
'''simple docstring'''







def 				SCREAMING_SNAKE_CASE__	(   __A = 1_000_000	)       ->	int:
	_snake_case   						=		limit + 1
	_snake_case   						=		[0] * limit
	for first_term in range(1			,				__A	):
		for n in range(__A			,				__A			,				__A	):
			_snake_case   						=		first_term + n / first_term
			if common_difference % 4:  # d must be divisble by 4
				continue
			else:
				common_difference /= 4
				if (
				    first_term > common_difference
				    and first_term < 4 * common_difference
				):  # since x,y,z are positive integers
					frequency[n] += 1  # so z>0 and a>d ,also 4d<a

	_snake_case   						=		sum(1 for x in frequency[1:limit] if x == 10	)

	return count


if __name__ == "__main__":
					print(F'''{solution() = }''')






'''simple docstring'''





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											=						{
    'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/config.json',
    'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/config.json',
    'xlm-roberta-large-finetuned-conll02-dutch': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/config.json'
    ),
    'xlm-roberta-large-finetuned-conll02-spanish': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/config.json'
    ),
    'xlm-roberta-large-finetuned-conll03-english': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/config.json'
    ),
    'xlm-roberta-large-finetuned-conll03-german': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/config.json'
    ),
}






class 					lowerCamelCase_    (				SCREAMING_SNAKE_CASE_     ):
  """simple docstring"""




  a_												="""xlm-roberta"""




  def __init__( self      :	Any			,	_a      :	Optional[Any]=3_0522			,	_a      :	Optional[Any]=768			,	_a      :	int=12			,	_a      :	Tuple=12			,	_a      :	str=3072			,	_a      :	List[Any]="gelu"			,	_a      :	int=0.1			,	_a      :	Optional[int]=0.1			,	_a      :	Optional[int]=512			,	_a      :	List[Any]=2			,	_a      :	Optional[Any]=0.02			,	_a      :	str=1e-12			,	_a      :	str=1			,	_a      :	str=0			,	_a      :	Optional[Any]=2			,	_a      :	Optional[int]="absolute"			,	_a      :	int=True			,	_a      :	Tuple=None			,	**_a      :	Any			,	)					->					Dict:
    super().__init__(pad_token_id=_a			,	bos_token_id=_a			,	eos_token_id=_a			,	**_a   )

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






class 					lowerCamelCase_    (				SCREAMING_SNAKE_CASE_     ):
  """simple docstring"""




  @property
  def 						_lowercase     ( self      :	Optional[Any]   )					->					Mapping[str, Mapping[int, str]]:
    if self.task == "multiple-choice":
      __lowerCamelCase       :       int           = {0: 'batch', 1: 'choice', 2: 'sequence'}
    else:
      __lowerCamelCase       :       Any           = {0: 'batch', 1: 'sequence'}
    return OrderedDict(
        [
            ('input_ids', dynamic_axis),
            ('attention_mask', dynamic_axis),
        ]   )






