    ),
    """junnyu/roformer_chinese_char_base""": (
        """https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_discriminator""": (
        """https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json"""
    ),
    """junnyu/roformer_small_generator""": (
        """https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json"""
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}

class 		a__						(      a_						):
   __lowerCAmelCase            =				"""roformer"""
   def __init__(			self	,    _a=50_000	,    _a=None	,    _a=768	,    _a=12	,    _a=12	,    _a=3_072	,    _a="gelu"	,    _a=0.1	,    _a=0.1	,    _a=1_536	,    _a=2	,    _a=0.0_2	,    _a=1E-12	,    _a=0	,    _a=False	,    _a=True	,    **_a	,    ):
          super().__init__(pad_token_id=_a	,    **_a				)

          lowercase    :				Tuple       		=							vocab_size
          lowercase    :				Dict       		=							hidden_size if embedding_size is None else embedding_size
          lowercase    :				str       		=							hidden_size
          lowercase    :				Any       		=							num_hidden_layers
          lowercase    :				int       		=							num_attention_heads
          lowercase    :				Union[str, Any]       		=							hidden_act
          lowercase    :				List[Any]       		=							intermediate_size
          lowercase    :				int       		=							hidden_dropout_prob
          lowercase    :				str       		=							attention_probs_dropout_prob
          lowercase    :				List[Any]       		=							max_position_embeddings
          lowercase    :				str       		=							type_vocab_size
          lowercase    :				Tuple       		=							initializer_range
          lowercase    :				Tuple       		=							layer_norm_eps
          lowercase    :				Any       		=							rotary_value
          lowercase    :				Any       		=							use_cache


class 		a__						(      a_						):
   @property
   def 			__magic_name__			(			self				):
          if self.task == "multiple-choice":
                 lowercase    :				str       		=							{0: "batch", 1: "choice", 2: "sequence"}
          else:
                 lowercase    :				str       		=							{0: "batch", 1: "sequence"}
          lowercase    :				int       		=							{0: "batch", 1: "sequence"}
          return OrderedDict(
              [
                  ("input_ids", dynamic_axis),
                  ("attention_mask", dynamic_axis),
                  ("token_type_ids", dynamic_axis),
              ]				)




"""simple docstring"""




def   __magic_name__	(      __snake_case				:       int     , __snake_case				:       int     , __snake_case				:       int  ) ->				float:
       lowercase    :				List[Any]       		=							(num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
       # formula for sum of series
       return total


def   __magic_name__	(      ) ->				int:
       print(sum_of_series(1     , 1     , 10  )  )


if __name__ == "__main__":
   import doctest

   doctest.testmod()


