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reduce some spamminess
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+4
-3
@@ -1280,7 +1280,8 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
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bool use_mmap_buffer = true;
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LLAMA_LOG_INFO("%s: loading model tensors, this can take a while... (mmap = %s)\n", __func__, use_mmap_buffer ? "true" : "false");
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LLAMA_LOG_INFO("%s: loading model tensors, this can take a while...", __func__);
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// LLAMA_LOG_INFO("%s: loading model tensors, this can take a while... (mmap = %s)\n", __func__, use_mmap_buffer ? "true" : "false");
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// build a list of buffer types for the CPU and GPU devices
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pimpl->cpu_buft_list = make_cpu_buft_list(devices);
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@@ -1328,12 +1329,12 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
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const int act_gpu_layers = devices.empty() ? 0 : std::min(n_gpu_layers, (int)n_layer + 1);
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auto get_layer_buft_list = [&](int il) -> llama_model::impl::layer_dev {
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if (il < i_gpu_start || (il - i_gpu_start) >= act_gpu_layers) {
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LLAMA_LOG_DEBUG("load_tensors: layer %3d assigned to device %s\n", il, ggml_backend_dev_name(cpu_dev));
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// LLAMA_LOG_DEBUG("load_tensors: layer %3d assigned to device %s\n", il, ggml_backend_dev_name(cpu_dev));
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return {cpu_dev, &pimpl->cpu_buft_list};
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}
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const int layer_gpu = std::upper_bound(splits.begin(), splits.begin() + n_devices(), float(il - i_gpu_start)/act_gpu_layers) - splits.begin();
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auto * dev = devices.at(layer_gpu);
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LLAMA_LOG_DEBUG("load_tensors: layer %3d assigned to device %s\n", il, ggml_backend_dev_name(dev));
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// LLAMA_LOG_DEBUG("load_tensors: layer %3d assigned to device %s\n", il, ggml_backend_dev_name(dev));
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return {dev, &pimpl->gpu_buft_list.at(dev)};
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};
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