// where (x/c) is performed using multiplication with magic constants.
// To rewrite x%c == 0 requires pattern matching the rewritten expression
// and checking that the division by the same constant wasn't already calculated.
// This check is made by counting uses of the magic constant multiplication.
// Note that if there were an intermediate opt pass, this rule could be applied

		},
	}

	for _, tt := range cases {
		t.Run(tt.name, func(t *testing.T) {
			opt := buildClusterOpts{
				mutable: newClusterWrapper(tt.cluster),
				port:    &model.Port{Port: 80},
			}
			addTelemetryMetadata(tt.cluster, opt.port, tt.service, tt.direction, tt.svcInsts)
			if opt.mutable.cluster != nil && !reflect.DeepEqual(opt.mutable.cluster.Metadata, tt.want) {

	klet.admitHandlers.AddPodAdmitHandler(lifecycle.NewPredicateAdmitHandler(klet.getNodeAnyWay, criticalPodAdmissionHandler, klet.containerManager.UpdatePluginResources))
	// apply functional Option's
	for _, opt := range kubeDeps.Options {
		opt(klet)
	}

	if sysruntime.GOOS == "linux" {
		// AppArmor is a Linux kernel security module and it does not support other operating systems.
		klet.appArmorValidator = apparmor.NewValidator()

// RUN: odml-to-stablehlo-opt --uniform-quantized-stablehlo-to-tfl \
// RUN:     --split-input-file --verify-diagnostics %s | FileCheck %s

// ============================================================================
// The following functions tests example quantization patterns outputted from
// JAX Quantizer. JAX Quantizer should output integer types, which are
// composed into `UniformQuantized{|PerAxis}Type` via
// `compose_uniform_quantized_type_pass.cc`.

// RUN: tf-opt %s -tfl-legalize-tf --cse -split-input-file| FileCheck %s --dump-input=fail

func.func @add(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>) -> tensor<1xf32> {
  %0 = "tf.Add"(%arg0, %arg1) : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
  func.return %0: tensor<1xf32>

// CHECK-LABEL: add
// CHECK:  tfl.add %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<1xf32>
// CHECK:  return
}

            preset_method=_PresetMethod.METHOD_STATIC_RANGE_INT8
        ),
        tags=tags,
        signature_keys=['serving_default'],
        op_set=quant_opts_pb2.XLA,
        # Gather op is opt-outed if the size is smaller than the threshold.
        min_num_elements_for_weights=1024 if expect_quantized_gather else 8192,
    )

    data_gen = self._create_data_generator(
        input_key='input_tensor',

// RUN: tf-opt -split-input-file -verify-diagnostics -tfl-runtime-verify %s | FileCheck %s

// Unary math ops
// -----

// CHECK-LABEL: testCos
func.func @testCos(tensor<? x f32>) -> tensor<? x f32> {
^bb0(%arg0: tensor<? x f32>):
  // CHECK: "tfl.cos"(%arg0)
  %0 = "tfl.cos"(%arg0): (tensor<? x f32>) -> tensor<? x f32>
  func.return %0 : tensor<? x f32>
}

// -----

// test invalid Cos input