* 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")
* self hosting: self hosting (do not translate to "auto alojamiento")

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.

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

			int64(len("initial-value")), "", ""), ObjectOptions{})
	if err != nil {
		t.Fatal(err)
	}

	// Start a multipart upload WITHOUT conditional checks (this should work)
	res, err := obj.NewMultipartUpload(ctx, bucket, object, ObjectOptions{})
	if err != nil {
		t.Fatal(err)
	}

	// Upload a part
	partData := bytes.Repeat([]byte("a"), 5*humanize.MiByte)
	md5Hex := getMD5Hash(partData)

## How to enable Fan-Out Uploads ?

          retention-days: 5

      # Upload the results to GitHub's code scanning dashboard (optional).
      # Commenting out will disable upload of results to your repo's Code Scanning dashboard
      - name: "Upload to code-scanning"
        uses: github/codeql-action/upload-sarif@fe4161a26a8629af62121b670040955b330f9af2 # v3.29.5
        with:

You can also use `File()` with `UploadFile`, for example, to set additional metadata:

{* ../../docs_src/request_files/tutorial001_03_an_py39.py hl[9,15] *}

## Multiple File Uploads { #multiple-file-uploads }

It's possible to upload several files at the same time.

They would be associated to the same "form field" sent using "form data".

To use that, declare a list of `bytes` or `UploadFile`:

Você também pode usar `File()` com `UploadFile`, por exemplo, para definir metadados adicionais:

{* ../../docs_src/request_files/tutorial001_03_an_py39.py hl[9,15] *}

## Uploads de Múltiplos Arquivos { #multiple-file-uploads }

É possível realizar o upload de vários arquivos ao mesmo tempo.

Eles serão associados ao mesmo "campo de formulário" enviado usando "dados de formulário".

          #     of the value entered here.
          publish_results: true

      # Upload the results as artifacts (optional). Commenting out will disable uploads of run results in SARIF
      # format to the repository Actions tab.
      - name: "Upload artifact"
        uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4 # v5.0.0
        with:
          name: SARIF file

					if asyncErr == nil {
						asyncErr = err
					}
					asyncErrMu.Unlock()
				}
			}(name, header.FileInfo(), b)
			continue
		}

		// If zero or earlier modtime, set to current.
		// Otherwise the resulting objects will be invalid.
		if header.ModTime.UnixNano() <= 0 {
			header.ModTime = time.Now()
		}

		// Sync upload.
		rc := disconnectReader{r: tarReader}