this.artifactCacheRules = new ArrayList<>(policy.artifactCacheRules);
        this.offline = policy.offline;
        this.refresh = policy.refresh;
    }

    /**
     * Sets the validator to invoke prior to each mutation.
     */
    public void setMutationValidator(MutationValidator validator) {
        this.mutationValidator = validator;
    }

    @Override
    public void setOffline() {

        private val mainKtFile: KtFile,
        private val injectedSymbolMapping: Map<CodeFragmentCapturedId, InjectedValue>
    ) : (FirReference, Fir2IrConversionScope) -> InjectedValue? {
        override fun invoke(calleeReference: FirReference, conversionScope: Fir2IrConversionScope): InjectedValue? {
            val irFile = conversionScope.containingFileIfAny()
            val psiFile = (irFile?.fileEntry as? PsiIrFileEntry)?.psiFile

  // wrt the input.
  if (reduced_label_set.empty()) {
    return grad_reduced;
  }
  // Otherwise, we currently have the gradient wrt the output of the reduction
  // operation "abc->ac". Invoke the subroutine for the gradient for unary
  // einsum with reductions.
  return EinsumGradReducedHelper(scope, grad_reduced, left_subs, input_subs,
                                 input_shape, reduced_label_set);
}

import static com.google.common.base.Throwables.throwIfUnchecked;
import static java.lang.invoke.MethodType.methodType;

import com.google.errorprone.annotations.Immutable;
import com.google.j2objc.annotations.J2ObjCIncompatible;
import java.lang.invoke.MethodHandle;
import java.lang.invoke.MethodHandles;
import java.security.Key;
import java.util.ArrayList;
import java.util.Arrays;

          Class.forName("com.google.appengine.api.ThreadManager")
              .getMethod("currentRequestThreadFactory")
              .invoke(null);
    } catch (IllegalAccessException | ClassNotFoundException | NoSuchMethodException e) {
      throw new RuntimeException("Couldn't invoke ThreadManager.currentRequestThreadFactory", e);
    } catch (InvocationTargetException e) {
      throw Throwables.propagate(e.getCause());
    }

	String() string  // string form of address (for example, "192.0.2.1:25", "[2001:db8::1]:80")
}

// Conn is a generic stream-oriented network connection.
//
// Multiple goroutines may invoke methods on a Conn simultaneously.
type Conn interface {
	// Read reads data from the connection.
	// Read can be made to time out and return an error after a fixed
	// time limit; see SetDeadline and SetReadDeadline.

            for (String prefix : Arrays.asList("get", "is", "to", "as")) {
                Method method = classMap.findMethod(prefix + methodBase);
                if (method != null) {
                    return method.invoke(value, OBJECT_ARGS);
                }
            }
            return null;
        } catch (InvocationTargetException e) {
            throw new IntrospectionException(e.getTargetException());

        prettyPrint(event).let { prettyPrinted ->
            println(prettyPrinted)
            events.add(LogEvent(event, prettyPrinted))
        }
    }

    override fun invoke(severity: ReportSeverity, message: String, position: Position?) {
        println("[EDITOR_$severity] '$message' ${position?.line ?: ""}")
        reports.add(IdeReport(severity, message, position))
    }

	// if a new sandbox does not need to be created for a pod, it indicates that
	// a sandbox for the pod with networking configured already exists.
	// Otherwise, the kubelet needs to invoke the container runtime to create a
	// fresh sandbox and configure networking for the sandbox.
	if !newSandboxNeeded {
		return v1.PodCondition{
			Type:   v1.PodReadyToStartContainers,
			Status: v1.ConditionTrue,

    ::mlir::Value variance = rewriter.create<TF::MeanOp>(
        bn_op.getLoc(), mean_var_type, square_diff, reduce_dim_op,
        /*keep_dims=*/rewriter.getBoolAttr(false));

    // Invoke BatchNormInferenceOp
    ::mlir::FloatAttr epsilon = bn_op.getEpsilonAttr();
    ::mlir::Value batch_norm = rewriter.create<mhlo::BatchNormInferenceOp>(
        bn_op.getLoc(), inputs, bn_op.getScale(), bn_op.getOffset(), mean,