fmt.Printf("%.1f\n", y)
	// Output:
	// 0.0
	// 1.0
}

func ExampleLog2() {
	fmt.Printf("%.1f", math.Log2(256))
	// Output: 8.0
}

func ExampleLog10() {
	fmt.Printf("%.1f", math.Log10(100))
	// Output: 2.0
}

func ExampleRemainder() {
	fmt.Printf("%.1f", math.Remainder(100, 30))
	// Output: 10.0
}

func ExampleMod() {
	c := math.Mod(7, 4)
	fmt.Printf("%.1f", c)

// Method :
//	Based on
//	        acosh(x) = log [ x + sqrt(x*x-1) ]
//	we have
//	        acosh(x) := log(x)+ln2,	if x is large; else
//	        acosh(x) := log(2x-1/(sqrt(x*x-1)+x)) if x>2; else
//	        acosh(x) := log1p(t+sqrt(2.0*t+t*t)); where t=x-1.
//
// Special cases:
//	acosh(x) is NaN with signal if x<1.
//	acosh(NaN) is NaN without signal.
//

// Acosh returns the inverse hyperbolic cosine of x.
//

     * can narrow the possible floor(log10(x)) values to two. For example, if floor(log2(x)) is 6,
     * then 64 <= x < 128, so floor(log10(x)) is either 1 or 2.
     */
    int y = maxLog10ForLeadingZeros[Long.numberOfLeadingZeros(x)];
    /*
     * y is the higher of the two possible values of floor(log10(x)). If x < 10^y, then we want the

	Ln2    = 0.693147180559945309417232121458176568075500134360255254120680009 // https://oeis.org/A002162
	Log2E  = 1 / Ln2
	Ln10   = 2.30258509299404568401799145468436420760110148862877297603332790 // https://oeis.org/A002392
	Log10E = 1 / Ln10
)

// Floating-point limit values.
// Max is the largest finite value representable by the type.
// SmallestNonzero is the smallest positive, non-zero value representable by the type.
const (

  ExpandDims \
  OnesLike

${generate} \
  --category=math \
  Mul \
  Conj \
  AddV2 \
  MatMul \
  Neg \
  Sum \
  Sub \
  Div \
  DivNoNan \
  Exp \
  Sqrt \
  SqrtGrad \
  Log1p

${generate} \
  --category=nn \
  SparseSoftmaxCrossEntropyWithLogits \
  ReluGrad \
  Relu \
  BiasAdd \
  BiasAddGrad

${generate} \
  --category=resource_variable \
  VarHandleOp \

     * can narrow the possible floor(log10(x)) values to two. For example, if floor(log2(x)) is 6,
     * then 64 <= x < 128, so floor(log10(x)) is either 1 or 2.
     */
    int y = maxLog10ForLeadingZeros[Long.numberOfLeadingZeros(x)];
    /*
     * y is the higher of the two possible values of floor(log10(x)). If x < 10^y, then we want the

// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

// issue 1136

package main

import "fmt"

func log1(f string, argv ...interface{}) {
	fmt.Printf("log: %s\n", fmt.Sprintf(f, argv...))
}

func main() {
	log1("%d", 42)

(tensor<3360x?xi32>, tensor<3xi32>) -> tensor<3x1120x?xi32> loc(#loc9)\0A    %1:3 = \22tf.Split\22(%arg2, %0) {_xla_outside_compilation = \220\22} : (tensor<i32>, tensor<3x1120x?xi32>) -> (tensor<1x1120x?xi32>, tensor<1x1120x?xi32>, tensor<1x1120x?xi32>) loc(#loc10)\0A    %2 = \22tf.Reshape\22(%1#0, %arg3) {_xla_outside_compilation = \220\22} : (tensor<1x1120x?xi32>, tensor<2xi32>) -> tensor<1120x?xi32> loc(#loc11)\0A    %3 = \22tf.Shape\22(%2) {_xla_outside_compilation = \220\22} : (tensor<1120x?xi32>) -> tensor<2xi32>...

}

TEST_F(CWiseUnaryGradTest, Log1p) {
  auto x_fn = [this](const int i) { return RV({0, 1e-6, 1, 2, 3, 4, 100}); };
  TestCWiseGrad<float, float>(LOG1P, x_fn);
}

TEST_F(CWiseUnaryGradTest, Log1p_Complex) {
  auto x_fn = [this](const int i) {
    return CRV({{0, 0}, {1e-6, 0}, {2, -1}, {1, 2}, {3, 4}});
  };
  TestCWiseGrad<complex64, complex64>(LOG1P, x_fn);
}

TEST_F(CWiseUnaryGradTest, Sinh) {

}

Status Log1pModel(AbstractContext* ctx,
                  absl::Span<AbstractTensorHandle* const> inputs,
                  absl::Span<AbstractTensorHandle*> outputs) {
  return ops::Log1p(ctx, inputs[0], &outputs[0], "Log1p");
}

Status DivNoNanModel(AbstractContext* ctx,
                     absl::Span<AbstractTensorHandle* const> inputs,
                     absl::Span<AbstractTensorHandle*> outputs) {