* code verbose. Whenever following this advice, you should check whether {@code Stream} could be
 * adopted more comprehensively in your code; the end result may be quite a bit simpler.
 *
 * <h3>See also</h3>
 *
 * <p>See the Guava User Guide article on <a href=
 * "https://github.com/google/guava/wiki/OrderingExplained">{@code Ordering}</a>.
 *
 * @author Jesse Wilson

fff}.pace-center-radar-primary .pace .pace-activity{border-color:#007bff transparent transparent}.pace-center-radar-primary .pace .pace-activity::before{border-color:#007bff transparent transparent}.pace-center-simple-primary .pace{background:#fff;border-color:#007bff}.pace-center-simple-primary .pace .pace-progress{background:#007bff}.pace-material-primary .pace{color:#007bff}.pace-corner-indicator-primary .pace .pace-activity{background:#007bff}.pace-corner-indicator-primary .pace .pace-activi...

.pace .pace-activity {\n  border-color: #007bff transparent transparent;\n}\n\n.pace-center-radar-primary .pace .pace-activity::before {\n  border-color: #007bff transparent transparent;\n}\n\n.pace-center-simple-primary .pace {\n  background: #fff;\n  border-color: #007bff;\n}\n\n.pace-center-simple-primary .pace .pace-progress {\n  background: #007bff;\n}\n\n.pace-material-primary .pace {\n  color: #007bff;\n}\n\n.pace-corner-indicator-primary .pace .pace-activity {\n  background: #007bff;\n}\n\n....

she would keep, through all her riper years, the simple and
loving heart of her childhood:  and how she would gather about
her other little children, and make THEIR eyes bright and eager
with many a strange tale, perhaps even with the dream of
Wonderland of long ago:  and how she would feel with all their
simple sorrows, and find a pleasure in all their simple joys,
remembering her own child-life, and the happy summer days.

But you can also exploit the benefits of parallelism and multiprocessing (having multiple processes running in parallel) for **CPU bound** workloads like those in Machine Learning systems.

That, plus the simple fact that Python is the main language for **Data Science**, Machine Learning and especially Deep Learning, make FastAPI a very good match for Data Science / Machine Learning web APIs and applications (among many others).

}

// Set server_def on the context, possibly updating it.
// TODO(b/291142876) Simplify TFE_ContextSetServerDefWithTimeoutAndRetries and
// TFE_ContextUpdateServerDefWithTimeout to be simple wrappers around the same
// C++ function.
// Retries are used for CreateContext calls, which is used in
// ParameterServerStrategy initialization to be robust to worker preemption.

    }

    @Test
    @DisplayName("Should handle concurrent encryption operations safely")
    void testConcurrentEncryption() throws Exception {
        // Given - Test a simpler concurrent scenario first
        Smb2EncryptionContext context = new Smb2EncryptionContext(EncryptionNegotiateContext.CIPHER_AES128_GCM, DialectVersion.SMB311,
                testEncryptionKey, testEncryptionKey);

   * between elements will be made, but the order in which those pairs of elements are passed to the
   * consumer is <i>not</i> defined.
   *
   * <p>Note that many usages of this method can be replaced with simpler calls to {@link #zip}.
   * This method behaves equivalently to {@linkplain #zip zipping} the stream elements into
   * temporary pair objects and then using {@link Stream#forEach} on that stream.
   *

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</p>

<p>
Don't be clever.
</p>

<h3 id="overview">Informal Overview</h3>

<p>
Go approaches its memory model in much the same way as the rest of the language,
aiming to keep the semantics simple, understandable, and useful.
This section gives a general overview of the approach and should suffice for most programmers.
The memory model is specified more formally in the next section.
</p>

<p>