




from collections import OrderedDict
from typing import Mapping

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


__SCREAMING_SNAKE_CASE     : int      =logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE     : Optional[Any]      ={
    """squeezebert/squeezebert-uncased""": (
        """https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/config.json"""
    ),
    """squeezebert/squeezebert-mnli""": """https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/config.json""",
    """squeezebert/squeezebert-mnli-headless""": (
        """https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/config.json"""
    ),
}






class       A      (		_a		):
     """simple docstring"""

     _snake_case:						Dict  =SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
     _snake_case:						int  ="squeezebert"




     def __init__(     self	: Optional[int]						,	A__	: Any=3_0_5_2_2						,	A__	: Tuple=7_6_8						,	A__	: Optional[int]=1_2						,	A__	: Dict=1_2						,	A__	: Optional[int]=3_0_7_2						,	A__	: int="gelu"						,	A__	: Dict=0.1						,	A__	: Any=0.1						,	A__	: int=5_1_2						,	A__	: int=2						,	A__	: Dict=0.02						,	A__	: Dict=1E-12						,	A__	: Optional[int]=0						,	A__	: int=7_6_8						,	A__	: Optional[int]=4						,	A__	: Optional[int]=4						,	A__	: str=4						,	A__	: List[Any]=1						,	A__	: List[str]=4						,	A__	: int=4						,	**A__	: Any						,	)					->							int:
           super().__init__(pad_token_id=A__						,	**A__      )

           lowerCamelCase__   	=					vocab_size
           lowerCamelCase__   	=					hidden_size
           lowerCamelCase__   	=					num_hidden_layers
           lowerCamelCase__   	=					num_attention_heads
           lowerCamelCase__   	=					hidden_act
           lowerCamelCase__   	=					intermediate_size
           lowerCamelCase__   	=					hidden_dropout_prob
           lowerCamelCase__   	=					attention_probs_dropout_prob
           lowerCamelCase__   	=					max_position_embeddings
           lowerCamelCase__   	=					type_vocab_size
           lowerCamelCase__   	=					initializer_range
           lowerCamelCase__   	=					layer_norm_eps
           lowerCamelCase__   	=					embedding_size
           lowerCamelCase__   	=					q_groups
           lowerCamelCase__   	=					k_groups
           lowerCamelCase__   	=					v_groups
           lowerCamelCase__   	=					post_attention_groups
           lowerCamelCase__   	=					intermediate_groups
           lowerCamelCase__   	=					output_groups






class       A      (		_a		):
     """simple docstring"""

     @property
     def 			__snake_case (     self	: str      )					->							Dict:





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






def        __SCREAMING_SNAKE_CASE	(				__lowercase:		int):



  '''simple docstring'''






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


if __name__ == "__main__":
      import doctest

      doctest.testmod()
