</p>


<h2 id="Types">Types</h2>

<p>
A type determines a set of values together with operations and methods specific
to those values. A type may be denoted by a <i>type name</i>, if it has one,
or specified using a <i>type literal</i>, which composes a type from existing types.
</p>

<pre class="ebnf">
Type      = TypeName | TypeLit | "(" Type ")" .

  return std::equal(i1, e1, i2);
}

// This function removes explicit broadcasting on type1 and returns whether if
// the reduced `type1` dimensions are the same as the ending dimensions
// of `type2`.
bool IsReducedTailOfShape(Type type1, Type type2) {
  auto tail_type = mlir::dyn_cast<ShapedType>(type1);
  auto full_type = mlir::dyn_cast<ShapedType>(type2);
  if (!tail_type || !full_type || !tail_type.hasRank() || !full_type.hasRank())

      ('use_constant_with_int32_input', dtypes.int32, False, True),
      ('use_variable_with_int32_input', dtypes.int32, True, True),
      ('use_constant_with_int64_input', dtypes.int64, False, True),
      ('use_variable_with_int64_input', dtypes.int64, True, True),
      ('small_gather_use_constant', dtypes.int32, False, False),
      ('small_gather_use_variable', dtypes.int32, True, False),
  )
  @test_util.run_v2_only

Attribute ConstFoldBinaryOp(
    Type result_type, ArrayRef<Attribute> operands,
    llvm::function_ref<APFloat(APFloat, APFloat)> float_calculate,
    llvm::function_ref<APInt(APInt, APInt)> int_calculate) {
  // Note: All types are wrapped in tensor types in TFlite. E.g., f32 is
  // represented as tensor<f32>. So we are only handling tensor types here.
  auto type = result_type.dyn_cast<ShapedType>();
  if (!type) return {};

	if expect, actual := []types.UID(nil), kubelet.podWorkers.(*fakePodWorkers).triggeredDeletion; !reflect.DeepEqual(expect, actual) {
		t.Fatalf("expected %v kills, got %v", expect, actual)
	}

	ready = true
	kubelet.HandlePodRemoves(pods)
	time.Sleep(2 * time.Second)

	// Sources are ready. Remove unwanted pods.

						Succeeded: func() []types.UID {
							uids := make([]types.UID, 499)
							for i := range uids {
								uids[i] = types.UID(strconv.Itoa(i))
							}
							return uids
						}(),
						Failed: []types.UID{"b"},
					},
					Failed: 1,
				},
				{
					UncountedTerminatedPods: &batch.UncountedTerminatedPods{
						Failed: []types.UID{"b"},
					},
					Succeeded: 499,

                    Attribute value) {
  // Handle the case where the type and value are already tensors.
  if (mlir::isa<TensorType>(type) && mlir::isa<ElementsAttr>(value)) {
    result.addTypes(type);
    result.addAttribute("value", value);
    return;
  }

  // Otherwise, default to the attribute builder.
  ConstOp::build(builder, result, value);

        "node": ">=12"
      }
    },
    "node_modules/@types/json-schema": {
      "version": "7.0.11",
      "resolved": "https://registry.npmjs.org/@types/json-schema/-/json-schema-7.0.11.tgz",
      "integrity": "sha512-wOuvG1SN4Us4rez+tylwwwCV1psiNVOkJeM3AUWUNWg/jDQY2+HE/444y5gc+jBmRqASOm2Oeh5c1axHobwRKQ==",
      "dev": true
    },
    "node_modules/@types/minimist": {
      "version": "1.2.2",

        VLOG(1) << "[potentially conservative] Op type `" << node.type_string()
                << "` is stateful but effects not modelled";
      } else {
        // See if any resource type is used.
        bool resource = false;
        std::function<bool(mlir::Type)> record_resource;
        record_resource = [&](mlir::Type type) {
          type.walk([&](mlir::Type t) {

	"k8s.io/kubernetes/pkg/kubelet/lifecycle"
	kubelettypes "k8s.io/kubernetes/pkg/kubelet/types"
	testingclock "k8s.io/utils/clock/testing"
	"k8s.io/utils/ptr"
)

const (
	lowPriority     = -1
	defaultPriority = 0
	highPriority    = 1
)

// mockPodKiller is used to testing which pod is killed
type mockPodKiller struct {
	pod                 *v1.Pod
	evict               bool