* Transforms the given object, and returns the transformed value.
     *
     * @param in The object to transform.
     * @return The transformed object.
     */
    OUT transform(IN in);

    def "reuses file from its origin cache when transform is none"() {
        given:
        def file = testDir.file("other/thing.jar")
        _ * globalCacheLocations.isInsideGlobalCache(file.absolutePath) >> true
        jar(file)
        def classpath = DefaultClassPath.of(file)
        transformer.transform(classpath, None)

        when:
        def cachedClasspath = transformer.transform(classpath, None)

        then:

import org.gradle.internal.Either;
import org.gradle.internal.classpath.transforms.ClassTransform;
import org.gradle.internal.classpath.transforms.ClasspathElementTransformFactory;
import org.gradle.internal.classpath.transforms.ClasspathElementTransformFactoryForAgent;
import org.gradle.internal.classpath.transforms.ClasspathElementTransformFactoryForLegacy;
import org.gradle.internal.classpath.transforms.InstrumentingClassTransform;

            // 1. serialize a task that uses the transformed artifact
            // 2. serialize a task whose serialization triggers execution of that transform
            // 3. serialize another task that uses the transformed artifact
            // In addition, the 1st and 3rd tasks need to resolve different variants that share the same transform

                        return project.getConfigurations().create("transformed", transformed -> {
                            transformed.setCanBeConsumed(false);
                            transformed.setCanBeResolved(true);
                            transformed.extendsFrom(base);

                            transformed.getAttributes().attribute(ARTIFACT_TYPE_ATTRIBUTE, TXT_TYPE);
                        });

#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.h"
#include "tensorflow/compiler/mlir/tensorflow/transforms/passes.h"

namespace mlir {
namespace TF {

namespace {

import org.gradle.api.internal.initialization.transform.InstrumentationAnalysisTransform;
import org.gradle.api.internal.initialization.transform.MergeInstrumentationAnalysisTransform;
import org.gradle.api.internal.initialization.transform.ProjectDependencyInstrumentingArtifactTransform;
import org.gradle.api.internal.initialization.transform.services.CacheInstrumentationDataBuildService;

            return null;
        }
    }

    public static boolean tryInstall() {
        // Installing the same transformer multiple times is very problematic, so additional correctness check is worth it.
        if (!INSTALLED.compareAndSet(false, true)) {
            throw new IllegalStateException("The transformer is already installed in " + DefaultClassFileTransformer.class.getClassLoader());
        }

  let summary = "Applies automatic space to depth transform for the first or frontier convolutions consume host inputs on TPU.";

  let description = [{
    Automatic space to depth transform is done by adding space to depth transform op after host input
    and applying space to depth transform for the first convolution and its backprop filter on TPU.

    For example, original program:

    public enum MarkerResource {
        // The transformed marker resource is an empty file to reduce archive size in the most common case.
        TRANSFORMED(new byte[0]),
        // Not transformed marker resource is a 1-byte file with a single "N" symbol.
        NOT_TRANSFORMED(new byte[]{'N'});

        public static final String RESOURCE_NAME = TransformReplacer.class.getName() + ".transformed";