'''simple docstring'''




from collections import OrderedDict
from typing import Mapping

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


__SCREAMING_SNAKE_CASE	:					Optional[int]					=  logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE	:					str					=  {
    '''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_     (snake_case_   ):
      '''simple docstring'''

      __UpperCamelCase:  Tuple      =						"""ernie"""




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

             _UpperCAmelCase					:  Tuple											=   vocab_size
             _UpperCAmelCase					:  Dict											=   hidden_size
             _UpperCAmelCase					:  List[str]											=   num_hidden_layers
             _UpperCAmelCase					:  List[str]											=   num_attention_heads
             _UpperCAmelCase					:  Optional[Any]											=   hidden_act
             _UpperCAmelCase					:  int											=   intermediate_size
             _UpperCAmelCase					:  List[str]											=   hidden_dropout_prob
             _UpperCAmelCase					:  Any											=   attention_probs_dropout_prob
             _UpperCAmelCase					:  Tuple											=   max_position_embeddings
             _UpperCAmelCase					:  Any											=   type_vocab_size
             _UpperCAmelCase					:  Optional[int]											=   task_type_vocab_size
             _UpperCAmelCase					:  str											=   use_task_id
             _UpperCAmelCase					:  Union[str, Any]											=   initializer_range
             _UpperCAmelCase					:  Dict											=   layer_norm_eps
             _UpperCAmelCase					:  Dict											=   position_embedding_type
             _UpperCAmelCase					:  List[str]											=   use_cache
             _UpperCAmelCase					:  int											=   classifier_dropout

class      lowerCamelCase_     (snake_case_   ):
      '''simple docstring'''

      @property
      def 					_A     (	self						:    Dict	):


             if self.task == "multiple-choice":
                    _UpperCAmelCase					:  List[Any]											=   {0: "batch", 1: "choice", 2: "sequence"}
             else:
                    _UpperCAmelCase					:  Tuple											=   {0: "batch", 1: "sequence"}
             return OrderedDict(
                 [
                     ("input_ids", dynamic_axis),
                     ("attention_mask", dynamic_axis),
                     ("token_type_ids", dynamic_axis),
                     ("task_type_ids", dynamic_axis),
                 ]	)


'''simple docstring'''




from __future__ import annotations

from collections.abc import Generator

def      UpperCamelCase_							( _UpperCAmelCase  :				int   )   ->   Generator[int, None, None]:


       """simple docstring"""







       if not isinstance(_UpperCAmelCase      ,     _UpperCAmelCase   ) or n < 1:
              raise Exception("Sequence only defined for positive integers"   )

       yield n
       while n != 1:
              if n % 2 == 0:
                     n //= 2
              else:
                     _UpperCAmelCase					:  Optional[Any]											=   3 * n + 1
              yield n

def      UpperCamelCase_							( )   ->   Any:


       """simple docstring"""







       _UpperCAmelCase					:  str											=   43
       _UpperCAmelCase					:  Optional[int]											=   tuple(collatz_sequence(_UpperCAmelCase   )   )
       print(_UpperCAmelCase   )
       print(F"""Collatz sequence from {n} took {len(_UpperCAmelCase   )} steps."""   )


if __name__ == "__main__":
  main()

