*
     * @param writer the print writer to write the event to
     * @param event the event name
     * @param data the event data to serialize as JSON
     */
    protected void sendSseEvent(final PrintWriter writer, final String event, final Map<String, Object> data) {
        try {
            writer.write("event: " + event + "\n");

	Read(p []byte) (n int, err error)
	Close() error
}

type Writer interface {
	Write(p []byte) (n int, err error)
	Close() error
}

// ReadWriter's methods are Read, Write, and Close.
type ReadWriter interface {
	Reader  // includes methods of Reader in ReadWriter's method set
	Writer  // includes methods of Writer in ReadWriter's method set
}
</pre>

<p>

     * A queue of elements currently in the map, ordered by write time. Elements are added to the
     * tail of the queue on write.
     */
    @GuardedBy("this")
    final Queue<ReferenceEntry<K, V>> writeQueue;

    /**
     * A queue of elements currently in the map, ordered by access time. Elements are added to the
     * tail of the queue on access (note that writes count as accesses).
     */
    @GuardedBy("this")

     * A queue of elements currently in the map, ordered by write time. Elements are added to the
     * tail of the queue on write.
     */
    @GuardedBy("this")
    final Queue<ReferenceEntry<K, V>> writeQueue;

    /**
     * A queue of elements currently in the map, ordered by access time. Elements are added to the
     * tail of the queue on access (note that writes count as accesses).
     */
    @GuardedBy("this")

`tensorflow` pip package has a new, optional installation method for Linux that installs necessary Nvidia CUDA libraries through pip. As long as the Nvidia driver is already installed on the system, you may now run `pip install tensorflow[and-cuda]` to install TensorFlow's Nvidia CUDA library dependencies in the Python environment. Aside from the Nvidia driver, no other pre-existing Nvidia CUDA packages are necessary.

*   Enable JIT-compiled i64-indexed kernels on GPU for large tensors with more...

constraints.DecimalMin.message = {item} moet groter zijn dan {value}.
constraints.Digits.message = {item} moet een getal zijn. (Verwacht: <getal>.<getal>)
constraints.Future.message = {item} moet een toekomstige waarde zijn.
constraints.Max.message = {item} moet kleiner of gelijk zijn aan {value}.
constraints.Min.message = {item} moet groter of gelijk zijn aan {value}.
constraints.NotNull.message = {item} is niet ingevuld.

errors.invalid_query_unsupported_sort_field = Le tri spécifié {0} n'est pas pris en charge.
errors.invalid_query_unsupported_sort_order = L'ordre de tri spécifié {0} n'est pas pris en charge.
errors.invalid_query_cannot_process=Impossible de traiter la requête spécifiée.
errors.crud_invalid_mode = Le mode est incorrect. (pas {0}, mais {1})
errors.crud_failed_to_create_instance = Échec de la création de nouvelles données.

common:rbe_linux_cuda --config=cuda_clang_official
common:rbe_linux_cuda --config=rbe_linux_cpu
# For Remote build execution -- GPU configuration
common:rbe_linux_cuda --repo_env=REMOTE_GPU_TESTING=1
# Update UMD version when RBE CUDA driver is updated.
common:rbe_linux_cuda --repo_env=HERMETIC_CUDA_UMD_VERSION="13.0.2"

common:rbe_linux_cuda_nvcc --config=rbe_linux_cuda
common:rbe_linux_cuda_nvcc --config=cuda_nvcc