func.func @is_nan(%arg0: tensor<3x4xf32>) -> tensor<3x4xi1> {
  // CHECK: %[[RESULT:.*]] = "tf.NotEqual"(%arg0, %arg0) <{incompatible_shape_error = true}> : (tensor<3x4xf32>, tensor<3x4xf32>) -> tensor<3x4xi1>
  %0 = "tf.IsNan"(%arg0) : (tensor<3x4xf32>) -> tensor<3x4xi1>
  // CHECK: return %[[RESULT]]
  func.return %0 : tensor<3x4xi1>
}

// CHECK-LABEL: func @fill
// CHECK-SAME: (%[[ARG0:.*]]: tensor<*xi64>, %[[ARG1:.*]]: tensor<*xf32>)

		if !(isSamePtr(p1, p2) && sizeof(t2) == 8 && is64BitFloat(t1) && !math.IsNaN(math.Float64frombits(uint64(x)))) {
			break
		}
		v.reset(OpConst64F)
		v.AuxInt = float64ToAuxInt(math.Float64frombits(uint64(x)))
		return true
	}
	// match: (Load <t1> p1 (Store {t2} p2 (Const32 [x]) _))
	// cond: isSamePtr(p1,p2) && sizeof(t2) == 4 && is32BitFloat(t1) && !math.IsNaN(float64(math.Float32frombits(uint32(x))))

	b := v.Block
	typ := &b.Func.Config.Types
	// match: (MTVSRD (MOVDconst [c]))
	// cond: !math.IsNaN(math.Float64frombits(uint64(c)))
	// result: (FMOVDconst [math.Float64frombits(uint64(c))])
	for {
		if v_0.Op != OpPPC64MOVDconst {
			break
		}
		c := auxIntToInt64(v_0.AuxInt)
		if !(!math.IsNaN(math.Float64frombits(uint64(c)))) {
			break
		}
		v.reset(OpPPC64FMOVDconst)

		{"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},
		{"Log", Func, 0},

.length-1}else e.some(f=>o(f))?n+=u([")"]):o("[")?n+=u(["]"]):["+","-","*","/"].includes(c)&&!["(","+","-","*","/",","].includes(a())?n+=` ${c} `:n+=c}return n.replace(/\s+/g," ")})}function as(i){return i.startsWith("url(")}function os(i){return!isNaN(Number(i))||ss(i)}function lr(i){return i.endsWith("%")&&os(i.slice(0,-1))||ss(i)}function ur(i){return i==="0"||new RegExp(`^[+-]?[0-9]*.?[0-9]+(?:[eE][+-]?[0-9]+)?${Mb}$`).test(i)||ss(i)}function Pu(i){return Bb.has(i)}function Du(i){let e=yi(L(i));for(let...

  );

  TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
}

def TF_IsNanOp : TF_Op<"IsNan", [Pure, SameOperandsAndResultShape]> {
  let summary = "Returns which elements of x are NaN.";

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

Example:

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

    *   Extend `tf.function` with basic support for CompositeTensors arguments
        (such as `SparseTensor` and `RaggedTensor`).
    *   `parallel_for.pfor`: add converters for Softmax, LogSoftmax, IsNaN, All,
        Any, and MatrixSetDiag.
    *   `parallel_for`: add converters for LowerTriangularSolve and Cholesky.
    *   `parallel_for`: add converters for `LogMatrixDeterminant` and
        `MatrixBandPart`.