




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_      						=   {
    "nghuyong/ernie-1.0-base-zh": "https://huggingface.co/nghuyong/ernie-1.0-base-zh/resolve/main/config.json",
    "nghuyong/ernie-2.0-base-en": "https://huggingface.co/nghuyong/ernie-2.0-base-en/resolve/main/config.json",
    "nghuyong/ernie-2.0-large-en": "https://huggingface.co/nghuyong/ernie-2.0-large-en/resolve/main/config.json",
    "nghuyong/ernie-3.0-base-zh": "https://huggingface.co/nghuyong/ernie-3.0-base-zh/resolve/main/config.json",
    "nghuyong/ernie-3.0-medium-zh": "https://huggingface.co/nghuyong/ernie-3.0-medium-zh/resolve/main/config.json",
    "nghuyong/ernie-3.0-mini-zh": "https://huggingface.co/nghuyong/ernie-3.0-mini-zh/resolve/main/config.json",
    "nghuyong/ernie-3.0-micro-zh": "https://huggingface.co/nghuyong/ernie-3.0-micro-zh/resolve/main/config.json",
    "nghuyong/ernie-3.0-nano-zh": "https://huggingface.co/nghuyong/ernie-3.0-nano-zh/resolve/main/config.json",
    "nghuyong/ernie-gram-zh": "https://huggingface.co/nghuyong/ernie-gram-zh/resolve/main/config.json",
    "nghuyong/ernie-health-zh": "https://huggingface.co/nghuyong/ernie-health-zh/resolve/main/config.json",
}

class        _lowerCamelCase  (	_SCREAMING_SNAKE_CASE      ):

      """simple docstring"""

      lowerCAmelCase__	:       int			=    "ernie"







      def __init__(   self    :       Union[str, Any]       ,				snake_case    :       int=30522       ,				snake_case    :       Union[str, Any]=768       ,				snake_case    :       Dict=12       ,				snake_case    :       Any=12       ,				snake_case    :       Union[str, Any]=3072       ,				snake_case    :       List[Any]="gelu"       ,				snake_case    :       Dict=0.1       ,				snake_case    :       List[str]=0.1       ,				snake_case    :       Any=512       ,				snake_case    :       Optional[Any]=2       ,				snake_case    :       List[str]=3       ,				snake_case    :       Tuple=False       ,				snake_case    :       str=0.02       ,				snake_case    :       List[Any]=1E-12       ,				snake_case    :       Dict=0       ,				snake_case    :       Optional[int]="absolute"       ,				snake_case    :       int=True       ,				snake_case    :       List[Any]=None       ,				**snake_case    :       Optional[Any]       ,				):
          super().__init__(pad_token_id=snake_case       ,				**snake_case )

          __UpperCamelCase     						=  vocab_size
          __UpperCamelCase     						=  hidden_size
          __UpperCamelCase     						=  num_hidden_layers
          __UpperCamelCase     						=  num_attention_heads
          __UpperCamelCase     						=  hidden_act
          __UpperCamelCase     						=  intermediate_size
          __UpperCamelCase     						=  hidden_dropout_prob
          __UpperCamelCase     						=  attention_probs_dropout_prob
          __UpperCamelCase     						=  max_position_embeddings
          __UpperCamelCase     						=  type_vocab_size
          __UpperCamelCase     						=  task_type_vocab_size
          __UpperCamelCase     						=  use_task_id
          __UpperCamelCase     						=  initializer_range
          __UpperCamelCase     						=  layer_norm_eps
          __UpperCamelCase     						=  position_embedding_type
          __UpperCamelCase     						=  use_cache
          __UpperCamelCase     						=  classifier_dropout







class        _lowerCamelCase  (	_SCREAMING_SNAKE_CASE      ):

      """simple docstring"""

      @property
      def 					snake_case		(   self    :       Tuple ):
          if self.task == "multiple-choice":
              __UpperCamelCase     						=  {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
          else:
              __UpperCamelCase     						=  {0: '''batch''', 1: '''sequence'''}
          return OrderedDict(
              [
                  ('''input_ids''', dynamic_axis),
                  ('''attention_mask''', dynamic_axis),
                  ('''token_type_ids''', dynamic_axis),
                  ('''task_type_ids''', dynamic_axis),
              ] )












def     __SCREAMING_SNAKE_CASE      (     lowercase_					)				->		bool:

    """simple docstring"""


    if not isinstance(lowercase_    ,   lowercase_					):
        __UpperCamelCase     						=  F"Input value of [number={number}] must be an integer"
        raise TypeError(lowercase_					)
    if number < 0 or number % 2 == 1:
        return False
    __UpperCamelCase     						=  int(number**0.5					)
    return number == number_sqrt * (number_sqrt + 1)


if __name__ == "__main__":
 import doctest

 doctest.testmod()






