


"""simple docstring"""
from torch import nn





class        __A       (nn.Module):





							'''simple docstring'''

							def __init__(			self							: Union[str, Any]						,    UpperCAmelCase_							: List[Any]						,    UpperCAmelCase_							: Tuple    )   ->Tuple:



														"""simple docstring"""



														super().__init__()
														snake_case_          =						class_size
														snake_case_          =						embed_size
														# self.mlp1 = nn.Linear(embed_size, embed_size)
														# self.mlp2 = (nn.Linear(embed_size, class_size))
														snake_case_          =						nn.Linear(UpperCAmelCase_						,    UpperCAmelCase_    )



							def 						lowerCAmelCase    (			self							: Dict						,    UpperCAmelCase_							: int    )   ->int:



														"""simple docstring"""



														snake_case_          =						self.mlp(UpperCAmelCase_    )
														return logits







"""simple docstring"""
from collections import defaultdict
from math import gcd







def   _a			( _SCREAMING_SNAKE_CASE = 1_500_000			)      ->			int:
							snake_case_          =						defaultdict(_SCREAMING_SNAKE_CASE			)
							snake_case_          =						2
							while 2 * euclid_m * (euclid_m + 1) <= limit:
														for euclid_n in range((euclid_m % 2) + 1			,	_SCREAMING_SNAKE_CASE			,	2			):
																					if gcd(_SCREAMING_SNAKE_CASE			,	_SCREAMING_SNAKE_CASE			) > 1:
																												continue
																					snake_case_          =						2 * euclid_m * (euclid_m + euclid_n)
																					for perimeter in range(_SCREAMING_SNAKE_CASE			,	limit + 1			,	_SCREAMING_SNAKE_CASE			):
																												frequencies[perimeter] += 1
														euclid_m += 1
							return sum(1 for frequency in frequencies.values() if frequency == 1			)


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



