int j = i & ARRAY_MASK;
      tmp += LongMath.log2(positive[j], mode);
    }
    return tmp;
  }

  @Benchmark
  int log10(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;
      tmp += LongMath.log10(positive[j], mode);
    }
    return tmp;
  }

  @Benchmark
  int sqrt(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {

      int j = i & ARRAY_MASK;
      tmp += IntMath.log2(positive[j], mode);
    }
    return tmp;
  }

  @Benchmark
  int log10(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {
      int j = i & ARRAY_MASK;
      tmp += IntMath.log10(positive[j], mode);
    }
    return tmp;
  }

  @Benchmark
  int sqrt(int reps) {
    int tmp = 0;
    for (int i = 0; i < reps; i++) {

// 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.
//

}

// Op: Log1p()
// Summary: Computes natural logarithm of (1 + x) element-wise.
//
// Description:
//   I.e., \\(y = \log_e (1 + x)\\).
//
//   Example:
//
//   ```python
//   x = tf.constant([0, 0.5, 1, 5])
//   tf.math.log1p(x) ==> [0., 0.4054651, 0.6931472, 1.7917595]
//   ```
Status Log1p(AbstractContext* ctx, AbstractTensorHandle* const x,

        assertEquals(BigIntegerMath.log10(valueOf(x), mode), LongMath.log10(x, mode));
      }
    }
  }

  // Relies on the correctness of log10(long, FLOOR) and of pow(long, int).
  @GwtIncompatible // TODO
  public void testLog10Exact() {
    for (long x : POSITIVE_LONG_CANDIDATES) {
      int floor = LongMath.log10(x, FLOOR);
      boolean expectedSuccess = LongMath.pow(10, floor) == x;

  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 \

DATA log10rodataL19<>+112(SB)/8, $-.64572084905921579630E-07
DATA log10rodataL19<>+120(SB)/8, $-5.5
DATA log10rodataL19<>+128(SB)/8, $18446744073709551616.
GLOBL log10rodataL19<>+0(SB), RODATA, $136

// Table of log10 correction terms
DATA log10tab2074<>+0(SB)/8, $0.254164497922885069E-01
DATA log10tab2074<>+8(SB)/8, $0.179018857989381839E-01
DATA log10tab2074<>+16(SB)/8, $0.118926768029048674E-01

     * 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[Integer.numberOfLeadingZeros(x)];
    /*
     * y is the higher of the two possible values of floor(log10(x)). If x < 10^y, then we want the

		}
	}
}
func TestLog10(t *testing.T) {
	for i := 0; i < len(vc); i++ {
		if f := Log10(vc[i]); !cVeryclose(log10[i], f) {
			t.Errorf("Log10(%g) = %g, want %g", vc[i], f, log10[i])
		}
	}
	for _, v := range log10SC {
		if f := Log10(v.in); !cAlike(v.want, f) {
			t.Errorf("Log10(%g) = %g, want %g", v.in, f, v.want)
		}
		if math.IsNaN(imag(v.in)) || math.IsNaN(imag(v.want)) {

   *     is not a power of ten
   */
  @GwtIncompatible // TODO
  @SuppressWarnings("fallthrough")
  public static int log10(BigInteger x, RoundingMode mode) {
    checkPositive("x", x);
    if (fitsInLong(x)) {
      return LongMath.log10(x.longValue(), mode);
    }

    int approxLog10 = (int) (log2(x, FLOOR) * LN_2 / LN_10);
    BigInteger approxPow = BigInteger.TEN.pow(approxLog10);