second intervals between attempts $MC_COMMAND ; STATUS=$? ; done ; set -e ; # reset `e` as active return 0 } # runCommand ($@) # Run custom mc command runCommand() { ${MC} "$@" return $? } # Try connecting to MinIO instance {{- if .Values.tls.enabled }} scheme=https {{- else }} scheme=http {{- end }} connectToMinio $scheme {{ if .Values.customCommands }} # Run custom commands {{- range .Values.customCommands }} runCommand {{ .command }} {{- end }} {{- end }} minio/templates/_helper_policy.tpl {{-...

second intervals between attempts $MC_COMMAND ; STATUS=$? ; done ; set -e ; # reset `e` as active return 0 } # runCommand ($@) # Run custom mc command runCommand() { ${MC} "$@" return $? } # Try connecting to MinIO instance {{- if .Values.tls.enabled }} scheme=https {{- else }} scheme=http {{- end }} connectToMinio $scheme {{ if .Values.customCommands }} # Run custom commands {{- range .Values.customCommands }} runCommand {{ .command }} {{- end }} {{- end }} minio/templates/_helper_policy.tpl {{-...

						References: []Reference{
							{ForeignKey: "OwnerType", ForeignSchema: "Toy", PrimaryValue: "users"},
						},
					},
				},
			},
		})
	})

	t.Run("has one with custom polymorphic type and id", func(t *testing.T) {
		type Toy struct {
			ID    int
			Name  string
			RefId int
			Type  string
		}

		type Cat struct {
			ID   int
			Name string

 different computation approaches and orders.
    *   To verify if oneDNN optimizations are on, look for a message with *"oneDNN custom operations are on"* in the log. If the exact phrase is not there, it means they are off.

* Making the `tf.function` type system fully available:

    * `tf.types.experimental.TraceType` now allows custom tf.function inputs to declare Tensor decomposition and type casting support.

		Path:      pathJoin(bucket, decodeDirObject(object)),
	}
	if opts != nil {
		tr.Custom = map[string]string{
			"dry":    fmt.Sprint(opts.DryRun),
			"remove": fmt.Sprint(opts.Remove),
			"mode":   fmt.Sprint(opts.ScanMode),
		}
		if result != nil {
			tr.Custom["version-id"] = result.VersionID
			tr.Custom["disks"] = strconv.Itoa(result.DiskCount)
			tr.Bytes = result.ObjectSize
		}
	}

  /*
   * Under Android, MyError propagates up and fails the test?
   *
   * TODO(b/218700094): Does this matter to prod users, or is it just a feature of our testing
   * environment? If the latter, maybe write a custom Executor that avoids failing the test when it
   * sees an Error?
   */
  @AndroidIncompatible
  public void testTaskThrowsError() throws Exception {
    class MyError extends Error {}

		# Get the original S3 object using the presigned URL
		r = requests.get(s3_url)
		original_object = r.content.decode('utf-8')

		# Transform all text in the original object to uppercase
		# You can replace it with your custom code based on your use case
		transformed_object = original_object.upper()

		# Write object back to S3 Object Lambda
		# response sends the transformed data
		# back to MinIO and then to the user

calculated over a time interval of 1 minute.
`,
		Example: `  # Retrieve workload metrics for productpage-v1 workload
  istioctl experimental metrics productpage-v1

  # Retrieve workload metrics for various services with custom duration
  istioctl experimental metrics productpage-v1 -d 2m

  # Retrieve workload metrics for various services in the different namespaces
  istioctl experimental metrics productpage-v1.foo reviews-v1.bar ratings-v1.baz`,

        }

        def acceptanceJson = new AcceptedApiChange(
            change.type,
            change.member,
            '[ADD YOUR CUSTOM REASON HERE]',
            change.changes
        )

        def changeId = (change.type + change.member).replaceAll('[^a-zA-Z0-9]', '_')
        Violation violation = Violation.error(
            member,

`autoscaling/v2alpha1`. The Horizontal Pod Autoscaler changes include support for status conditions, and autoscaling on memory and custom metrics.

* The metrics APIs, `custom-metrics.metrics.k8s.io` and `metrics`, were moved from `v1alpha1` to `v1beta1`, and renamed to `custom.metrics.k8s.io` and `metrics.k8s.io`, respectively. If you have deployed a custom metrics adapter, ensure that it supports the new API version. If you have deployed Heapster in aggregated API server mode, upgrade...