* depending on whether {@link #CLASSES} or {@link #MODULES} is present.
     *
     * @param moduleName name of the module on which to apply the path
     * @return an identification of the patch-module path for the given module.
     *
     * @see Modular#moduleName()
     */
    @Nonnull
    public static Modular patchModule(@Nonnull String moduleName) {
        return PATCH_MODULE.new Modular(moduleName);
    }

"""
Top-level module of TensorFlow. By convention, we refer to this module as
`tf` instead of `tensorflow`, following the common practice of importing
TensorFlow via the command `import tensorflow as tf`.

The primary function of this module is to import all of the public TensorFlow
interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

# Phase 4: copy root go.mod to staging dirs and rewrite

kube::log::status "go.mod: propagate to staging modules" >&11
for repo in $(kube::util::list_staging_repos); do
  (
    cd "staging/src/k8s.io/${repo}"

    echo "=== propagating to ${repo}"
    # copy root go.mod, changing module name
    sed "s#module k8s.io/kubernetes#module k8s.io/${repo}#" \
        < "${KUBE_ROOT}/go.mod" \

            check(Directives.WITH_RESOLVE_EXTENSION in moduleStructure.allDirectives) {
                "configureResolveExtensions() was called, but no modules specify WITH_RESOLVE_EXTENSION."
            }

            return TestModuleStructureImpl(
                moduleStructure.modules.map { it.transformAndRegisterResolveExtension() },
                moduleStructure.originalTestDataFiles,
            )
        }

}

// findModule searches for the module that contains the package at path.
// If the package was loaded, its containing module and true are returned.
// Otherwise, module.Version{} and false are returned.
func findModule(ld *loader, path string) (module.Version, bool) {
	if pkg, ok := ld.pkgCache.Get(path); ok {
		return pkg.mod, pkg.mod != module.Version{}
	}
	return module.Version{}, false
}

  }

  mlir::LogicalResult Run() {
    mlir::OwningOpRef<mlir::ModuleOp> module_before = module_->clone();
    LogicalResult run_result = pm_->run(module_.get());

    EXPECT_TRUE(ModulesEqual(*module_before, *module_));
    return run_result;
  }

 private:
  mlir::MLIRContext context_;
  mlir::OwningOpRef<ModuleOp> module_;
  std::unique_ptr<mlir::PassManager> pm_;
};

## Composition by architecture modules

Each [architecture module and platform](platforms.md) can contribute code to any of the runtimes.
Not every module contributes to every runtime.

The core-runtime module defines each runtime:

- The target JVM for the runtime. Each runtime has its own JVM compatibility constraints.

/**
 * [KotlinAnchorModuleProvider] provides modules which contain dependencies of libraries.
 *
 * In the IJ monorepo, anchor modules are required for navigation from Kotlin compiler library sources to IJ platform sources. The Kotlin
 * compiler depends on the IJ platform, but this dependency is not represented as JARs in the monorepo, but rather by certain monorepo

")
if [[ -n "${outdated}" ]]; then
  echo "These modules are pinned to versions different than the minimal preferred version."
  echo "That means that without replace directives, a different version would be selected,"
  echo "which breaks consumers of our published modules."
  echo "1. Use hack/pin-dependency.sh to switch to the preferred version for each module"
  echo "2. Run hack/update-vendor.sh to rebuild the vendor directory"

        }

        void addChecksum(HttpModule module, String algo, String type = "jar", String ext = "jar", String origin = null, String reason = null) {
            def checksum = getChecksum(module, algo, type)
            doAddChecksum(module.group, module.module, module.version, type, ext, algo, checksum, origin, reason)
        }