for (int exp : asList(-1022, -50, -1, 0, 1, 2, 3, 4, 100, 1022, 1023)) {
      for (RoundingMode mode : asList(HALF_EVEN, HALF_UP, HALF_DOWN)) {
        double x = Math.scalb(Math.sqrt(2) + 0.001, exp);
        double y = Math.scalb(Math.sqrt(2) - 0.001, exp);
        assertEquals(exp + 1, DoubleMath.log2(x, mode));
        assertEquals(exp, DoubleMath.log2(y, mode));
      }
    }
  }

	XVMODV		X3, X2, X1	// 418ce374
	XVMODBU		X3, X2, X1	// 410ce674
	XVMODHU		X3, X2, X1	// 418ce674
	XVMODWU		X3, X2, X1	// 410ce774
	XVMODVU		X3, X2, X1	// 418ce774

	// [X]VF{SQRT/RECIP/RSQRT}{F/D} instructions
	VFSQRTF		V1, V2		// 22e49c72
	VFSQRTD		V1, V2		// 22e89c72
	VFRECIPF	V1, V2		// 22f49c72
	VFRECIPD	V1, V2		// 22f89c72
	VFRSQRTF	V1, V2		// 22049d72
	VFRSQRTD	V1, V2		// 22089d72

   *
   * @throws IllegalStateException if the dataset is empty
   */
  public double populationStandardDeviation() {
    return Math.sqrt(populationVariance());
  }

  /**
   * Returns the <a href="http://en.wikipedia.org/wiki/Variance#Sample_variance">unbiased sample

assignment context to retrieve both the return value (if any) and the
C errno variable as an error (use _ to skip the result value if the
function returns void). For example:

	n, err = C.sqrt(-1)
	_, err := C.voidFunc()
	var n, err = C.sqrt(1)

Note that the C errno value may be non-zero, and thus the err result may be
non-nil, even if the function call is successful. Unlike normal Go conventions,

    assertEquals(ImmutableSet.of(1, 2, 3), bimap.inverse().keySet());
    assertEquals(ImmutableSet.of(1, 2, 3), sync.inverse().keySet());
  }

  private static final Function<Integer, Double> SQRT_FUNCTION = in -> Math.sqrt(in);

  public void testTransformValues() {
    Map<String, Integer> map = ImmutableMap.of("a", 4, "b", 9);
    Map<String, Double> transformed = transformValues(map, SQRT_FUNCTION);

        1e-10))` Alternatively, you can override `convolution_op`: `python class
        StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs,
        kernel): mean, var = tf.nn.moments(kernel, axes=[0, 1, 2],
        keepdims=True) # Author code uses std + 1e-5 return
        super().convolution_op(inputs, (kernel - mean) / tf.sqrt(var + 1e-10))`

tables[tableIndex].Select(t, windowValue) p.Add(p, t) tableIndex-- windowValue = byte & 0b1111 tables[tableIndex].Select(t, windowValue) p.Add(p, t) tableIndex-- } return p, nil } // {{.p}}Sqrt sets e to a square root of x. If x is not a square, {{.p}}Sqrt returns // false and e is unchanged. e and x can overlap. func {{.p}}Sqrt(e, x *{{ .Element }}) (isSquare bool) { candidate := new({{ .Element }}) {{.p}}SqrtCandidate(candidate, x) square := new({{ .Element }}).Square(candidate) if square.Equal(x) != 1 {...

tables[tableIndex].Select(t, windowValue) p.Add(p, t) tableIndex-- windowValue = byte & 0b1111 tables[tableIndex].Select(t, windowValue) p.Add(p, t) tableIndex-- } return p, nil } // {{.p}}Sqrt sets e to a square root of x. If x is not a square, {{.p}}Sqrt returns // false and e is unchanged. e and x can overlap. func {{.p}}Sqrt(e, x *{{ .Element }}) (isSquare bool) { candidate := new({{ .Element }}) {{.p}}SqrtCandidate(candidate, x) square := new({{ .Element }}).Square(candidate) if square.Equal(x) != 1 {...

pkg math, func Signbit(float64) bool
pkg math, func Sin(float64) float64
pkg math, func Sincos(float64) (float64, float64)
pkg math, func Sinh(float64) float64
pkg math, func Sqrt(float64) float64
pkg math, func Tan(float64) float64
pkg math, func Tanh(float64) float64
pkg math, func Trunc(float64) float64
pkg math, func Y0(float64) float64
pkg math, func Y1(float64) float64

the non-blank method and field names must be distinct.
</p>

<p>
Given defined type <code>Point</code> the declarations
</p>

<pre>
func (p *Point) Length() float64 {
	return math.Sqrt(p.x * p.x + p.y * p.y)
}

func (p *Point) Scale(factor float64) {
	p.x *= factor
	p.y *= factor
}
</pre>

<p>
bind the methods <code>Length</code> and <code>Scale</code>,