Function PowGrad

tensorflow/cc/gradients/math_grad.cc:508–540

REGISTER_GRADIENT_OP("AddN", AddNGrad);

Status PowGrad(const Scope& scope, const Operation& op,
               const std::vector<Output>& grad_inputs,
               std::vector<Output>* grad_outputs) {
  auto x = ConjugateHelper(scope, op.input(0));
  auto y = ConjugateHelper(scope, op.input(1));
  auto z = ConjugateHelper(scope, op.output(0));
  auto grad = grad_inputs[0];
  // grad * y * pow(x, y - 1)
  auto one = Cast(scope, Const(scope, 1.0), y.type());
  auto gx_1 = Mul(scope,
                  Mul(scope, grad, y),
                  Pow(scope, x, Sub(scope, y, one)));
  // Avoid false singularity at x = 0
  DataType x_dtype = x.type();
  auto zero = Cast(scope, Const(scope, 0.0), x_dtype);
  if (x_dtype == DT_COMPLEX64 || x_dtype == DT_COMPLEX128) {
    // real(x) < 0 is fine for the complex case
    auto log_x = Where3(scope,
                        NotEqual(scope, x, zero),
                        Log(scope, x),
                        ZerosLike(scope, x));
    auto gy_1 = Mul(scope, Mul(scope, grad, z), log_x);
    return BinaryGradCommon(scope, op, grad_outputs, gx_1, gy_1);
  } else {
    // There's no sensible real value to return if x < 0, so return 0
    auto log_x = Where3(scope,
                        Greater(scope, x, zero),
                        Log(scope, x),
                        ZerosLike(scope, x));
    auto gy_1 = Mul(scope, Mul(scope, grad, z), log_x);
    return BinaryGradCommon(scope, op, grad_outputs, gx_1, gy_1);
  }
}
REGISTER_GRADIENT_OP("Pow", PowGrad);

// MaximumMinimumGradCommon adds shared ops to calculate gradients for