addFinish() {
        const finish = this.generateFinish()
        this.container.appendChild(finish)
    }

    /**
     * Animate a typed line.
     * @param {Node} line - The line element to render.
     */
    async type(line) {
        const chars = [...line.textContent];
        line.textContent = '';
        this.container.appendChild(line);

        for (let char of chars) {

        assertArrayEquals(result1, result2);
    }

    @Test
    void testHMACT64WithKnownTestVector() throws NoSuchAlgorithmException {
        // Test with known test vector
        // Using test vector from RFC 2104 adapted for HMACT64
        byte[] key = new byte[16];
        Arrays.fill(key, (byte) 0x0b);
        byte[] data = "Hi There".getBytes();

        bindings.put("priorVersions", priorVersions);
        bindings.put("notableHighlights", notableHighlights);
        bindings.put("nonNotableHighlights", nonNotableHighlights);

        return TemplateUtils.render(template, bindings);
    }

// that defines two inputs, "concat_dim" and "values" (in that order).
// You must use TF_AddInput() for the first input (since it takes a
// single tensor), and TF_AddInputList() for the second input (since
// it takes a list, even if you were to pass a list with a single
// tensor), as in:
//   TF_OperationDescription* desc = TF_NewOperation(graph, "Concat", "c");
//   TF_Output concat_dim_input = {...};

{% for repo in topic_repos %}

<a href={{repo.html_url}} target="_blank">★ {{repo.stars}} - {{repo.name}}</a> by <a href={{repo.owner_html_url}} target="_blank">@{{repo.owner_login}}</a>.

    }

    @Test
    public void test_user_title() {
        final User user = new User();
        assertNull(user.getTitle());

        user.setTitle("Senior Engineer");
        assertEquals("Senior Engineer", user.getTitle());
    }

    @Test
    public void test_user_postalCode() {
        final User user = new User();
        assertNull(user.getPostalCode());

        bindings.put("nextMajor", (version.getMajor() + 1) + ".0");
        bindings.put("version", version);

        return TemplateUtils.render(template, bindings);
    }

*  `tf.Tensor`

    mock_dumps.assert_not_called()


def test_explicit_response_class_uses_json_dumps():
    """When response_class is explicitly set to JSONResponse, the normal path
    is used and json.dumps is called via JSONResponse.render()."""
    with patch(
        "starlette.responses.json.dumps", wraps=__import__("json").dumps
    ) as mock_dumps:
        response = client.get("/explicit")
    assert response.status_code == 200

     * the result.
     *
     * @param template a Groovy template
     * @param bindings parameters for the template
     * @return the rendered template
     */
    public static String render(String template, Map<String, Object> bindings) throws IOException {
        final StringWriter writer = new StringWriter();

        try {
            final SimpleTemplateEngine engine = new SimpleTemplateEngine();