# Note this gives the DaemonSet a relatively high privilege, as modifying pod metadata/status can have wider impacts.
      labelPods: false
      # deletePods will delete any broken pod. These will then be rescheduled, hopefully onto a node that is fully ready.
      # Note this gives the DaemonSet a relatively high privilege, as it can delete any Pod.
      deletePods: false

import java.util.ArrayDeque;
import java.util.Collection;
import java.util.Queue;

/**
 * A non-blocking queue which automatically evicts elements from the head of the queue when
 * attempting to add new elements onto the queue and it is full. This queue orders elements FIFO
 * (first-in-first-out). This data structure is logically equivalent to a circular buffer (i.e.,
 * cyclic buffer or ring buffer).
 *

#include "tensorflow/core/platform/test.h"

namespace {

struct LoggingDevice {
  tensorflow::string device_name;
  tensorflow::string underlying_device;
  // Set to true whenever a TensorHandle is copied onto the device
  bool* arrived_flag;
  // Set to true whenever an operation is executed
  bool* executed_flag;
  // If true, only explicit op placements are accepted. If false, uses
  // type-based dispatch.

  EXPECT_THAT(bundle_reader.status(), Not(IsOk()));
}

TEST_F(SaveVariablesToCheckpointTest, MutableVariablesNotSaved) {
  // This function includes an AssignVariableOp that does not initialize the
  // variable from a ConstOp. In this case, the variable is not saved to the
  // checkpoint.
  constexpr absl::string_view kModuleCode = R"mlir(
    module attributes {tf_saved_model.semantics} {

// reduce_fn call.
WhileRegionOp CreateDatasetWhile(OpBuilder builder,
                                 ReduceDatasetOp reduce_dataset) {
  auto const_true = builder.create<TF::ConstOp>(
      reduce_dataset.getLoc(),
      DenseIntElementsAttr::get(
          RankedTensorType::get(/*shape=*/{}, builder.getI1Type()), true));

  SmallVector<Value, 4> while_input_values;

docker export ${MOUNTER_DEFAULT_NAME} > /tmp/${MOUNTER_DEFAULT_NAME}.tar
docker rm ${MOUNTER_DEFAULT_NAME} > /dev/null
docker rmi "${IMAGE_URL}" > /dev/null

echo
echo "Loading mount utilities onto this instance..."
echo

mkdir -p ${MOUNTER_PATH}
tar xf /tmp/${MOUNTER_DEFAULT_NAME}.tar -C ${MOUNTER_PATH}

# Bind the kubelet directory to one under flexvolume_mounter
mkdir -p ${MOUNTER_PATH}/var/lib/kubelet

// WithAuthentication creates an http handler that tries to authenticate the given request as a user, and then
// stores any such user found onto the provided context for the request. If authentication fails or returns an error
// the failed handler is used. On success, "Authorization" header is removed from the request and handler
// is invoked to serve the request.

  if (tfl::IsQuantized(tensor)) {
    auto op = builder.create<tfl::QConstOp>(
        loc, mlir::TypeAttr::get(shaped_type), value);
    return op.getOperation();
  }
  auto op = builder.create<tfl::ConstOp>(loc, value);
  op->setAttr("tfl.is_variable", builder.getUnitAttr());
  if (tensor.quantization && !tensor.quantization->min.empty()) {
    if (auto stats_op =

      mlir::RankedTensorType::get({}, builder->getIntegerType(32));
  auto split_dimension_attr =
      mlir::DenseElementsAttr::get(split_dim_type, split_dimension);
  auto split_dimension_op = builder->create<mlir::TF::ConstOp>(
      location, split_dim_type, split_dimension_attr);

  // Correctly set output shapes of split op output if input shape is statically
  // known.
  mlir::Type output_type;

// a hook with a fake return address whose lower 9 bits are `fake_pc` up to a
// constant shift. This is achieved by pushing a return address pointing into
// 512 ret instructions at offset `fake_pc` onto the stack and then jumping
// directly to the address of the hook.
//
// Note: We only set the lowest 9 bits of the return address since only these
// bits are used by the libFuzzer value profiling mode for integer compares, see