)

const (
	// SSECustomerKeySize is the size of valid client provided encryption keys in bytes.
	// Currently AWS supports only AES256. So the SSE-C key size is fixed to 32 bytes.
	SSECustomerKeySize = 32

	// SSEIVSize is the size of the IV data
	SSEIVSize = 32 // 32 bytes

	// SSEDAREPackageBlockSize - SSE dare package block size.

				Limit: 1,
			},
			// TODO(#108003): As of now, watchcache is deliberately ignoring
			// limit if RV=0 is specified, returning whole list of objects.
			// While this should eventually get fixed, for now we're explicitly
			// ignoring this testcase for watchcache.
			ignoreForWatchCache:        true,
			expectedOut:                []example.Pod{*preset[1]},
			expectContinue:             true,

}

def TensorFlowShapeInferencePass : Pass<"tf-shape-inference", "ModuleOp"> {
  let summary =
    "Shape inference on TF dialect and ops implementing InferTypeOpInterface";

  let description = [{
    Fixed point shape refinement pass that utilizes the shape functions
    registered on ops using the InferTypeOpInterface as well as by bridging to
    the TensorFlow op registry's shape functions. This is an interprocedural

// should be performed by other components (like the volume manager). The duration
// of this call is the minimum latency for static pods to be restarted if they
// are updated with a fixed UID (most should use a dynamic UID), and no config
// updates are delivered to the pod workers while this method is running.
func (kl *Kubelet) HandlePodCleanups(ctx context.Context) error {

test:release_macos_arm64 --config=release_macos_base

# Ensure release_base is set on windows
build:release_cpu_windows --config=release_base

# TODO(kanglan): Update windows configs after b/289091160 is fixed
build:release_cpu_windows --config=avx_win
build:release_cpu_windows --define=no_tensorflow_py_deps=true

# Exclude TFRT integration for anything but Linux.
build:android --config=no_tfrt

    readonly_model_ = input_model_->GetModel();
    model_ = UnPackFlatBufferModel(*readonly_model_);
  }
};

// TODO(b/327796566): re-enable after the bug is fixed
// TEST_F(QuantizeConvNoBiasModelTest, QuantizationSucceeds) {
//   auto status = QuantizeModelAllOperators(
//       &model_, TensorType_INT8, TensorType_INT8,

	// authZ plugin is set, role policies are just claims sent to
	// the plugin and they need not exist.
	//
	// If some mapped policies do not exist, we print some error
	// messages but continue any way - they can be fixed in the
	// running server by creating the policies after start up.
	for arn, rolePolicies := range m {
		specifiedPoliciesSet := newMappedPolicy(rolePolicies).policySet()

    auto indices_rank = indices_ty.getRank();
    int64_t num_index_dims = indices_ty.getDimSize(indices_rank - 1);
    if (!params_ty || !indices_ty) return failure();
    // the last dim of indices of GatherNdOp must be fixed shaped
    if (num_index_dims == ShapedType::kDynamic) return failure();

    SmallVector<int64_t, 4> slice_sizes;
    slice_sizes.reserve(params_rank);
    for (int64_t i = 0; i < params_rank; ++i) {

          none_of(op->getResultTypes(), CanBeRefined))
        return WalkResult::advance();

      // Best-effort shape inference in attached functions. Do not return
      // failure even if it doesn't get to fixed point, but propagate "real"
      // failure.
      if (failed(PropagateShapeIntoAttachedFunctions(op, max_iterations))) {
        op->emitWarning() << "unable to refine shape of attached function "

in one of these ways:

    a) Convey the object code in, or embodied in, a physical product
    (including a physical distribution medium), accompanied by the
    Corresponding Source fixed on a durable physical medium
    customarily used for software interchange.

    b) Convey the object code in, or embodied in, a physical product
    (including a physical distribution medium), accompanied by a