}
    auto const_op =
        rewriter.create<TF::ConstOp>(loc, new_type, tensor_proto_attr);
    // Add scast op to match quantize -> composition pattern. The added scast
    // is then removed by canonicalization. ([scast - scast] -> [])
    auto scast_op = rewriter.create<quantfork::StorageCastOp>(
        loc, tensor_qtype, const_op.getOutput());
    q_op->replaceAllUsesWith(scast_op);

				if cast != nil {
					st.setTemplate(cast, tmpl)
					st.clearTemplateArgs(args)
					cast = nil
				}
				a = nil
				next = tmpl
			case 'T':
				next = st.templateParam()
			case 'E':
				if a == nil {
					st.fail("expected prefix")
				}
				if cast != nil {
					var toTmpl *Template
					if castTempl, ok := cast.To.(*Template); ok {
						toTmpl = castTempl

				"application/vnd.oma.bcast.associated-procedure-parameter+xml",
				"application/vnd.oma.bcast.drm-trigger+xml",
				"application/vnd.oma.bcast.imd+xml",
				"application/vnd.oma.bcast.ltkm",
				"application/vnd.oma.bcast.notification+xml",
				"application/vnd.oma.bcast.provisioningtrigger",
				"application/vnd.oma.bcast.sgboot",
				"application/vnd.oma.bcast.sgdd+xml",
				"application/vnd.oma.bcast.sgdu",

    %18 = "tf.Round"(%17) : (tensor<f32>) -> tensor<f32>
    %19 = "tf.Cast"(%18) : (tensor<f32>) -> tensor<i32>
    %20 = "tf.AddV2"(%19, %arg10) : (tensor<i32>, tensor<i32>) -> tensor<i32>
    %21 = "tf.Cast"(%20) : (tensor<i32>) -> tensor<i8>
    %22 = "tf.Cast"(%21) {Truncate = false} : (tensor<i8>) -> tensor<i8>
    %23 = "tf.Cast"(%22) {Truncate = false} : (tensor<i8>) -> tensor<i32>

            // CHECK: %[[CAST:.+]] = "tf.Cast"(%[[CARG1]])
            // CHECK: "tf.Less"(%[[CARG0]], %[[CAST]])
            // CHECK: "tf.Yield"
            ^bb0(%carg0: tensor<i32>, %carg1: !tf_ref, %carg2: !tf_ref, %carg3: !tf_ref):
               %read0 = "tf.ReadVariableOp"(%carg1) : (!tf_ref) -> tensor<f32>
               %cast = "tf.Cast"(%read0) : (tensor<f32>) -> tensor<i32>

    auto cond = symbol_table.lookup<mlir::func::FuncOp>(
        while_op->getAttr("cond").cast<mlir::FlatSymbolRefAttr>().getValue());
    AddCallOpInWhileOpRegion(while_op.getCond(), cond);
    while_op->removeAttr("cond");
    auto body = symbol_table.lookup<mlir::func::FuncOp>(
        while_op->getAttr("body").cast<mlir::FlatSymbolRefAttr>().getValue());
    AddCallOpInWhileOpRegion(while_op.getBody(), body);

  // CHECK: [[VAL15:%.+]] = "tf.Cast"([[VAL10]]#1)
  // CHECK: [[VAL16:%.+]] = "tf.Div"([[VAL15]], [[VAL6]])
  // CHECK: [[VAL17:%.+]] = "tf.Mul"([[VAL16]], [[VAL5]])
  // CHECK: [[VAL18:%.+]] = "tf.Cast"([[VAL17]])
  // CHECK: [[VAL19:%.+]] = "tf.Reshape"([[VAL18]], [[VAL1]])
  // CHECK: [[VAL20:%.+]] = "tf.Mul"([[VAL19]], [[VAL10]]#2)
  // CHECK: [[VAL21:%.+]] = "tf.Cast"([[VAL10]]#2)

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.gradle.internal.service;

import org.gradle.api.Action;
import org.gradle.internal.Cast;
import org.gradle.internal.Factory;
import org.gradle.internal.concurrent.CompositeStoppable;
import org.gradle.internal.concurrent.Stoppable;

import javax.annotation.Nullable;
import java.io.Closeable;

	svc, exists := proxier.svcPortMap[*svcPortName]

	if exists {
		svcInfo, ok := svc.(*serviceInfo)

		if !ok {
			klog.ErrorS(nil, "Failed to cast serviceInfo", "servicePortName", svcPortName)
			return
		}

		if svcInfo.winProxyOptimization && redundantCleanup {
			// This is a second cleanup call.

  Output a = ops::Placeholder(root.WithOpName("test/a"), DT_INT64);
  Output b = ops::Placeholder(root.WithOpName("test/b"), DT_INT64);

  Output cast_a = ops::Cast(root.WithOpName("test/cast_a"), a, DT_INT32);
  Output cast_b = ops::Cast(root.WithOpName("test/cast_b"), b, DT_INT32);

  Output tensor_list_reserve = ops::TensorListReserve(
      root.WithOpName("test/tensor_list_reserve"), cast_a, cast_b, DT_FLOAT);