code: def additive_step(self, t0, t1, y0, extra0):
      del extra0
      dt = t1 - t0
      rdt = 1 / dt
      I_k, I_k0 = self.bm(t0, t1, return_U=True)
  
      y1 = y0
      H0 = []
      for i in range(sra1.STAGES):
          H0i = y0
          for j in range(i):
              f = self.sde.f(t0 + sra1.C0[j] * dt, H0[j])
              g_weight = sra1.B0[i][j] * I_k0 * rdt
              g_prod = self.sde.g_prod(
                  t0 + sra1.C1[j] * dt, y0, g_weight
              )
              H0i = H0i + sra1.A0[i][j] * f * dt + g_prod
          H0.append(H0i)
  
          f = self.sde.f(t0 + sra1.C0[i] * dt, H0i)
          g_weight = sra1.beta1[i] * I_k + sra1.beta2[i] * I_k0 * rdt
          g_prod = self.sde.g_prod(t0 + sra1.C1[i] * dt, y0, g_weight)
          y1 = y1 + sra1.alpha[i] * f * dt + g_prod
      return y1, ()
  
file_path: torchsde/torchsde/_core/methods/srk.py
imports: from .tableaus import sra1, srid2
  from ..None import adjoint_sde
  from ..None import base_solver
  from ...settings import SDE_TYPES, NOISE_TYPES, LEVY_AREA_APPROXIMATIONS
label_desc: Use image node_id 4 for calling the SRK obj's underlying member method code with example usage: obj.additive_step(t0, t1, y0, extra0) and returns: y1,  