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Fixed OpenCL offloading prints (#2082)
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parent
7f0e9a775e
commit
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15
llama.cpp
15
llama.cpp
@ -1156,6 +1156,7 @@ static void llama_model_load_internal(
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}
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}
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#endif // GGML_USE_CUBLAS
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#if defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST)
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const int n_gpu = std::min(n_gpu_layers, int(hparams.n_layer));
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@ -1164,6 +1165,10 @@ static void llama_model_load_internal(
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fprintf(stderr, "%s: offloading non-repeating layers to GPU\n", __func__);
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}
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size_t vram_kv_cache = 0;
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#ifdef GGML_USE_CUBLAS
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const int max_backend_supported_layers = hparams.n_layer + 3;
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const int max_offloadable_layers = low_vram ? hparams.n_layer + 1 : hparams.n_layer + 3;
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if (n_gpu_layers > (int) hparams.n_layer + 1) {
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if (low_vram) {
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fprintf(stderr, "%s: cannot offload v cache to GPU due to low VRAM option\n", __func__);
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@ -1180,14 +1185,18 @@ static void llama_model_load_internal(
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vram_kv_cache += MEM_REQ_KV_SELF().at(model.type) / 2;
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}
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}
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const int max_offloadable_layers = low_vram ? hparams.n_layer + 1 : hparams.n_layer + 3;
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#elif defined(GGML_USE_CLBLAST)
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const int max_backend_supported_layers = hparams.n_layer + 1;
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const int max_offloadable_layers = hparams.n_layer + 1;
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#endif // GGML_USE_CUBLAS
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fprintf(stderr, "%s: offloaded %d/%d layers to GPU\n",
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__func__, std::min(n_gpu_layers, max_offloadable_layers), hparams.n_layer + 3);
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__func__, std::min(n_gpu_layers, max_offloadable_layers), max_backend_supported_layers);
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fprintf(stderr, "%s: total VRAM used: %zu MB\n",
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__func__, (vram_weights + vram_scratch + vram_kv_cache + MB - 1) / MB); // round up
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#else
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(void) n_gpu_layers;
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#endif
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#endif // defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST)
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}
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// populate `tensors_by_name`
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