func tgs(x, y []string) []pair {
	// Count the number of times each string appears in a and b.
	// We only care about 0, 1, many, counted as 0, -1, -2
	// for the x side and 0, -4, -8 for the y side.
	// Using negative numbers now lets us distinguish positive line numbers later.
	m := make(map[string]int)
	for _, s := range x {
		if c := m[s]; c > -2 {
			m[s] = c - 1
		}
	}
	for _, s := range y {
		if c := m[s]; c > -8 {

func (h *Hash) Write(b []byte) (int, error) {
	size := len(b)
	// Deal with bytes left over in h.buf.
	// h.n <= bufSize is always true.
	// Checking it is ~free and it lets the compiler eliminate a bounds check.
	if h.n > 0 && h.n <= bufSize {
		k := copy(h.buf[h.n:], b)
		h.n += k
		if h.n < bufSize {
			// Copied the entirety of b to h.buf.
			return size, nil
		}

In this case, also `jackson-annotation:2.9.5` will be taken, as that is how we defined our local virtual platform.

For both published and virtual platforms, Gradle lets you override the version choice of the platform itself by specifying an _enforced_ dependency on the platform:

.Forceful platform downgrade
====

  }

  /**
   * Creates the permissions normally used for Windows filesystems, looking up the user afresh, even
   * if previous calls have initialized the {@code PermissionSupplier} fields.
   *
   * <p>This lets us test the effects of different values of the {@code user.name} system property
   * without needing a separate VM or classloader.
   */
  @IgnoreJRERequirement // used only when Path is available (and only from tests)

	n := uintptr(CTL_MAXNAME) * siz

	p := (*byte)(unsafe.Pointer(&buf[0]))
	bytes, err := ByteSliceFromString(name)
	if err != nil {
		return nil, err
	}

	// Magic sysctl: "setting" 0.3 to a string name
	// lets you read back the array of integers form.
	if err = sysctl([]_C_int{0, 3}, p, &n, &bytes[0], uintptr(len(name))); err != nil {
		return nil, err
	}
	return buf[0 : n/siz], nil
}

vulnerabilities.

## Security properties of execution modes

TensorFlow has several execution modes, with Eager-mode being the default in v2.
Eager mode lets users write imperative-style statements that can be easily
inspected and debugged and it is intended to be used during the development
phase.

As part of the differences that make Eager mode easier to debug, the [shape

[tools](https://www.tensorflow.org/resources/tools),
[libraries](https://www.tensorflow.org/resources/libraries-extensions), and
[community](https://www.tensorflow.org/community) resources that lets
researchers push the state-of-the-art in ML and developers easily build and
deploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working within

----
plugins {
    id 'java'                          // core plugin, no version required
    id 'org.some.plugin' version '2.8' // community plugin, version required
}
----
=====

The repositories section lets Gradle know where to pull dependencies from:

[.multi-language-sample]
=====
[source, kotlin]
----
repositories {
    mavenCentral()  // get dependencies from the Maven central repository
}
----

		}
	}
}

func (rc *reconciler) waitForVolumeAttach(volumeToMount cache.VolumeToMount) {
	logger := klog.TODO()
	if rc.controllerAttachDetachEnabled || !volumeToMount.PluginIsAttachable {
		//// lets not spin a goroutine and unnecessarily trigger exponential backoff if this happens
		if volumeToMount.PluginIsAttachable && !volumeToMount.ReportedInUse {

    mainClass = 'running.tutorial.groovy.App'
}

tasks.named('test') {
    // Use JUnit Platform for unit tests.
    useJUnitPlatform()
}
----
=====

This build script lets Gradle know which dependencies and plugins the `app` subproject is using and where to find them.
We will look at this in more detail in the following sections.

[.text-right]