import torch
import torch.nn as nn

class Model(nn.Module):
    def __init__(self, eps=1e-12):
        super().__init__()
        self.eps = eps

    def forward(self, x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
        num = torch.abs(x - y)
        den = torch.abs(x) + torch.abs(y) + self.eps
        return torch.sqrt(torch.sum((num / den).pow(2), dim=1))

batch_size = 1024
feature_dim = 4096

def get_inputs():
    x = torch.randn(batch_size, feature_dim, dtype=torch.float32)
    y = torch.randn(batch_size, feature_dim, dtype=torch.float32)
    return [x, y]

def get_init_inputs():
    return [1e-12]