b = mayAppendQuote(b, opts.quoted)
	e.Write(b)
}

type floatEncoder int // number of bits

func (bits floatEncoder) encode(e *encodeState, v reflect.Value, opts encOpts) {
	f := v.Float()
	if math.IsInf(f, 0) || math.IsNaN(f) {
		e.error(&UnsupportedValueError{v, strconv.FormatFloat(f, 'g', -1, int(bits))})
	}

	// Convert as if by ES6 number to string conversion.
	// This matches most other JSON generators.

          // Unary
          {"PW",
           {"ComplexAbs", "Angle", "Conj", "Abs", "Acos", "Acosh", "Asin",
            "Atan", "Atanh", "Ceil", "Cos", "Cosh", "Sin", "Exp", "Expm1",
            "Floor", "IsFinite", "IsInf", "IsNan", "Inv", "Reciprocal", "Log",
            "Log1p", "Invert", "LogicalNot", "Ndtri", "Neg", "Rint", "Round",
            "Rsqrt", "Sigmoid", "Sign", "Sinh", "Softplus", "Softsign", "Sqrt",

  // CHECK: %[[RESULT:.*]] = "tf.Equal"(%[[ABS]], %[[INF]]) <{incompatible_shape_error = true}> : (tensor<3x4xf32>, tensor<f32>) -> tensor<3x4xi1>
  %0 = "tf.IsInf"(%arg0) : (tensor<3x4xf32>) -> tensor<3x4xi1>
  // CHECK: return %[[RESULT]]
  func.return %0 : tensor<3x4xi1>
}

// CHECK-LABEL: @is_nan
func.func @is_nan(%arg0: tensor<3x4xf32>) -> tensor<3x4xi1> {

		if f := Gamma(vf[i]); !close(gamma[i], f) {
			t.Errorf("Gamma(%g) = %g, want %g", vf[i], f, gamma[i])
		}
	}
	for _, g := range vfgamma {
		f := Gamma(g[0])
		var ok bool
		if IsNaN(g[1]) || IsInf(g[1], 0) || g[1] == 0 || f == 0 {
			ok = alike(g[1], f)
		} else if g[0] > -50 && g[0] <= 171 {
			ok = veryclose(g[1], f)
		} else {
			ok = close(g[1], f)
		}
		if !ok {

		{"Float64bits", Func, 0},
		{"Float64frombits", Func, 0},
		{"Floor", Func, 0},
		{"Frexp", Func, 0},
		{"Gamma", Func, 0},
		{"Hypot", Func, 0},
		{"Ilogb", Func, 0},
		{"Inf", Func, 0},
		{"IsInf", Func, 0},
		{"IsNaN", Func, 0},
		{"J0", Func, 0},
		{"J1", Func, 0},
		{"Jn", Func, 0},
		{"Ldexp", Func, 0},
		{"Lgamma", Func, 0},
		{"Ln10", Const, 0},
		{"Ln2", Const, 0},

  );

  TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
}

def TF_IsInfOp : TF_Op<"IsInf", [Pure, SameOperandsAndResultShape]> {
  let summary = "Returns which elements of x are Inf.";

  let description = [{
@compatibility(numpy)
Equivalent to np.isinf
@end_compatibility

Example:

```python
x = tf.constant([5.0, np.inf, 6.8, np.inf])