void Append(const TF_WritableFile* file, const char* buffer, size_t n,
            TF_Status* status);
int64_t Tell(const TF_WritableFile* file, TF_Status* status);
void Flush(const TF_WritableFile* file, TF_Status* status);
void Sync(const TF_WritableFile* file, TF_Status* status);
void Close(const TF_WritableFile* file, TF_Status* status);
}  // namespace tf_writable_file

namespace tf_read_only_memory_region {

                                                TF_Status* status);

// Obtains statistics for the given path. If status is TF_OK, *stats is
// updated, otherwise it is not touched.
TF_CAPI_EXPORT extern void TF_FileStat(const char* filename,
                                       TF_FileStatistics* stats,
                                       TF_Status* status);

                          const char* device, TF_Status* status);
  // Dereferences the backing buffer for the variable. Note that since this can
  // fail (it runs operations), it must be called explicitly and the resulting
  // `status` checked.
  void Destroy(TFE_Context* context, TF_Status* status);

  // Reads from the variable.
  TensorHandlePtr Read(TFE_Context* context, TF_Status* status);
  // Assigns a new value to the variable.

                                              TF_Status* status);

// Starts an in-process TensorFlow server.
TF_CAPI_EXPORT extern void TF_ServerStart(TF_Server* server, TF_Status* status);

// Stops an in-process TensorFlow server.
TF_CAPI_EXPORT extern void TF_ServerStop(TF_Server* server, TF_Status* status);

// Blocks until the server has been successfully stopped (via TF_ServerStop or

        TFE_NewOp(context, "Const", status), TFE_DeleteOp);
    if (TF_GetCode(status) != TF_OK) return nullptr;
    TFE_OpSetDevice(const_op.get(), underlying_devices_[device_index].c_str(),
                    status);
    if (TF_GetCode(status) != TF_OK) return nullptr;
    TFE_OpSetAttrTensor(const_op.get(), "value", tensor.get(), status);
    if (TF_GetCode(status) != TF_OK) return nullptr;

  TF_Status* status = TF_NewStatus();
  TF_Tensor* t = TFE_AllocateHostTensor(ctx, datatype, dims, num_dims, status);
  memcpy(TF_TensorData(t), data, TF_TensorByteSize(t));
  TFE_TensorHandle* th = TFE_NewTensorHandleFromTensor(ctx, t, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteTensor(t);
  TF_DeleteStatus(status);
  return th;
}

class NotDifferentiableGradientFunction : public GradientFunction {
  Status Compute(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> grad_outputs,
                 absl::Span<AbstractTensorHandle*> grad_inputs) override;
};
// Shorthand for registry->Register(op, new NotDifferentiableGradientFunction)
Status RegisterNotDifferentiable(GradientRegistry* registry, const string& op);
}  // namespace gradients

  // available to be called/referenced by its name in this context.
  virtual Status RegisterFunction(AbstractFunction*) = 0;
  // Remove a function. 'func' argument is the name of a previously added
  // FunctionDef. The name is in fdef.signature.name.
  virtual Status RemoveFunction(const string& func) = 0;

 private:
  const AbstractContextKind kind_;
};

namespace internal {

TF_CAPI_EXPORT extern void TFE_OpSetDevice(TFE_Op* op, const char* device_name,
                                           TF_Status* status);
// The returned string remains valid throughout the lifetime of 'op'.
TF_CAPI_EXPORT extern const char* TFE_OpGetDevice(const TFE_Op* op,
                                                  TF_Status* status);

  virtual Status SetAttrInt(const char* attr_name, int64_t value) = 0;
  virtual Status SetAttrFloat(const char* attr_name, float value) = 0;
  virtual Status SetAttrBool(const char* attr_name, bool value) = 0;
  virtual Status SetAttrType(const char* attr_name, DataType value) = 0;
  virtual Status SetAttrShape(const char* attr_name, const int64_t* dims,
                              const int num_dims) = 0;