// Represents a (partially-defined) shape.
typedef struct TF_Shape {
  int num_dims;  // Must be >= -1; -1 represents unknown rank.
  int64_t* dim_sizes;
} TF_Shape;

// Add a new parameter to a TensorFlow Function.
TF_AbstractTensor* TF_AddFunctionParameter(TF_ExecutionContext* func,
                                           TF_DataType dtype, TF_Shape shape,

// Create a ServerDef with the given `job_name` and add `num_tasks` tasks in it.
tensorflow::ServerDef GetServerDef(const tensorflow::string& job_name,
                                   int num_tasks);

// Create a ServerDef with job name "localhost" and add `num_tasks` tasks in it.
tensorflow::ServerDef GetServerDef(int num_tasks);

// Create a multi-client ServerDef with the given `job_name`, add `num_tasks`

                          const char* name = "scalar");

TF_Operation* Add(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
                  TF_Status* s, const char* name = "add");

TF_Operation* AddNoCheck(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
                         TF_Status* s, const char* name = "add");

TF_Operation* AddWithCtrlDependency(TF_Operation* l, TF_Operation* r,

// MLIR implementation or to a graph implementation.
class TracingContext : public AbstractContext {
 protected:
  explicit TracingContext(AbstractContextKind kind) : AbstractContext(kind) {}

 public:
  // Add a function parameter and return the corresponding tensor.
  virtual Status AddParameter(DataType dtype, const PartialTensorShape& shape,
                              TracingTensorHandle**) = 0;

//   // forward `op`.
//   return new AddGradientFunction;
// }
//
// Status RegisterGradients(GradientRegistry* registry) {
//   return registry->Register("Add", AddRegisterer);
// }
class GradientFunction {
 public:
  virtual Status Compute(AbstractContext* ctx,
                         absl::Span<AbstractTensorHandle* const> grad_outputs,