// Create 2 resources and initialize them with dummy values.
  TF_CHECK_OK(device->resource_manager()->Create(
      container, "var1", new tensorflow::Var(tensorflow::DataType::DT_FLOAT)));
  TF_CHECK_OK(device->resource_manager()->Create(
      container, "var2", new tensorflow::Var(tensorflow::DataType::DT_FLOAT)));
}

Status FakeSession::Create(const tensorflow::GraphDef& graph) {

        compile {
            attributes.attribute(buildType, 'debug')
            outgoing {
                variants {
                    var1 {
                        artifact oneJar
                        attributes.attribute(flavor, 'one')
                    }
                    var2 {
                        artifact twoJar
                        attributes.attribute(flavor, 'two')
                    }
                }

        '''
        file('src/main/java/org/gradle/test/Main.java') << '''
        package org.gradle.test;

        class Main {
            public static void main(String[] args) {
                if (!"value1".equals(System.getProperty("var1"))) {
                    throw new RuntimeException("Expected system property not specified (var1)");
                }

TEST_F(PjRtExecutionUtilTest, PreparePjRtExecutableArgumentsVariableInputs) {
  std::vector<VariableInfo> variables;
  Var* var1 = CreateVariable<int32>("v1", TensorShape({1, 2}), {1, 2});
  variables.emplace_back(3, "v1", var1);
  Var* var2 = CreateVariable<int32>("v2", TensorShape({1, 2}), {3, 4});
  variables.emplace_back(4, "v2", var2);

  std::vector<const Tensor*> inputs;

        compile {
            outgoing {
                variants {
                    var1 {
                        artifact file('a1.jar')
                        attributes.attribute(buildType, 'profile')
                        attributes.attribute(flavor, 'bland')
                    }
                    var2 {
                        artifact file('a2.jar')

    loop body inine):

    ```mlir
      %var0 = ...
      %var1 = ...
      tf.while (..., %var0, %var1) {
        tf_device.replicate ([%var0, %var1] as %rvar) {
          %compile:2 = "tf._TPUCompileMlir"()
          tf.TPUExecuteAndUpdateVariablesOp(%rvar, compile#1)
        }
      }
    ```

    This pass will transform it into

    ```mlir
      %var0 = ...
      %var1 = ...
      %state_var0 = ...

func.func @init() attributes {tf_saved_model.exported_names = ["__tf_saved_model_session_initializer_init"]} {
  %var0 = "tf.VarHandleOp"() {container = "", shared_name = "var0"} : () -> tensor<!tf_type.resource<tensor<i1>>>
  %cond = "tf.ReadVariableOp"(%var0) {device = "/CPU:0"} : (tensor<!tf_type.resource<tensor<i1>>>) -> tensor<i1>

                id("base")
            }

            task jar1(type: Jar) {}
            task jar2(type: Jar) {}

            configurations {
                named("default") {
                    outgoing.artifact(tasks.jar1)
                }
                archives {
                    outgoing.artifact(tasks.jar2)
                }
            }
        """

        expect:

		"foo": sets.New[string]("dev-foo1", "dev-foo2", "dev-foo3"),
		"bar": sets.New[string]("dev-bar1", "dev-bar2", "dev-bar3"),
		"baz": sets.New[string]("dev-baz1", "dev-baz2", "dev-baz3"),
	}
	resp = devs.Filter(cond)

    def "creates manifest classpath with relative urls"() {
        when:
        def classpathFiles = [tmpDir.file('mydir/jar1.jar'), tmpDir.file('mydir/nested/jar2.jar')]

        then:
        ManifestUtil.createManifestClasspath(jarFile, classpathFiles) == "jar1.jar nested/jar2.jar";
    }

    def "creates manifest classpath with absolute urls"() {
        when:
        def tmpDirPath = tmpDir.testDirectory.toURI().rawPath