//      To compensate the error in the argument reduction, we use
//              expm1(r+c) = expm1(r) + c + expm1(r)*c
//                         ~ expm1(r) + c + r*c
//      Thus c+r*c will be added in as the correction terms for
//      expm1(r+c). Now rearrange the term to avoid optimization
//      screw up:
//                      (      2                                    2 )
//                      ({  ( r    [ R1 -  (3 - R1*r/2) ]  )  }    r  )

DATA ·expm1tab<> + 120(SB)/8, $-.115062908917949451E-01
GLOBL ·expm1tab<> + 0(SB), RODATA, $128

// Expm1 returns e**x - 1, the base-e exponential of x minus 1.
// It is more accurate than Exp(x) - 1 when x is near zero.
//
// Special cases are:
//      Expm1(+Inf) = +Inf
//      Expm1(-Inf) = -1
//      Expm1(NaN) = NaN
// Very large values overflow to -1 or +Inf.

var AsinhNovec = asinh
var ErfNovec = erf
var ErfcNovec = erfc
var AtanNovec = atan
var Atan2Novec = atan2
var CbrtNovec = cbrt
var LogNovec = log
var TanNovec = tan
var ExpNovec = exp
var Expm1Novec = expm1
var PowNovec = pow
var HypotNovec = hypot

func ExampleExp2() {
	fmt.Printf("%.2f\n", math.Exp2(1))
	fmt.Printf("%.2f\n", math.Exp2(-3))
	// Output:
	// 2.00
	// 0.12
}

func ExampleExpm1() {
	fmt.Printf("%.6f\n", math.Expm1(0.01))
	fmt.Printf("%.6f\n", math.Expm1(-1))
	// Output:
	// 0.010050
	// -0.632121
}

func ExampleTrunc() {
	fmt.Printf("%.2f\n", math.Trunc(math.Pi))
	fmt.Printf("%.2f\n", math.Trunc(-1.2345))
	// Output:

	}
	for i := 0; i < len(vf); i++ {
		a := vf[i] / 100
		if f := Expm1Novec(a); !veryclose(expm1[i], f) {
			t.Errorf("Expm1(%g) = %g, want %g", a, f, expm1[i])
		}
	}
	for i := 0; i < len(vf); i++ {
		a := vf[i] * 10
		if f := Expm1Novec(a); !close(expm1Large[i], f) {
			t.Errorf("Expm1(%g) = %g, want %g", a, f, expm1Large[i])
		}
	}
	for i := 0; i < len(vfexpm1SC); i++ {

}

TEST_F(CWiseUnaryGradTest, Expm1) {
  auto x_fn = [this](const int i) { return RV({0, -1, 1e-6, 1, -1.5, 1.5}); };
  TestCWiseGrad<float, float>(EXPM1, x_fn);
}

TEST_F(CWiseUnaryGradTest, Expm1_Complex) {
  auto x_fn = [this](const int i) {
    return CRV({{-1, 0}, {1, 0}, {1.5, -1.5}});
  };
  TestCWiseGrad<complex64, complex64>(EXPM1, x_fn);
}

TEST_F(CWiseUnaryGradTest, Log) {

                            (TF_ConstOp (getScaledAlpha $features)))))>;



//===----------------------------------------------------------------------===//
// Expm1 op patterns.
//===----------------------------------------------------------------------===//

// Expm1(x) = Exp(x) - 1
def LowerExp1mOp : Pat<
  (TF_Expm1Op $x),
  (TF_SubOp
    (TF_ExpOp $x),
    (TF_ConstOp (GetScalarOfType<1> $x))
  )>;

TEXT ·expm1TrampolineSetup(SB), NOSPLIT, $0
	MOVB   ·hasVX(SB), R1
	CMPBEQ R1, $1, vectorimpl                 // vectorfacility = 1, vector supported
	MOVD   $·expm1vectorfacility+0x00(SB), R1
	MOVD   $·expm1(SB), R2
	MOVD   R2, 0(R1)
	BR     ·expm1(SB)

vectorimpl:
	MOVD $·expm1vectorfacility+0x00(SB), R1
	MOVD $·expm1Asm(SB), R2
	MOVD R2, 0(R1)
	BR   ·expm1Asm(SB)

GLOBL ·expm1vectorfacility+0x00(SB), NOPTR, $8

		a := vf[i] / 100
		if f := Expm1(a); !veryclose(expm1[i], f) {
			t.Errorf("Expm1(%g) = %g, want %g", a, f, expm1[i])
		}
	}
	for i := 0; i < len(vf); i++ {
		a := vf[i] * 10
		if f := Expm1(a); !close(expm1Large[i], f) {
			t.Errorf("Expm1(%g) = %g, want %g", a, f, expm1Large[i])
		}
	}
	for i := 0; i < len(vfexpm1SC); i++ {
		if f := Expm1(vfexpm1SC[i]); !alike(expm1SC[i], f) {

                 std::vector<Output>* grad_outputs) {
  // y = expm1(x)
  // dy/dx = exp(x)
  auto dydx = Exp(scope, op.input(0));
  // grad(x) = grad(y) * conj(dy/dx)
  grad_outputs->push_back(
      Mul(scope, grad_inputs[0], ConjugateHelper(scope, dydx)));
  return scope.status();
}
REGISTER_GRADIENT_OP("Expm1", Expm1Grad);

Status LogGrad(const Scope& scope, const Operation& op,