notification.Notify();
    // Wait for other thread to issue read.
    Env::Default()->SleepForMicroseconds(100000);  // 0.1 secs
    TF_SetStatus(status, TF_OK, "");
    return n;
  };
  tf_gcs_filesystem::RamFileBlockCache cache(block_size, block_size, 0,
                                             fetcher);
  // Fork off thread for parallel read.
  std::unique_ptr<Thread> concurrent(

                                  const std::shared_ptr<Block>& block,
                                  TF_Status* status) {
  absl::MutexLock lock(&mu_);
  if (block->timestamp == 0) {
    // The block was evicted from another thread. Allow it to remain evicted.
    return TF_SetStatus(status, TF_OK, "");
  }
  if (block->lru_iterator != lru_list_.begin()) {
    lru_list_.erase(block->lru_iterator);
    lru_list_.push_front(key);

  cc_options.numa_node = options->numa_node;
  return reinterpret_cast<TF_Thread*>(::tensorflow::Env::Default()->StartThread(
      cc_options, thread_name, [=]() { (*work_func)(param); }));
}

void TF_JoinThread(TF_Thread* thread) {
  // ::tensorflow::Thread joins on destruction
  delete reinterpret_cast<::tensorflow::Thread*>(thread);
}

void* TF_LoadSharedLibrary(const char* library_filename, TF_Status* status) {

        block_fetcher_(block_fetcher),
        timer_seconds_(timer_seconds),
        pruning_thread_(nullptr,
                        [](TF_Thread* thread) { TF_JoinThread(thread); }) {
    if (max_staleness_ > 0) {
      TF_ThreadOptions thread_options;
      TF_DefaultThreadOptions(&thread_options);
      pruning_thread_.reset(
          TF_StartThread(&thread_options, "TF_prune_FBC", PruneThread, this));
    }

}

}  // namespace

TEST(TestEnv, TestThreads) {
  TF_ThreadOptions options;
  TF_DefaultThreadOptions(&options);
  SomeThreadData data;
  TF_Thread* thread =
      TF_StartThread(&options, "SomeThreadName", &SomeThreadFunc, &data);
  TF_JoinThread(thread);
  ::tensorflow::mutex_lock l(data.mu);
  ASSERT_TRUE(data.did_work);

  virtual void SetJitCompileRewrite(bool enable) = 0;

  // Sets the device placement policy for the current thread.
  virtual void SetThreadLocalDevicePlacementPolicy(
      ContextDevicePlacementPolicy policy) = 0;
  // Returns the device placement policy for the current thread.
  virtual ContextDevicePlacementPolicy GetDevicePlacementPolicy() const = 0;

  // Configure graph collection in RunMetadata.

#include <memory>
#include <string>

#include "absl/base/thread_annotations.h"
#include "absl/synchronization/mutex.h"
#include "tensorflow/c/env.h"
#include "tensorflow/c/tf_status.h"

namespace tf_gcs_filesystem {

/// \brief An LRU cache of string keys and arbitrary values, with configurable
/// max item age (in seconds) and max entries.
///
/// This class is thread safe.
template <typename T>
class ExpiringLRUCache {

// ops.
TF_CAPI_EXPORT extern void TFE_ContextClearCaches(TFE_Context* ctx);

// Sets a thread-local device placement policy. After this call, other calls to
// TFE_Execute in the same thread will use the device policy specified here
// instead of the device policy used to construct the context. This has no
// effect on the device policy used by other program threads.
TF_CAPI_EXPORT extern void TFE_ContextSetThreadLocalDevicePlacementPolicy(

  // unnecessary allocations each Execute call, we keep one heap-allocated
  // version for the thread.
  StatusPtr status_ TF_GUARDED_BY(execution_mutex_);

  const std::string device_;
  ExecutorPtr executor_ TF_GUARDED_BY(execution_mutex_);
  mutable OpPtr op_ TF_GUARDED_BY(execution_mutex_);
  std::unique_ptr<Thread> thread_;
};

DeviceThread::~DeviceThread() {
  {
    tensorflow::mutex_lock l(execution_mutex_);

TF_CAPI_EXPORT extern TF_Thread* TF_StartThread(const TF_ThreadOptions* options,
                                                const char* thread_name,
                                                void (*work_func)(void*),
                                                void* param);

// Waits for the given thread to finish execution, then deletes it.
TF_CAPI_EXPORT extern void TF_JoinThread(TF_Thread* thread);