}

// CanFloat reports whether [Value.Float] can be used without panicking.
func (v Value) CanFloat() bool {
	switch v.kind() {
	case Float32, Float64:
		return true
	default:
		return false
	}
}

// Float returns v's underlying value, as a float64.
// It panics if v's Kind is not [Float32] or [Float64]
func (v Value) Float() float64 {
	k := v.kind()
	switch k {
	case Float32:

	// Fun with floating point.
	{math.NaN(), math.NaN(), false},
	{&[1]float64{math.NaN()}, &[1]float64{math.NaN()}, false},
	{&[1]float64{math.NaN()}, self{}, true},
	{[]float64{math.NaN()}, []float64{math.NaN()}, false},
	{[]float64{math.NaN()}, self{}, true},
	{map[float64]float64{math.NaN(): 1}, map[float64]float64{1: 2}, false},
	{map[float64]float64{math.NaN(): 1}, self{}, true},

	// Nil vs empty: not the same.

		if globalExpiryState != nil {
			expPendingTasks.Value = float64(globalExpiryState.PendingTasks())
			expMissedTasks.Value = float64(globalExpiryState.stats.MissedTasks())
			expMissedFreeVersions.Value = float64(globalExpiryState.stats.MissedFreeVersTasks())
			expMissedTierJournalTasks.Value = float64(globalExpiryState.stats.MissedTierJournalTasks())
			expNumWorkers.Value = float64(globalExpiryState.stats.NumWorkers())
		}

    }

    public void setBoost_Equal(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Equal(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {
        setBoost_Term(boost, opLambda);
    }

    public void setBoost_Term(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Term(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {

				"unsortedInts": []interface{}{int64(2), int64(1)},
				"emptyInts":    []interface{}{},

				"doubles":         []interface{}{float64(1), float64(2), float64(2), float64(3)},
				"unsortedDoubles": []interface{}{float64(2), float64(1)},
				"emptyDoubles":    []interface{}{},

				"intBackedDoubles":          []interface{}{int64(1), int64(2), int64(2), int64(3)},

        bias = array_ops.constant(
            np.random.uniform(size=[shapes[1][-1]]), dtype=dtypes.float32
        )
    model = MatmulModel(bias)
    x = array_ops.constant(
        np.random.uniform(size=x_shape), dtype=dtypes.float32
    )
    y = array_ops.constant(
        np.random.uniform(size=y_shape), dtype=dtypes.float32
    )
    if use_kernel:
      model.matmul = model.matmul_with_kernel

</p>

<pre>
uint(iota)               // iota value of type uint
float32(2.718281828)     // 2.718281828 of type float32
complex128(1)            // 1.0 + 0.0i of type complex128
float32(0.49999999)      // 0.5 of type float32
float64(-1e-1000)        // 0.0 of type float64
string('x')              // "x" of type string
string(0x266c)           // "♬" of type string

    }

    public void setBoost_Equal(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Equal(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {
        setBoost_Term(boost, opLambda);
    }

    public void setBoost_Term(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Term(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {

    }

    public void setBoost_Equal(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Equal(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {
        setBoost_Term(boost, opLambda);
    }

    public void setBoost_Term(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Term(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {

                 element_type)) {
    std::vector<float> mins = {static_cast<float>(qtype.getMin())};
    std::vector<float> maxs = {static_cast<float>(qtype.getMax())};
    q_params = tflite::CreateQuantizationParameters(
        builder_, builder_.CreateVector<float>(mins),
        builder_.CreateVector<float>(maxs));
  }
  return tflite::CreateTensor(