




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__              =						{
    '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 				__SCREAMING_SNAKE_CASE							(		lowerCamelCase  ):
					_lowerCamelCase		  = """ernie"""

					def __init__(				self ,       __lowercase=30_522 ,       __lowercase=768 ,       __lowercase=12 ,       __lowercase=12 ,       __lowercase=3_072 ,       __lowercase="gelu" ,       __lowercase=0.1 ,       __lowercase=0.1 ,       __lowercase=512 ,       __lowercase=2 ,       __lowercase=3 ,       __lowercase=False ,       __lowercase=0.02 ,       __lowercase=1E-12 ,       __lowercase=0 ,       __lowercase="absolute" ,       __lowercase=True ,       __lowercase=None ,       **__lowercase ,       ):







						'''simple docstring'''




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

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


class 				__SCREAMING_SNAKE_CASE							(		lowerCamelCase  ):

					@property
					def 	lowercase_							(				self					):







						'''simple docstring'''




						if self.task == "multiple-choice":
							lowerCamelCase_							:		str							   =							{0: 'batch', 1: 'choice', 2: 'sequence'}
						else:
							lowerCamelCase_							:		List[str]							   =							{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"""
__UpperCamelCase			:		Tuple		    =   10**8

def 						_SCREAMING_SNAKE_CASE       (_UpperCAmelCase :  int       ):
 if n % 10 == 0:
  return False
 lowerCAmelCase  							=      str(_UpperCAmelCase       )
 return s == s[::-1]

def 						_SCREAMING_SNAKE_CASE       ():
 lowerCAmelCase  							=      set()
 lowerCAmelCase  							=      1
 lowerCAmelCase  							=      5
 while sum_squares < LIMIT:
  lowerCAmelCase  							=      first_square + 1
  while sum_squares < LIMIT:
   if is_palindrome(_UpperCAmelCase       ):
    answer.add(_UpperCAmelCase       )
   last_square += 1
   sum_squares += last_square**2
  first_square += 1
  lowerCAmelCase  							=      first_square**2 + (first_square + 1) ** 2

 return sum(_UpperCAmelCase       )


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





