def METHOD_NAME():
  snapshot: nimble.neural.BackpropSnapshot = nimble.neural.forwardPass(world, idempotent=True)
  forceVel = snapshot.getControlForceVelJacobian(world)
  velPreStep = snapshot.getPreStepVelocity()
  velPostStep = snapshot.getPostStepVelocity()
  velDelta = velPostStep - velPreStep
  # Trim small singular values manually, to avoid having explosions when we invert
  U, S, V = np.linalg.svd(forceVel)
  Sinv = S
  for i in range(len(S)):
    if abs(S[i]) < 1e-5:
      Sinv[i] = 0
    else:
      Sinv[i] = 1/S[i]
  # Invert, with tiny singular values now set to 0, instead of massive values
  forceVelInv = np.matmul(np.transpose(V), np.diag(Sinv), np.transpose(U))
  # Compute the control forces we'd need in order to stabilize
  stabilizingControls = np.matmul(forceVelInv, -velDelta)
  # Check how much velocity we'd actually accumulate here
  inverted = np.matmul(forceVel, stabilizingControls)
  atlas.setControlForces(stabilizingControls)