if (&g_state.contexts[i].context == ctx) {
g_state.contexts[i].used = false;
- GGML_PRINT_DEBUG("%s: context %d with %d objects has been freed. memory used = %zu\n",
- __func__, i, ctx->n_objects, ctx->objects_end->offs + ctx->objects_end->size);
+ GGML_PRINT_DEBUG("%s: context %d has been freed. memory used = %zu\n",
+ __func__, i, ggml_used_mem(ctx));
if (ctx->mem_buffer_owned) {
GGML_ALIGNED_FREE(ctx->mem_buffer);
if (GGML_OP_HAS_FINALIZE[node->op]) {
params.nth = n_tasks_arr[node_n];
ggml_compute_forward(¶ms, node);
- ggml_graph_compute_perf_stats_node(node, state->shared);
}
+ ggml_graph_compute_perf_stats_node(node, state->shared);
}
// distribute new work or execute it direct if 1T
if (GGML_OP_HAS_FINALIZE[node->op]) {
params.type = GGML_TASK_FINALIZE;
ggml_compute_forward(¶ms, node);
- ggml_graph_compute_perf_stats_node(node, state->shared);
}
+
+ ggml_graph_compute_perf_stats_node(node, state->shared);
} else {
break;
}
}
void ggml_graph_export(const struct ggml_cgraph * cgraph, const char * fname) {
- //assert(cgraph->work == NULL);
- //assert(cgraph->work_size == 0);
-
uint64_t size_eval = 0;
// compute size of intermediate results
GGML_PRINT("=== GRAPH ===\n");
- GGML_PRINT_DEBUG("n_threads = %d\n", cgraph->n_threads);
- GGML_PRINT_DEBUG("total work size = %zu bytes\n", cgraph->work_size);
-
GGML_PRINT("n_nodes = %d\n", cgraph->n_nodes);
for (int i = 0; i < cgraph->n_nodes; i++) {
struct ggml_tensor * node = cgraph->nodes[i];