KindFloat64Histogram
)

// Value represents a metric value returned by the runtime.
type Value struct {
	kind    ValueKind
	scalar  uint64         // contains scalar values for scalar Kinds.
	pointer unsafe.Pointer // contains non-scalar values.
}

// Kind returns the tag representing the kind of value this is.
func (v Value) Kind() ValueKind {
	return v.kind
}

}

// normalizeScalar brings the scalar within the byte size of the order of the
// curve, as expected by the nistec scalar multiplication functions.
func (curve *nistCurve[Point]) normalizeScalar(scalar []byte) []byte {
	byteSize := (curve.params.N.BitLen() + 7) / 8
	if len(scalar) == byteSize {
		return scalar
	}
	s := new(big.Int).SetBytes(scalar)
	if len(scalar) > byteSize {
		s.Mod(s, curve.params.N)
	}

	stopCh := make(chan struct{})

	canary := Chain("MONITOR-TEST-CANARY")
	tables := []Table{TableMangle, TableFilter, TableNAT}
	go ipt.Monitor(canary, tables, func() {
		if !ensureNoChains(mfe) {
			t.Errorf("reload called while canaries still exist")
		}
		atomic.AddUint32(&reloads, 1)
	}, 100*time.Millisecond, stopCh)

	// Monitor should create canary chains quickly

        failure.assertHasCause("""A model element of type: 'Container' can not be constructed.
Its property 'java.util.$type<Thing> items' is not a valid scalar collection
A scalar collection can not contain 'Thing's
A valid scalar collection takes the form of List<T> or Set<T> where 'T' is one of (String, Boolean, Character, Byte, Short, Integer, Float, Long, Double, BigInteger, BigDecimal, File)""")

        where:

    ConvertToTensorShapeProto(tensor_type.getShape(), &tensor_shape_proto);
    return PartialTensorShape(tensor_shape_proto);
  }

  // If type is not a RankedTensor or UnrankedTensor, it must be a scalar.
  // Empty TensorShape indicates a scalar.
  return TensorShape();
}

mlir::TF::ShapeAttr ConvertTypeToTensorShapeAttr(const mlir::Type& type) {
  if (mlir::isa<mlir::UnrankedTensorType>(type)) {

      t.scalar<tensorflow::ResourceHandle>()().set_name("var1");
      t.scalar<tensorflow::ResourceHandle>()().set_device(kDeviceName);

      outputs->push_back(t);
    } else if (output_name == "var2") {
      Tensor t = Tensor(tensorflow::DT_RESOURCE, tensorflow::TensorShape({1}));
      t.scalar<tensorflow::ResourceHandle>()().set_name("var2");

    deps = [
        ":iostream",
        ":none",
        ":scalars",
        ":string",
        ":tensor_spec",
        "//tensorflow/core:framework",
        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
    ],
)

cc_library(
    name = "scalars",
    hdrs = [
        "scalars.h",
    ],
)

tf_cc_test(
    name = "scalars_test",

    name: server
---
# Control plane pod proving the existence of istio.io/rev 'canary'
apiVersion: v1
kind: Pod
metadata:
  name: istiod-canary-1234567890-12345
  namespace: istio-system
  labels:
    app: istiod
    istio: pilot
    istio.io/rev: canary
spec:
  containers:
  - image: gcr.io/google-samples/microservices-demo/adservice:v0.1.1
    name: server
---

    .Attr("max_percentile: float = 0.0")
    .SetShapeFn([](::tensorflow::shape_inference::InferenceContext* c) {
      c->set_output(0, c->input(0));
      c->set_output(1, c->Scalar());
      c->set_output(2, c->Scalar());

      const tensorflow::AttrValue* num_bins_attr;
      TF_RETURN_IF_ERROR(c->GetAttr("num_bins", &num_bins_attr));
      c->set_output(3, c->MakeShape({num_bins_attr->i()}));

cond: A Tensor. If the tensor is a scalar of non-boolean type, the
    scalar is converted to a boolean according to the
    following rule: if the scalar is a numerical value, non-zero means
    True and zero means False; if the scalar is a string, non-empty
    means True and empty means False. If the tensor is not a scalar,
    being empty means False and being non-empty means True.