namespace tensorflow {
namespace parallel_device {

// A helper for performing common operations on variables. A much more
// restricted stand-in for tf.Variable in Python.
class Variable {
 public:
  // Construct a Variable from a resource-dtype TFE_TensorHandle and an
  // indication of the dtype of the variable's value.
  //
  // Note that creating this resource-dtype handle can fail, so `Create` is a

          uint64_t stat_cache_max_age, size_t stat_cache_max_entries);
} GCSFile;

// This function is used to initialize a filesystem without the need of setting
// manually environement variables.
void InitTest(TF_Filesystem* filesystem, bool compose, uint64_t block_size,
              size_t max_bytes, uint64_t max_staleness,
              uint64_t stat_cache_max_age, size_t stat_cache_max_entries,

typedef struct TF_WhileParams {
  // The number of inputs to the while loop, i.e. the number of loop variables.
  // This is the size of cond_inputs, body_inputs, and body_outputs.
  const int ninputs;

  // The while condition graph. The inputs are the current values of the loop
  // variables. The output should be a scalar boolean.
  TF_Graph* const cond_graph;
  const TF_Output* const cond_inputs;

// other languages.
//
// The class currently only interacts with single-slice (i.e., non-partitioned)
// variables.
class CheckpointReader {
 public:
  CheckpointReader(const string& filename, TF_Status* status);

  bool HasTensor(const string& name) const;
  const string DebugString() const;

  // Returns a map from variable names to their shapes.  Slices of a partitioned
  // tensor are combined into a single entry.

// Create a variable handle with name `variable_name` on a device with name
// `device_name`.
TFE_TensorHandle* CreateVarHandle(TFE_Context* ctx,
                                  const tensorflow::string& device_name,
                                  const tensorflow::string& variable_name);

// Create a variable with value `value` and name `variable_name` on a device
// with name `device_name`.

// MakeCleanup(f) returns an RAII cleanup object that calls 'f' in its
// destructor. The easiest way to use MakeCleanup is with a lambda argument,
// capturing the return value in an 'auto' local variable. Most users will not
// need more sophisticated syntax than that.
//
// Example:
//   void func() {
//     FILE* fp = fopen("data.txt", "r");
//     if (fp == nullptr) return;

    TF_CheckpointReader* reader, const char* name);
// Get the variable name at the given index
TF_CAPI_EXPORT extern const char* TF_CheckpointReaderGetVariable(
    TF_CheckpointReader* reader, int index);
// Get the number of variable in the checkpoint
TF_CAPI_EXPORT extern int TF_CheckpointReaderSize(TF_CheckpointReader* reader);
// Get the DataType of a variable
TF_CAPI_EXPORT extern TF_DataType TF_CheckpointReaderGetVariableDataType(

  /// the LRU cache, the timestamp (seconds since epoch) at which the block
  /// was cached, a coordination lock, and state & condition variables.
  ///
  /// Thread safety:
  /// The iterator and timestamp fields should only be accessed while holding
  /// the block-cache-wide mu_ instance variable. The state variable should only
  /// be accessed while holding the Block's mu lock. The data vector should only

///   and check the postconditions after the operation returns). If plugins need
///   additional invariants, they should be checked on the plugin side and the
///   `status` out variable should be updated accordingly (e.g., to include
///   plugin version information that relates to the condition change).
///
/// All other changes to the data structures (e.g., method removal, method