def METHOD_NAME(p: torch.Tensor) -> torch.Tensor:
    k = torch.tensor(wavenum)
    u = torch.complex(s_real(p), s_imag(p))
    x = p[..., 0:1]
    y = p[..., 1:2]
    r = torch.sqrt(x**2 + y**2)
    u_x_real, u_y_real = gradient(torch.real(u), p, create_graph=True, split=True)
    u_x_imag, u_y_imag = gradient(torch.imag(u), p, create_graph=True, split=True)
    u_xx_real, _ = gradient(u_x_real, p, create_graph=True, split=True)
    u_xx_imag, _ = gradient(u_x_imag, p, create_graph=True, split=True)
    _, u_yy_real = gradient(u_y_real, p, create_graph=True, split=True)
    _, u_yy_imag = gradient(u_y_imag, p, create_graph=True, split=True)
    u_xx = torch.complex(u_xx_real, u_xx_imag)
    u_yy = torch.complex(u_yy_real, u_yy_imag)
    return torch.imag(u_xx + u_yy + k**2*u + f(p))