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triage for opencl
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481f7a6fbc
commit
762eeb6204
4 changed files with 60 additions and 6 deletions
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@ -934,11 +934,19 @@ ModelLoadResult gpttype_load_model(const load_model_inputs inputs, FileFormat in
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model_params.n_gpu_layers = inputs.gpulayers;
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#if defined(GGML_USE_CLBLAST)
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if(file_format==FileFormat::GGUF_GENERIC && (file_format_meta.model_architecture == GGUFArch::FALCON || file_format_meta.model_architecture == GGUFArch::PHI) && model_params.n_gpu_layers>0)
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if(file_format==FileFormat::GGUF_GENERIC && model_params.n_gpu_layers>0)
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{
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if(file_format_meta.model_architecture == GGUFArch::FALCON)
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{
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printf("\nOpenCL does not support GPU Layer offloading for this model architecture! GPU Offload has been disabled.\n");
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model_params.n_gpu_layers = 0;
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}
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else if(file_format_meta.model_architecture == GGUFArch::PHI || file_format_meta.n_expert_count>1)
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{
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printf("\nOpenCL cannot use regular GPU offloading for this model architecture. A fallback GPU offloader will be used with degraded performance.\n");
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clblast_offload_fallback_mode = true;
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}
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}
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#endif
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#if defined(GGML_USE_CUBLAS)
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if(ggml_cpu_has_gpublas() && cu_parseinfo_maindevice>0)
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43
llama.cpp
43
llama.cpp
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@ -180,6 +180,25 @@ static std::string format(const char * fmt, ...) {
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return std::string(buf.data(), size);
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}
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static bool clblast_offload_fallback_mode = false; //used when regular offload will segfault
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static int clblast_offload_fallback_layers = 0;
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static int layer_name_to_number(std::string inputString)
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{
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size_t firstDotPosition = inputString.find('.');
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int converted = -1;
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if (firstDotPosition != std::string::npos) {
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size_t secondDotPosition = inputString.find('.', firstDotPosition + 1);
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if (secondDotPosition != std::string::npos) {
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std::string numbersPortion = inputString.substr(firstDotPosition + 1, secondDotPosition - firstDotPosition - 1);
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try{converted = std::stoi(numbersPortion);}
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catch (const std::invalid_argument& e) {}
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catch (const std::out_of_range& e) {}
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}
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}
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return converted;
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}
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//
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// gguf constants (sync with gguf.py)
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//
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@ -2628,6 +2647,19 @@ struct llama_model_loader {
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}
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}
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#if defined(GGML_USE_CLBLAST)
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if(clblast_offload_fallback_mode)
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{
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int layernum = layer_name_to_number(cur->name);
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bool shouldoffload = (layernum>=0 && clblast_offload_fallback_layers>layernum);
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if(shouldoffload)
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{
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cur->backend = GGML_BACKEND_GPU;
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ggml_cl_transform_tensor(cur->data, cur);
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}
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}
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#endif
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size_done += ggml_nbytes(cur);
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}
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@ -3330,7 +3362,14 @@ static bool llm_load_tensors(
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model.n_gpu_layers = n_gpu_layers;
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const int64_t n_layer = hparams.n_layer;
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const int64_t i_gpu_start = std::max((int64_t) hparams.n_layer - n_gpu_layers, (int64_t) 0);
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int64_t i_gpu_start = std::max((int64_t) hparams.n_layer - n_gpu_layers, (int64_t) 0);
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if(clblast_offload_fallback_mode)
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{
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printf("\nOpenCL GPU Offload Fallback...");
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clblast_offload_fallback_layers = n_gpu_layers;
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i_gpu_start = std::max((int64_t) hparams.n_layer, (int64_t) 0);
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}
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// there is very little benefit to offloading the input layer, so always keep it on the CPU
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model.buft_input = llama_default_buffer_type_cpu(true);
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@ -3401,7 +3440,7 @@ static bool llm_load_tensors(
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};
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}
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// assign the output layer
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if (n_gpu_layers > n_layer) {
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if (n_gpu_layers > n_layer && !clblast_offload_fallback_mode) {
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model.buft_output = {
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split_buft,
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llama_default_buffer_type_offload(main_gpu)
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@ -272,10 +272,16 @@ void print_tok_vec(std::vector<float> &embd)
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if(modelarch!="" && fileformatmeta!=nullptr)
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{
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std::string fkey = modelarch+".context_length";
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auto keyidx = gguf_find_key(ctx, fkey.c_str());
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int keyidx = gguf_find_key(ctx, fkey.c_str());
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if (keyidx != -1) {
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fileformatmeta->n_ctx_train = gguf_get_val_u32(ctx, keyidx);
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}
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fkey = modelarch+".expert_count";
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keyidx = gguf_find_key(ctx, fkey.c_str());
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if (keyidx != -1) {
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fileformatmeta->n_expert_count = gguf_get_val_u32(ctx, keyidx);
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}
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int filever = gguf_get_version(ctx);
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fileformatmeta->fileversion = filever;
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fileformatmeta->model_architecture = GGUFArch::DEFAULT;
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@ -62,6 +62,7 @@ struct FileFormatExtraMeta
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int n_ctx_train = 2048;
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int fileversion = 0;
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GGUFArch model_architecture = GGUFArch::DEFAULT;
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int n_expert_count = 0;
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};
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enum ModelLoadResult
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