* worker processes: worker processes (do not translate to "procesos trabajadores" or "procesos de trabajo")
* worker: worker (do not translate to "trabajador")
* load balancer: load balancer (do not translate to "balanceador de carga")
* load balance: load balance (do not translate to "balancear carga")

You could load it at the top level of the module/file, but that would also mean that it would **load the model** even if you are just running a simple automated test, then that test would be **slow** because it would have to wait for the model to load before being able to run an independent part of the code.

TF_CAPI_EXPORT extern TF_Library* TF_LoadPluggableDeviceLibrary(
    const char* library_filename, TF_Status* status);

// Frees the memory associated with the library handle.
// Does NOT unload the library.
TF_CAPI_EXPORT extern void TF_DeletePluggableDeviceLibraryHandle(
    TF_Library* lib_handle);

// Removes `func_name` from `g`. If `func_name` is not in `g`, an error will be
// returned.

ange","touchstart","touchmove","touchend","touchcancel","pointerdown","pointermove","pointerup","pointerleave","pointercancel","gesturestart","gesturechange","gestureend","focus","blur","change","reset","select","submit","focusin","focusout","load","unload","beforeunload","resize","move","DOMContentLoaded","readystatechange","error","abort","scroll"]);function O(t,e){return e&&`${e}::${k++}`||t.uidEvent||k++}function I(t){const e=O(t);return t.uidEvent=e,T[e]=T[e]||{},T[e]}function D(t,e,s=null){return...

// --------------------------------------------------------------------------
// Load plugins containing custom ops and kernels

// TF_Library holds information about dynamically loaded TensorFlow plugins.
typedef struct TF_Library TF_Library;

// Load the library specified by library_filename and register the ops and
// kernels present in that library.
//

DOWNLOADS="$(mktemp -d)"
mkdir -p "$DOWNLOADS"
gsutil -m rsync -r "$TFCI_ARTIFACT_STAGING_GCS_URI" "$DOWNLOADS"
ls "$DOWNLOADS"

# Upload all build artifacts to e.g. gs://tensorflow/versions/2.16.0-rc1 (releases) or
# gs://tensorflow/nightly/2.16.0-dev20240105 (nightly), overwriting previous values.
if [[ "$TFCI_ARTIFACT_FINAL_GCS_ENABLE" == 1 ]]; then

st"),e)r.setRequestHeader(n,e[n]);o=function(e){return function(){o&&(o=a=r.onload=r.onerror=r.onabort=r.ontimeout=r.onreadystatechange=null,"abort"===e?r.abort():"error"===e?"number"!=typeof r.status?t(0,"error"):t(r.status,r.statusText):t(Yt[r.status]||r.status,r.statusText,"text"!==(r.responseType||"text")||"string"!=typeof r.responseText?{binary:r.response}:{text:r.responseText},r.getAllResponseHeaders()))}},r.onload=o(),a=r.onerror=r.ontimeout=o("error"),void 0!==r.onabort?r.onabort=a:r.onr...

st"),e)r.setRequestHeader(n,e[n]);o=function(e){return function(){o&&(o=a=r.onload=r.onerror=r.onabort=r.ontimeout=r.onreadystatechange=null,"abort"===e?r.abort():"error"===e?"number"!=typeof r.status?t(0,"error"):t(r.status,r.statusText):t(Yt[r.status]||r.status,r.statusText,"text"!==(r.responseType||"text")||"string"!=typeof r.responseText?{binary:r.response}:{text:r.responseText},r.getAllResponseHeaders()))}},r.onload=o(),a=r.onerror=r.ontimeout=o("error"),void 0!==r.onabort?r.onabort=a:r.onr...

	if uploadIDMarker != "" {
		for uploadIndex < len(uploads) {
			if uploads[uploadIndex].UploadID != uploadIDMarker {
				uploadIndex++
				continue
			}
			if uploads[uploadIndex].UploadID == uploadIDMarker {
				uploadIndex++
				break
			}
			uploadIndex++
		}
	}
	for uploadIndex < len(uploads) {
		result.Uploads = append(result.Uploads, uploads[uploadIndex])

	defer globalAuthPluginMutex.Unlock()
	return globalAuthNPlugin
}

func newGlobalAuthZPluginFn() *polplugin.AuthZPlugin {
	globalAuthPluginMutex.Lock()
	defer globalAuthPluginMutex.Unlock()
	return globalAuthZPlugin
}

func setGlobalAuthNPlugin(authn *idplugin.AuthNPlugin) {
	globalAuthPluginMutex.Lock()
	globalAuthNPlugin = authn
	globalAuthPluginMutex.Unlock()
}