func.return %4 : tensor<*xf32>
}

// CHECK: %[[q:.*]] = "quantfork.qcast"(%arg0)
// CHECK: %[[sc1:.*]] = "quantfork.scast"(%[[q]]) : (tensor<*x!quant.uniform<i8:f32, 5.000000e-02:-10>>)
// CHECK: %[[fcast:.*]] = "tf.Cast"(%[[sc1]]) <{Truncate = false}> : (tensor<*xi8>) -> tensor<*xf32>
// CHECK: %[[avgpool_f32:.*]] = "tf.AvgPool"(%[[fcast]])
// CHECK-SAME: (tensor<*xf32>) -> tensor<*xf32>
// CHECK: %[[round:.*]] = "tf.Round"(%[[avgpool_f32]])

     *
     * @param outputType The type to cast the input to
     * @param object The object to be cast (must not be {@code null})
     * @param <O> The type to be cast to
     * @param <I> The type of the object to be vast
     * @return The input object, cast to the output type
     */
    public static <O, I> O cast(Class<O> outputType, I object) {
        try {

  }
};

// Inserts a "quant.qcast" and "quant.dcast" op pair (QDQs) in place of the
// tf.FakeQyantWithMinMax{Vars|VarsPerChannel|Args}Op
// before the op being constant folded. Since the constant
// folding logic will use a "arith.constant" op to replace the
// "tf.FakeQuantWithMinMaxVarsOp", the "quant.qcast" op is used to preserve
// the quantization parameters as a TypeAttr and "quant.dcast" op used to

   %1 = "quantfork.qcast"(%0) {volatile} : (tensor<2x3xf32>) -> tensor<2x3x!quant.uniform<i8<-127:127>:f32, 5.000000e-03>>
   %2 = "quantfork.dcast"(%1) : (tensor<2x3x!quant.uniform<i8<-127:127>:f32, 5.000000e-03>>) -> tensor<2x3xf32>
   %3 = "quantfork.qcast"(%arg0) {volatile} : (tensor<1x2xf32>) -> tensor<1x2x!quant.uniform<i8:f32, 6.000000e-03:-128>>

  // CHECK-NOT: "quantfork.qcast"
  // CHECK-NOT: "quantfork.dcast"
  // CHECK: return %[[CST]]
  %cst = stablehlo.constant dense<[[-0.960978984, -0.390246302], [-0.790828585, -0.601039409], [-1.0280807, -1.02731466]]> : tensor<3x2xf32>
  %q = "quantfork.qcast"(%cst) {volatile} : (tensor<3x2xf32>) -> tensor<3x2x!quant.uniform<i8:f32, 0.013075299590241675:-64>>

    b.setInsertionPoint(op);
    if (auto dq = llvm::dyn_cast<DequantizeOp>(op)) {
      auto dcast = b.create<quantfork::DequantizeCastOp>(
          dq.getLoc(), dq.getOutput().getType(), dq.getInput());
      dq.getOutput().replaceAllUsesWith(dcast);
      dq.erase();
    } else if (auto q = llvm::dyn_cast<QuantizeOp>(op)) {
      auto qcast = b.create<quantfork::QuantizeCastOp>(
          q.getLoc(), q.getOutput().getType(), q.getInput());

    %cst = stablehlo.constant dense<3.000000e-01> : tensor<2x3xf32>
    %0 = "quantfork.qcast"(%cst) : (tensor<2x3xf32>) -> tensor<2x3x!quant.uniform<i8:f32, 6.000000e-03>>
    %1 = "quantfork.dcast"(%0) : (tensor<2x3x!quant.uniform<i8:f32, 6.000000e-03>>) -> tensor<2x3xf32>

				//      case.
				//
				// UnstructuredJSONScheme's behavior is replicated here.
				var items []interface{}
				if uncast, present := content["items"]; present {
					var cast bool
					items, cast = uncast.([]interface{})
					if !cast {
						strict, lax = nil, fmt.Errorf("items field of UnstructuredList must be encoded as an array or null if present")
						return
					}
				}

    return false;

  if (mlir::cast<IntegerAttr>(elements.front()).getInt() != 1 ||
      mlir::cast<IntegerAttr>(elements.back()).getInt() != 1)
    return false;

  Builder b(op->getContext());
  *x = b.getI32IntegerAttr(mlir::cast<IntegerAttr>(elements[1]).getInt());
  *y = b.getI32IntegerAttr(mlir::cast<IntegerAttr>(elements[2]).getInt());
  *z = b.getI32IntegerAttr(mlir::cast<IntegerAttr>(elements[3]).getInt());

package org.gradle.internal

import spock.lang.Specification

import static Cast.cast

class CastTest extends Specification {

    def "casting"() {
        given:
        def arg = "1"

        when:
        cast(Integer, arg)

        then:
        def e = thrown(ClassCastException)
        e.message == "Failed to cast object $arg of type ${arg.class.name} to target type ${Integer.name}"

        when: