// do in this test.
  const size_t size = 256;
  std::vector<char> buf;
  buf.reserve(size);
  for (int i = 0; i < size; i++) {
    buf.push_back(i);
  }
  // The fetcher just fetches slices of the buffer.
  auto fetcher = [&buf](const string& filename, size_t offset, size_t n,
                        char* buffer, TF_Status* status) -> int64_t {
    int64_t bytes_transferred;

  // Since `p` is allocated by plugin, free it using plugin's method.
  plugin_memory_free_(p);
  return ret;
}

void ModularFileSystem::FlushCaches(TransactionToken* token) {
  if (ops_->flush_caches != nullptr) ops_->flush_caches(filesystem_.get());
}

Status ModularFileSystem::SetOption(const std::string& name,
                                    const std::vector<string>& values) {

                                              TFE_TensorHandle** inputs,
                                              int num_inputs,
                                              TF_Status* status);

// Fetches the current number of inputs attached to `op`.
//
// Does not use the operation's definition to determine how many inputs should
// be attached. It is intended for use with TFE_OpGetFlatInput to inspect an

setup_file() {
    cd /tf/tensorflow
    bazel version  # Start the bazel server
}

# Do a bazel query specifically for the licenses checker. It searches for
# targets matching the provided query, which start with // or @ but not
# //tensorflow (so it looks for //third_party, //external, etc.), and then
# gathers the list of all packages (i.e. directories) which contain those

// nodes in parallel.
// in_flight_nodes_limit: when is_async is true, this value controls the
// maximum number of in flight async nodes. Enqueuing of additional async ops
// after the limit is reached blocks until some inflight nodes finishes.
// The effect is bounding the memory held by inflight TensorHandles that are
// referenced by the inflight nodes.
// A recommended value has not been established.

  // migrated to TFRT.
  //===--------------------------------------------------------------------===//
  // Clear pending nodes in thread executors and kernel caches.
  virtual void ClearCachesAndThreadExecutors() = 0;

  // Initialize the step resource container for a training step. This is used
  // in current TF runtime. For tfrt, it is used by fallback op handler.

constexpr char kMaxCacheSize[] = "GCS_READ_CACHE_MAX_SIZE_MB";
constexpr size_t kDefaultMaxCacheSize = 0;
// The environment variable that overrides the maximum staleness of cached file
// contents. Once any block of a file reaches this staleness, all cached blocks
// will be evicted on the next read.
constexpr char kMaxStaleness[] = "GCS_READ_CACHE_MAX_STALENESS";
constexpr uint64_t kDefaultMaxStaleness = 0;

// from a placeholder node "arg_tensor_enqueue_<tensor_id>".
//
// `tensor` is still owned by the caller. This call will be blocked if the queue
// has reached its capacity, and will be unblocked when the queued tensors again
// drop below the capacity due to dequeuing.
//
// Tensors are dequeued via the corresponding TF dequeue op.
// TODO(hongm): Add support for `timeout_ms`.

# ==============================================================================
setup_file() {
    bazel version  # Start the bazel server
}

# Do a bazel query specifically for the licenses checker. It searches for
# targets matching the provided query, which start with // or @ but not
# //tensorflow (so it looks for //third_party, //external, etc.), and then
# gathers the list of all packages (i.e. directories) which contain those

  // ForwardAccumulators, where more deeply nested accumulators should not see
  // computations from less deeply nested accumulators.
  bool BusyAccumulating() const { return call_state_.top().accumulating; }

  // Fetches the current Jacobian-vector product associated with `tensor_id`, or
  // a nullptr if none is available.
  //
  // Returns a borrowed reference, i.e. does not run VSpace::MarkAsResult on its