"fried_egg":                            "\U0001f373",
	"fried_shrimp":                         "\U0001f364",
	"fries":                                "\U0001f35f",
	"frog":                                 "\U0001f438",
	"frowning":                             "\U0001f626",
	"frowning_face":                        "\u2639\ufe0f",
	"frowning_man":                         "\U0001f64d\u200d\u2642\ufe0f",
	"frowning_person":                      "\U0001f64d",

	clusterCollector = newMinioClusterCollector(allMetricsGroups)
	bucketCollector = newMinioBucketCollector(bucketMetricsGroups)
}

// MetricNamespace is top level grouping of metrics to create the metric name.
type MetricNamespace string

// MetricSubsystem is the sub grouping for metrics within a namespace.
type MetricSubsystem string

const (
	bucketMetricNamespace    MetricNamespace = "minio_bucket"

    More precisely, for every minimal unexplainable control dependency path
    we emit op warnings for all involved ops. The pass does not report
    intermediate dummy ops for grouping control dependencies (Identity, NoOp),
    unless they are part of an unexplainable path between other ops.
    This pass is useful to understand control dependency conservatism for a
    given MLIR module.

	}

	// If the pod originates from the kube-api, when we know that the kube-apiserver is responding and the kubelet's credentials are valid.
	// Knowing this, it is reasonable to wait until the service lister has synchronized at least once before attempting to build
	// a service env var map.  This doesn't present the race below from happening entirely, but it does prevent the "obvious"

}

// Dependencies is a bin for things we might consider "injected dependencies" -- objects constructed
// at runtime that are necessary for running the Kubelet. This is a temporary solution for grouping
// these objects while we figure out a more comprehensive dependency injection story for the Kubelet.
type Dependencies struct {
	Options []Option

	// Injected Dependencies

            to generate the reports on the Maven-generated site.
            These reports will be run when a user executes {@code mvn site}.
            All the reports will be included in the navigation bar for browsing.
          </description>
          <association>
            <type>Reporting</type>
          </association>
        </field>
      </fields>
    </class>
    <class>

github.com/xeipuuv/gojsonschema v1.2.0 h1:LhYJRs+L4fBtjZUfuSZIKGeVu0QRy8e5Xi7D17UxZ74=
github.com/xeipuuv/gojsonschema v1.2.0/go.mod h1:anYRn/JVcOK2ZgGU+IjEV4nwlhoK5sQluxsYJ78Id3Y=
github.com/xiang90/probing v0.0.0-20190116061207-43a291ad63a2/go.mod h1:UETIi67q53MR2AWcXfiuqkDkRtnGDLqkBTpCHuJHxtU=
github.com/xlab/treeprint v1.2.0 h1:HzHnuAF1plUN2zGlAFHbSQP2qJ0ZAD3XF5XD7OesXRQ=

  // Verify that the result stays uchanged
  // CHECK: return %arg0 : tensor<*xf32>
  func.return %0#0 : tensor<*xf32>
}

// Unused value flowing through the while (operand 2 and 3, is unused in the
// while and the corresponding result is unused as well). Canonicalization will
// eliminate them.
// CHECK-LABEL: testWhileRegionUnusedValue

  let description = [{
    Splits the `value` tensor along `split_dim` into a number of sub-tensors
    with same shape as the original one, except for `split_dim`. The grouping
    of the resultant sub-tensors is decided by `size-splits`. Same as tf.SplitV.
  }];

  let arguments = (ins
    TFL_TensorOf<[F32, I16, I32, I64, I8, UI8, QI8, QUI8, QI16]>:$value,

    shape_inference::InferenceContext* shape_context =
        shape_refiner_->GetContext(&node);
    return shape_ic(shape_context);
  }

  // Treat TensorList init ops specially here as the op requires knowing its
  // element dtype.
  // TODO(jpienaar): Reconsider post refactoring shape functions.
  if (node.type_string() == "TensorListReserve" ||
      node.type_string() == "EmptyTensorList") {
    mlir::Type etype;