[Fix] Compiling clip-quantize-cli and running it in a CUDA environment will cause ggml_fp16_to_fp32 to report an error when trying to access video memory. You need to switch to the CPU backend to run quantize.

After the fix, it will automatically run in the CPU backend and will no longer be bound to CUDA.

Author: Ivy233

examples/llava/clip.cpp

@@ -1370,9 +1370,9 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32
 }
 
 // read and create ggml_context containing the tensors and their data
-struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
+struct clip_ctx * clip_model_load(const char * fname, const int verbosity, const bool use_gpu) {
     return clip_init(fname, clip_context_params{
-        /* use_gpu */   true,
+        /* use_gpu */   use_gpu,
         /* verbosity */ verbosity,
     });
 }
@@ -2989,7 +2989,7 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i
     assert(itype < GGML_TYPE_COUNT);
     ggml_type type = static_cast<ggml_type>(itype);
 
-    auto * ctx_clip = clip_model_load(fname_inp, 2);
+    auto * ctx_clip = clip_model_load(fname_inp, 2, false);
 
     const auto & ctx_src = ctx_clip->ctx_gguf;
     const auto & ctx_data = ctx_clip->ctx_data;

examples/llava/clip.h

@@ -45,7 +45,7 @@ struct clip_context_params {
 };
 
 // deprecated, use clip_init
-CLIP_API struct clip_ctx * clip_model_load(const char * fname, int verbosity);
+CLIP_API struct clip_ctx * clip_model_load(const char * fname, const int verbosity=1, const bool use_gpu=true);
 
 CLIP_API struct clip_ctx * clip_init(const char * fname, struct clip_context_params ctx_params);