%0 = "tf.Sqrt"(%arg1) : (tensor<8x16xf32>) -> tensor<8x16xf32>
  %1 = "tf.Div"(%arg0, %0) {device = "/job:localhost/replica:0/task:0/device:GPU:0"} : (tensor<8x16xf32>, tensor<8x16xf32>) -> tensor<8x16xf32>
  func.return %1: tensor<8x16xf32>

// CHECK: %0 = "tf.Rsqrt"(%arg1) {device = "/job:localhost/replica:0/task:0/device:GPU:0"} : (tensor<8x16xf32>) -> tensor<8x16xf32>

^bb0(%arg0: tensor<? x f32>):
  // CHECK: "tfl.rsqrt"(%arg0)
  %0 = "tfl.rsqrt"(%arg0): (tensor<? x f32>) -> tensor<? x f32>
  func.return %0 : tensor<? x f32>
}

// CHECK-LABEL: testRsqrtQuant
func.func @testRsqrtQuant(%arg0: tensor<1x80x1x!quant.uniform<i8:f32, 0.048358432948589325:-128>>) -> tensor<1x80x1x!quant.uniform<i8:f32, 0.0066055487841367722:-128>> {

  );

  let results = (outs
    TFL_TensorOf<[F32, I32, I64, QI16, QUI8, TFL_Quint8]>:$output
  );

  let hasOptions = 1;
}

def TFL_RsqrtOp: TFL_Op<"rsqrt", [Pure,
                                  QuantizableResult,
                                  TFL_SameFirstOperandAndFirstResultElementType,
                                  SameOperandsAndResultShape]> {

   * Map<String, Integer> map = ImmutableMap.of("a", 4, "b", 9);
   * Function<Integer, Double> sqrt =
   *     new Function<Integer, Double>() {
   *       public Double apply(Integer in) {
   *         return Math.sqrt((int) in);
   *       }
   *     };
   * Map<String, Double> transformed = Maps.transformValues(map, sqrt);
   * System.out.println(transformed);
   * }</pre>
   *

   * Map<String, Integer> map = ImmutableMap.of("a", 4, "b", 9);
   * Function<Integer, Double> sqrt =
   *     new Function<Integer, Double>() {
   *       public Double apply(Integer in) {
   *         return Math.sqrt((int) in);
   *       }
   *     };
   * Map<String, Double> transformed = Maps.transformValues(map, sqrt);
   * System.out.println(transformed);
   * }</pre>
   *

(Div64F x (Const64F <t> [c])) && reciprocalExact64(c) => (Mul64F x (Const64F <t> [1/c]))

// rewrite single-precision sqrt expression "float32(math.Sqrt(float64(x)))"
(Cvt64Fto32F sqrt0:(Sqrt (Cvt32Fto64F x))) && sqrt0.Uses==1 => (Sqrt32 x)

(Sqrt (Const64F [c])) && !math.IsNaN(math.Sqrt(c)) => (Const64F [math.Sqrt(c)])

// for rewriting results of some late-expanded rewrites (below)
(SelectN [0] (MakeResult x ___)) => x

          input_tensor, min=-0.1, max=0.2, num_bits=8, narrow_range=False
      )
      sqrt = math_ops.sqrt(q_input, name='sqrt')
      identity = array_ops.identity(sqrt, name='output')

      input_map = {'input': input_tensor}
      output_map = {'sqrt': identity}
      signature = signature_def_utils_impl.predict_signature_def(
          inputs=input_map, outputs=output_map
      )

// CHECK-LABEL: sigmoid
// CHECK:  "tfl.logistic"(%arg0) : (tensor<?x88xf32>) -> tensor<?x88xf32>
}

func.func @sqrt(%arg0: tensor<8x16xf32>) -> tensor<8x16xf32> {
  %0 = "tf.Sqrt"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16xf32>
  func.return %0 : tensor<8x16xf32>
// CHECK-LABEL: sqrt
// CHECK:  "tfl.sqrt"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16xf32>
}

func.func @square(%arg0: tensor<8x16xf32>) -> tensor<8x16xf32> {

  if (!IsF32ShapedType(result_type)) return nullptr;

  auto compute = [](APFloat value) -> APFloat {
    float f = value.convertToFloat();
    float result = std::sqrt(f);
    return APFloat(result);
  };
  return ConstFoldUnaryOp(result_type, operands[0], compute);
}

//===----------------------------------------------------------------------===//
// RsqrtOp

func isPrime(x uint64) bool {
	if x != 0 && x < 4 {
		return true // eliminates special-casing 2.
	} else if (x & 1) == 0 {
		return false // eliminates even numbers >2.
	}

	limit := uint64(math.Sqrt(float64(x)))
	for factor := uint64(3); factor <= limit; factor += 2 {
		if (x % factor) == 0 {
			return false
		}
	}
	return true
}

func validateSubset(subset *networking.Subset) error {