if (!status->status.ok()) {
    TF_DeleteCheckpointReader(reader);
    return nullptr;
  }
  const auto& m = reader->GetVariableToDataTypeMap();
  for (auto it = m.begin(); it != m.end(); ++it)
    reader->variable_list.push_back(it->first);
  std::sort(reader->variable_list.begin(), reader->variable_list.end());
  return reader;
}

void TF_DeleteCheckpointReader(TF_CheckpointReader* reader) { delete reader; }

} PosixFile;

static void Cleanup(TF_RandomAccessFile* file) {
  auto posix_file = static_cast<PosixFile*>(file->plugin_file);
  close(posix_file->fd);
  // This would be safe to free using `free` directly as it is only opaque.
  // However, it is better to be consistent everywhere.
  plugin_memory_free(const_cast<char*>(posix_file->filename));
  delete posix_file;
}

static int64_t Read(const TF_RandomAccessFile* file, uint64_t offset, size_t n,

  TFE_ExecutorWaitForAllPendingNodes(executor, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteExecutor(executor);
  TF_DeleteStatus(status);
}

// Read the value of variable `var` and save it into `out_value`.
void ReadVariable(TFE_Context* ctx, TFE_TensorHandle* var,
                  TFE_TensorHandle** out_value) {
  TF_Status* status = TF_NewStatus();
  TFE_Op* op = TFE_NewOp(ctx, "ReadVariableOp", status);

}

void RamFileBlockCache::RemoveFile_Locked(const std::string& filename) {
  Key begin = std::make_pair(filename, 0);
  auto it = block_map_.lower_bound(begin);
  while (it != block_map_.end() && it->first.first == filename) {
    auto next = std::next(it);
    RemoveBlock(it);
    it = next;
  }
}

void RamFileBlockCache::RemoveBlock(BlockMap::iterator entry) {

  EXPECT_EQ(cache.CacheSize(), 0);
}

TEST(RamFileBlockCacheTest, ParallelReads) {
  // This fetcher won't respond until either `callers` threads are calling it
  // concurrently (at which point it will respond with success to all callers),
  // or 10 seconds have elapsed (at which point it will respond with an error).
  const int callers = 4;
  BlockingCounter counter(callers);

  // Finalize the function by providing the returned values.
  TF_AbstractFunction* func;
  {
    // We want to return the output of both add operations, create a new list
    // and populate it.
    TF_OutputList* func_outputs = TF_NewOutputList();
    TF_OutputListPushBack(func_outputs, add_output1, s);
    ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
    TF_OutputListPushBack(func_outputs, add_output2, s);

  char* p = ops_->translate_name(filesystem_.get(), name.c_str());
  CHECK(p != nullptr) << "TranslateName(" << name << ") returned nullptr";

  std::string ret(p);
  // 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());
}

    TF_DeleteStatus(status);
  }

  // 6. Read `var` using `ctx_1`. This read should succeed since `ctx_1` was
  // created with `isolate_session_state` set to false, and update should
  // preserve it.
  {
    // Create a handle to `var`, using `ctx_1`.
    TFE_TensorHandle* var_handle =
        CreateVarHandle(ctx_1, remote_device, /*variable_name=*/"var");

    TFE_TensorHandle* handle_1 = nullptr;

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

namespace tensorflow {

namespace {

// Managing context for the DLManagedTensor, will manage the lifetime of
// DLManagedTensor. When calling DLManagedTensor::deleter, it will notify the
// original framework of destruction, and this context will be deleted also.
struct TfDlManagedTensorCtx {
  TensorReference reference;
  std::vector<int64_t> shape;
  std::vector<int64_t> strides;

  AbstractContext* ctx_;
};

// Returns the number of elements in the gradient tensor.
int64_t TapeVSpace::NumElements(AbstractTensorHandle* tensor) const {
  // TODO(srbs): It seems like this is used only for performance optimization
  // and not for correctness. The only downside of keeping this 1 seems to be
  // that the gradient accumulation is unbounded and we will never