"//tensorflow/core/grappler:grappler_item",
        "//tensorflow/core/grappler:grappler_item_builder",
        "//tensorflow/core/grappler/clusters:virtual_cluster",
        "//tensorflow/core/grappler/optimizers:meta_optimizer",
        "//tensorflow/core/protobuf:for_core_protos_cc",
        "@llvm-project//llvm:Support",
    ],

    }
    for (const auto& input : specs.inputs) {
      terminal_nodes.push_back(input.first);
    }
    TF_RETURN_IF_ERROR(tensorflow::grappler::SetTransitiveFaninGraph(
        graphdef, &pruned_graph_def, terminal_nodes));
    // TODO(ashwinm): Add a separate utility in grappler utils that abstracts
    // both SetTransitiveFaninGraph and restoring the missing contents from the

// Note: This implements the fusions performed in the old Remapper Grappler
// pass. That pass has specific cases for GPU and based on different
// target configurations on both CPU and GPU (Intel MKL, ROCm, etc.). This MLIR
// pass covers (some of) the general CPU case and at the moment does not account
// for any target-specific configurations.

// This pass is being ported over from the Grappler Remapper pass based on

        "//tensorflow/cc/saved_model:loader.h",
    ],
)

filegroup(
    name = "pywrap_required_hdrs",
    srcs = [
        "training/coordinator.h",
    ],
    visibility = ["//tensorflow/python/grappler:__pkg__"],
)

cc_library(
    name = "gradients",
    srcs = [
        "framework/gradients.cc",
        "framework/while_gradients.cc",
        "framework/while_gradients.h",
    ],

import org.gradle.api.tasks.TaskAction;
import org.gradle.api.tasks.options.Option;
import org.gradle.api.tasks.options.OptionValues;
import org.gradle.api.tasks.wrapper.internal.DefaultWrapperVersionsResources;
import org.gradle.api.tasks.wrapper.internal.WrapperDefaults;
import org.gradle.api.tasks.wrapper.internal.WrapperGenerator;
import org.gradle.util.GradleVersion;
import org.gradle.util.internal.GUtil;

java.net.URLConnection); public final String calculateUserAgent(); } org/gradle/wrapper/GradleUserHomeLookup.class package org.gradle.wrapper; public abstract synchronized class GradleUserHomeLookup { public static final String DEFAULT_GRADLE_USER_HOME; static void <clinit>(); } org/gradle/wrapper/GradleWrapperMain.class package org.gradle.wrapper; public synchronized class GradleWrapperMain { public static void main(String[]); } org/gradle/wrapper/Install$1.class package org.gradle.wrapper; public final synchronized...

                TARGET_WRAPPER_FINAL + "/gradle-wrapper.properties")
        new File(getProject().getProjectDir(), TARGET_WRAPPER_FINAL).mkdirs()
        wrapper.setDistributionPath("somepath")
        wrapper.setDistributionSha256Sum("somehash")
    }

    Wrapper getTask() {
        return wrapper
    }

    def "wrapper has correct defaults"() {
        given:
        wrapper = createTask(Wrapper.class)

        expect:

d81e0f23ade952b35e55333dd5f1821585e887c6d24305aeea2fbc8dad564b95 gradle/wrapper/gradle-wrapper.jar
----

Generating the actual checksum of the Wrapper JAR on macOS:

[source,bash,subs=+attributes]
----
$ shasum --algorithm=256 gradle/wrapper/gradle-wrapper.jar
d81e0f23ade952b35e55333dd5f1821585e887c6d24305aeea2fbc8dad564b95 gradle/wrapper/gradle-wrapper.jar
----

        executer.inDirectory(file("second")).withTasks("wrapper").run()

        then: "the checksum should be constant (unless there are code changes)"
        Hashing.sha256().hashFile(file("first/gradle/wrapper/gradle-wrapper.jar")) == EXPECTED_WRAPPER_JAR_HASH

        and:
        file("first/gradle/wrapper/gradle-wrapper.jar").md5Hash == file("second/gradle/wrapper/gradle-wrapper.jar").md5Hash

public abstract class ModelType<T> {

    public static final ModelType<Object> UNTYPED = ModelType.of(Object.class);

    private final TypeWrapper wrapper;

    private ModelType(TypeWrapper wrapper) {
        this.wrapper = wrapper;
    }

    protected ModelType() {
        this.wrapper = wrap(new TypeToken<T>(getClass()) {
        }.getType());
    }

    public static <T> ModelType<T> of(Class<T> clazz) {