






from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase__							  =						logging.get_logger(__name__)

UpperCAmelCase__							  =						{
    "andreasmadsen/efficient_mlm_m0.40": (
        "https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json"
    ),
}






class 						lowercase_   (      UpperCAmelCase__  ):






      '''simple docstring'''




      __snake_case	    =    '''roberta-prelayernorm'''







      def __init__( self :		Union[str, Any]					,   __UpperCAmelCase :		Optional[int]=50_265					,   __UpperCAmelCase :		Dict=768					,   __UpperCAmelCase :		Dict=12					,   __UpperCAmelCase :		Dict=12					,   __UpperCAmelCase :		List[Any]=3_072					,   __UpperCAmelCase :		List[Any]="gelu"					,   __UpperCAmelCase :		Optional[int]=0.1					,   __UpperCAmelCase :		Union[str, Any]=0.1					,   __UpperCAmelCase :		Optional[int]=512					,   __UpperCAmelCase :		List[Any]=2					,   __UpperCAmelCase :		Optional[int]=0.02					,   __UpperCAmelCase :		str=1e-1_2					,   __UpperCAmelCase :		List[Any]=1					,   __UpperCAmelCase :		Any=0					,   __UpperCAmelCase :		Optional[Any]=2					,   __UpperCAmelCase :		Optional[Any]="absolute"					,   __UpperCAmelCase :		Any=True					,   __UpperCAmelCase :		List[str]=None					,   **__UpperCAmelCase :		Optional[int]					,   )       ->Any:




       """simple docstring"""


       super().__init__(pad_token_id=__lowercase					,   bos_token_id=__lowercase					,   eos_token_id=__lowercase					,   **__lowercase    )

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






class 						lowercase_   (      UpperCAmelCase__  ):






      '''simple docstring'''




      @property
      def  __lowerCAmelCase   ( self :		str    )       ->List[Any]:




       """simple docstring"""


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








def 		lowerCamelCase__       (						):







	'''simple docstring'''





	for n in range(1	,      1000000				):
		yield n * (n + 1) // 2


def 		lowerCamelCase__       (						_A				):







	'''simple docstring'''





	snake_case_						       =	1
	snake_case_						       =	2
	while i * i <= n:
		snake_case_						       =	0
		while n % i == 0:
			n //= i
			multiplicity += 1
		divisors_count *= multiplicity + 1
		i += 1
	if n > 1:
		divisors_count *= 2
	return divisors_count


def 		lowerCamelCase__       (						):







	'''simple docstring'''





	return next(i for i in triangle_number_generator() if count_divisors(_A				) > 500				)


if __name__ == "__main__":
		print(solution())
