// -----------------------------------------------------------------------------
// Dynamic cluster API.

// Update an existing context with a new set of servers defined in a ServerDef
// proto. Servers can be added to and removed from the list of remote workers
// in the context. A New set of servers identified by the ServerDef must be up
// when the context is updated.
//
// This API is for experimental usage and may be subject to change.

//      params->optimizer_configs->struct_size =
//      TP_OPTIMIZER_CONFIGS_STRUCT_SIZE; params->optimizer_configs->remapping =
//      TF_TriState_Off;
//
//      // Set functions to create a new optimizer.
//      params->optimizer->struct_size = TP_OPTIMIZER_STRUCT_SIZE;
//      params->optimizer->create_func = (My_optimizer::create_func);
//    }

#define GO_MAJOR 0
#define GO_MINOR 0
#define GO_PATCH 1

  }

  // We may need to allocate zero inputs for trainable dtypes we don't have JVPs
  // for. Make sure they get cleaned up.
  std::vector<Gradient*> new_zeros;
  auto delete_new_zeros = gtl::MakeCleanup([&new_zeros, this] {
    for (Gradient* tensor : new_zeros) {
      this->vspace_.DeleteGradient(tensor);
    }
  });
  std::vector<Gradient*> in_grads;
  in_grads.reserve(input_tensors.size());

// Aborts all ongoing collectives with the specified status. After abortion,
// subsequent collectives will error with this status immediately. To reset the
// collectives, create a new EagerContext.
//
// This is intended to be used when a peer failure is detected.
TF_CAPI_EXPORT extern void TFE_AbortCollectiveOps(TFE_Context* ctx,
                                                  TF_Status* status);

                                                         TF_Status* status);

// Create a new TFE_TensorHandle with the same contents as 'h' but placed
// in the memory of the device name 'device_name'.
// If source and destination are the same device, then this creates a new handle
// that shares the underlying buffer. Otherwise, it currently requires at least