%identity = "tf.Identity"(%input) : (tensor<*xi8>) -> tensor<*xi8>
    %input_i32 = "tf.Cast"(%identity) : (tensor<*xi8>) -> tensor<*xi32>
    %output = "tf.Sub"(%input_i32, %zp) : (tensor<*xi32>, tensor<*xi32>) -> tensor<*xi32>
    %cast = "tf.Cast"(%output) : (tensor<*xi32>) -> tensor<*xf32>
    %mul = "tf.Mul"(%cast, %scale) : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
    func.return %mul : tensor<*xf32>
  }

    %1 = "tf.Round"(%0) : (tensor<1x2240x2240x3xf32>) -> tensor<1x2240x2240x3xf32>
    %2 = "tf.Cast"(%1) : (tensor<1x2240x2240x3xf32>) -> tensor<1x2240x2240x3xi32>
    %3 = "tf.AddV2"(%2, %arg2) : (tensor<1x2240x2240x3xi32>, tensor<i32>) -> tensor<1x2240x2240x3xi32>
    %4 = "tf.Cast"(%3) {Truncate = false} : (tensor<1x2240x2240x3xi32>) -> tensor<1x2240x2240x3xi8>
    return %4 : tensor<1x2240x2240x3xi8>
  }

        }
        return type.cast(this);
    }

    public T notEmpty() {
        notNull();
        if (value.length() == 0) {
            throw failure(String.format("%s cannot be empty.", name));
        }
        return type.cast(this);
    }

    public T validInFileName() {
        if (value == null || value.length() == 0) {
            return type.cast(this);
        }

  func.return %0 : tensor<1x2x3xf32>

// CHECK-NEXT: %[[AXIS:.*]] = arith.constant 0 : i32
// CHECK-NEXT: %[[CAST:.*]] = "tfr.cast"(%arg0) : (tensor<2x3xf32>) -> !tfr.tensor
// CHECK-NEXT: %[[ED:.*]] = tfr.call @tf__expand_dims(%[[CAST]], %[[AXIS]]) : (!tfr.tensor, i32) -> !tfr.tensor
// CHECK-NEXT: %[[BACK:.*]] = "tfr.cast"(%[[ED]]) : (!tfr.tensor) -> tensor<1x2x3xf32>
// CHECK-NEXT: return %[[BACK]] : tensor<1x2x3xf32>
}

        if (type.isInstance(getValue())) {
            return type.cast(this);
        }
        if (type.isEnum()) {
            return type.cast(Enum.valueOf(Cast.uncheckedNonnullCast(type.asSubclass(Enum.class)), getValue()));
        }
        if (Named.class.isAssignableFrom(type)) {
            return type.cast(instantiator.named(type.asSubclass(Named.class), getValue()));
        }

    if (!mlir::cast<ShapedType>(conv_op.getRhs().getType()).hasStaticShape()) {
      return false;
    }
    if (!mlir::cast<ShapedType>(conv_op.getLhs().getType()).hasStaticShape() &&
        !mlir::cast<ShapedType>(conv_op.getType()).hasStaticShape()) {
      auto dnums = conv_op.getDimensionNumbers();
      auto lhs_type = mlir::cast<ShapedType>(conv_op.getLhs().getType());

        return Cast.uncheckedCast(instantiator.newInstance(DefaultPolymorphicDomainObjectContainer.class, elementType, instantiator, elementInstantiator, collectionCallbackActionDecorator));
    }

    @Override
    public <T> DomainObjectSet<T> newDomainObjectSet(Class<T> elementType) {
        Instantiator instantiator = instantiatorFactory.decorateLenient();

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:

// CHECK: %[[quant:.*]] = "tfr.cast"(%arg0) : (tensor<1x10xi8>) -> !tfr.tensor
// CHECK: %[[scale_cast:.*]] = "tfr.cast"(%[[scale]])
// CHECK: %[[zp_cast:.*]] = "tfr.cast"(%[[zp]])
// CHECK: %[[requant:.*]] = tfr.call @tf__requantize(%[[quant]], %[[scale_cast]], %[[zp_cast]])
// CHECK: %[[result:.*]] = "tfr.cast"(%[[requant]])
// CHECK-NOT: quant.uniform

    %identity = "tf.Identity"(%input) : (tensor<*xi8>) -> tensor<*xi8>
    %input_i32 = "tf.Cast"(%identity) : (tensor<*xi8>) -> tensor<*xi32>
    %output = "tf.Sub"(%input_i32, %zp) : (tensor<*xi32>, tensor<*xi32>) -> tensor<*xi32>
    %cast = "tf.Cast"(%output) : (tensor<*xi32>) -> tensor<*xf32>
    %mul = "tf.Mul"(%cast, %scale) : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
    func.return %mul : tensor<*xf32>
  }