__attribute__((aligned(GGML_MEM_ALIGN)))
#endif
char context_buffer[GGML_MAX_SPLITS*GGML_MAX_SPLIT_INPUTS*sizeof(struct ggml_tensor) + sizeof(struct ggml_cgraph)];
+
+ ggml_backend_sched_eval_callback callback_eval;
+ void * callback_eval_user_data;
};
#define hash_id(node) ggml_hash_find_or_insert(sched->hash_set, node)
ggml_graph_dump_dot(split->graph, NULL, split_filename);
#endif
+
uint64_t compute_start_us = ggml_time_us();
- ggml_backend_graph_compute(split_backend, &split->graph);
- //ggml_backend_synchronize(split_backend); // necessary to measure compute time
+ if (!sched->callback_eval) {
+ ggml_backend_graph_compute(split_backend, &split->graph);
+ //ggml_backend_synchronize(split_backend); // necessary to measure compute time
+ } else {
+ // similar to ggml_backend_compare_graph_backend
+ for (int j0 = 0; j0 < split->graph.n_nodes; j0++) {
+ struct ggml_tensor * t = split->graph.nodes[j0];
+
+ // check if the user needs data from this node
+ bool need = sched->callback_eval(t, true, sched->callback_eval_user_data);
+
+ int j1 = j0;
+
+ // determine the range [j0, j1] of nodes that can be computed together
+ while (!need && j1 < split->graph.n_nodes - 1) {
+ t = split->graph.nodes[++j1];
+ need = sched->callback_eval(t, true, sched->callback_eval_user_data);
+ }
+
+ struct ggml_cgraph gv = ggml_graph_view(&split->graph, j0, j1 + 1);
+
+ ggml_backend_graph_compute(split_backend, &gv);
+
+ if (need && !sched->callback_eval(t, false, sched->callback_eval_user_data)) {
+ break;
+ }
+
+ j0 = j1;
+ }
+ }
uint64_t compute_end_us = ggml_time_us();
compute_us[split_backend_id] += compute_end_us - compute_start_us;
}
sched_reset(sched);
}
+
+void ggml_backend_sched_set_eval_callback(ggml_backend_sched_t sched, ggml_backend_sched_eval_callback callback, void * user_data) {
+ sched->callback_eval = callback;
+ sched->callback_eval_user_data = user_data;
+}
+
int ggml_backend_sched_get_n_splits(ggml_backend_sched_t sched) {
return sched->n_splits;
}
struct ggml_backend_sched;
typedef struct ggml_backend_sched * ggml_backend_sched_t;
+ // when ask == true, the scheduler wants to know if the user wants to observe this node
+ // this allows the scheduler to batch nodes together in order to evaluate them in a single call
+ //
+ // when ask == false, the scheduler is passing the node tensor to the user for observation
+ // if the user returns false, the scheduler will cancel the graph compute
+ //
+ typedef bool (*ggml_backend_sched_eval_callback)(struct ggml_tensor * t, bool ask, void * user_data);
+
// Initialize a backend scheduler
GGML_API ggml_backend_sched_t ggml_backend_sched_new(ggml_backend_t * backends, ggml_backend_buffer_type_t * bufts, int n_backends, size_t graph_size);
GGML_API void ggml_backend_sched_free(ggml_backend_sched_t sched);
// Reset all assignments and allocators - must be called before using the sched allocators to allocate inputs
GGML_API void ggml_backend_sched_reset(ggml_backend_sched_t sched);
+ // Set a callback to be called for each resulting node during graph compute
+ GGML_API void ggml_backend_sched_set_eval_callback(ggml_backend_sched_t sched, ggml_backend_sched_eval_callback callback, void * user_data);
+
//
// Utils
//