@@ -1442,7 +1442,7 @@ __STATIC_INLINE__ ggml_tensor* ggml_ext_group_norm(ggml_context* ctx,
14421442
14431443__STATIC_INLINE__ void ggml_ext_backend_tensor_get_and_sync (ggml_backend_t backend, const ggml_tensor* tensor, void * data, size_t offset, size_t size) {
14441444 if ((sd_backend_is (backend, " ROCm" ) || sd_backend_is (backend, " CUDA" ) || sd_backend_is (backend, " SYCL" )) &&
1445- !ggml_backend_is_cpu (backend)) {
1445+ !sd_backend_is_cpu (backend)) {
14461446 ggml_backend_tensor_get_async (backend, tensor, data, offset, size);
14471447 ggml_backend_synchronize (backend);
14481448 return ;
@@ -1899,7 +1899,7 @@ struct GGMLRunner {
18991899 LOG_DEBUG (" %s compute buffer size: %.2f MB(%s)" ,
19001900 get_desc ().c_str (),
19011901 compute_buffer_size / 1024.0 / 1024.0 ,
1902- ggml_backend_is_cpu (runtime_backend) ? " RAM" : " VRAM" );
1902+ sd_backend_is_cpu (runtime_backend) ? " RAM" : " VRAM" );
19031903 return true ;
19041904 }
19051905
@@ -1986,7 +1986,7 @@ struct GGMLRunner {
19861986 LOG_DEBUG (" %s cache backend buffer size = % 6.2f MB(%s) (%i tensors)" ,
19871987 get_desc ().c_str (),
19881988 cache_buffer_size / (1024 .f * 1024 .f ),
1989- ggml_backend_is_cpu (runtime_backend) ? " RAM" : " VRAM" ,
1989+ sd_backend_is_cpu (runtime_backend) ? " RAM" : " VRAM" ,
19901990 num_tensors);
19911991 if (old_cache_buffer != nullptr ) {
19921992 ggml_backend_buffer_free (old_cache_buffer);
@@ -2293,13 +2293,13 @@ struct GGMLRunner {
22932293 max_graph_vram_bytes > 0 &&
22942294 plan.segments .size () > 1 &&
22952295 params_backend != runtime_backend &&
2296- !ggml_backend_is_cpu (runtime_backend);
2296+ !sd_backend_is_cpu (runtime_backend);
22972297 }
22982298
22992299 bool can_attempt_graph_cut_segmented_compute () const {
23002300 return max_graph_vram_bytes > 0 &&
23012301 params_backend != runtime_backend &&
2302- !ggml_backend_is_cpu (runtime_backend);
2302+ !sd_backend_is_cpu (runtime_backend);
23032303 }
23042304
23052305 bool resolve_graph_cut_plan (ggml_cgraph* gf,
@@ -2436,8 +2436,8 @@ struct GGMLRunner {
24362436 int64_t t_copy_begin = ggml_time_ms ();
24372437 copy_data_to_backend_tensor (gf, !preserve_backend_tensor_data_map);
24382438 int64_t t_copy_end = ggml_time_ms ();
2439- if (ggml_backend_is_cpu (runtime_backend)) {
2440- ggml_backend_cpu_set_n_threads (runtime_backend, n_threads);
2439+ if (sd_backend_is_cpu (runtime_backend)) {
2440+ sd_backend_cpu_set_n_threads (runtime_backend, n_threads);
24412441 }
24422442
24432443 int64_t t_compute_begin = ggml_time_ms ();
@@ -2679,7 +2679,7 @@ struct GGMLRunner {
26792679 LOG_DEBUG (" %s params backend buffer size = % 6.2f MB(%s) (%i tensors)" ,
26802680 get_desc ().c_str (),
26812681 params_buffer_size / (1024 .f * 1024 .f ),
2682- ggml_backend_is_cpu (params_backend) ? " RAM" : " VRAM" ,
2682+ sd_backend_is_cpu (params_backend) ? " RAM" : " VRAM" ,
26832683 num_tensors);
26842684 return true ;
26852685 }
@@ -2746,7 +2746,7 @@ struct GGMLRunner {
27462746 return nullptr ;
27472747 }
27482748 // it's performing a compute, check if backend isn't cpu
2749- if (!ggml_backend_is_cpu (runtime_backend) && (tensor->buffer == nullptr || ggml_backend_buffer_is_host (tensor->buffer ))) {
2749+ if (!sd_backend_is_cpu (runtime_backend) && (tensor->buffer == nullptr || ggml_backend_buffer_is_host (tensor->buffer ))) {
27502750 // pass input tensors to gpu memory
27512751 auto backend_tensor = ggml_dup_tensor (compute_ctx, tensor);
27522752
0 commit comments