}
    }

    private String getSingular(String plural) {
        if (plural.endsWith("ies")) {
            return plural.substring(0, plural.length() - 3) + "y";
        }
        if (plural.endsWith("s")) {
            return plural.substring(0, plural.length() - 1);
        }
        return plural;
    }

    private void recordString(String path, String value) {
        pathStats

* «/// check»: «/// check | Testen»
* «/// danger»: «/// danger | Gefahr»
* «/// info»: «/// info | Info»

}

// TableName convert string to table name
func (ns NamingStrategy) TableName(str string) string {
	if ns.SingularTable {
		return ns.TablePrefix + ns.toDBName(str)
	}
	return ns.TablePrefix + inflection.Plural(ns.toDBName(str))
}

// SchemaName generate schema name from table name, don't guarantee it is the reverse value of TableName
func (ns NamingStrategy) SchemaName(table string) string {

* «the request body»: «le corps de la requête»
* «the response body»: «le corps de la réponse»

* «path operation»: «opération de chemin»
* «path operations» (plural): «opérations de chemin»
* «path operation function»: «fonction de chemin»
* «path operation decorator»: «décorateur d'opération de chemin»

* «path parameter»: «paramètre de chemin»

* OAuth2 Scopes: Scopes de OAuth2 (do not translate to "Alcances de OAuth2")
* on the fly: sobre la marcha (do not translate to "al vuelo")
* terminal: terminal (femenine, as in "la terminal")
* terminals: terminales (plural femenine, as in "las terminales")
* lifespan: lifespan (do not translate to "vida útil" or "tiempo de vida")
* unload: quitar de memoria (do not translate to "descargar")
* mount (noun): mount (do not translate to "montura")

	for i, testCase := range testCases {
		output := prepareUpdateMessage(testCase.dlURL, testCase.older)
		line1 := fmt.Sprintf("%s %s", plainMsg, color.YellowBold(testCase.expectedSubStr))
		line2 := fmt.Sprintf("Update: %s", color.CyanBold(testCase.dlURL))
		// Uncomment below to see message appearance:
		// fmt.Println(output)
		switch {
		case testCase.dlURL == "" && output != "":

designs the management of shared state is built into the system, TensorFlow enables developers to experiment with novel optimizations and training algorithms. TensorFlow supports a variety of applications, with a focus on training and inference on deep neural networks. Several Google services use TensorFlow in production, we have released it as an open-source project, and it has become widely used for machine learning research. In this paper, we describe the TensorFlow dataflow model and demonstrate the...

deploy ML-powered applications.

TensorFlow was originally developed by researchers and engineers working within
the Machine Intelligence team at Google Brain to conduct research in machine
learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.

TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)

* <abbr title="A group of machines that are configured to be connected and work together in some way.">cluster</abbr>
* <abbr title="A method of machine learning that uses artificial neural networks with numerous hidden layers between input and output layers, thereby developing a comprehensive internal structure">Deep Learning</abbr>

    are available in Linux x86, Windows x86, and Linux aarch64 packages.

    *   **Linux x86 packages:**
        *   oneDNN optimizations are *enabled by default* on CPUs with
            neural-network-focused hardware features such as AVX512_VNNI,
            AVX512_BF16, AMX, etc.
            ([Intel Cascade Lake](https://www.intel.com/content/www/us/en/products/platforms/details/cascade-lake.html)