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llama : do not print "offloading layers" message in CPU-only builds (#5416)

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slaren 2024-02-08 21:33:03 +01:00 committed by GitHub
parent 6e99f2a04f
commit 41f308f58e
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1 changed files with 5 additions and 5 deletions
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llama.cpp
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@ -4209,8 +4209,7 @@ static bool llm_load_tensors(
ctx_bufs.emplace_back(ctx, buf); ctx_bufs.emplace_back(ctx, buf);
} }
// print memory requirements if (llama_supports_gpu_offload()) {
{
const int n_gpu = std::min(n_gpu_layers, int(hparams.n_layer)); const int n_gpu = std::min(n_gpu_layers, int(hparams.n_layer));
LLAMA_LOG_INFO("%s: offloading %d repeating layers to GPU\n", __func__, n_gpu); LLAMA_LOG_INFO("%s: offloading %d repeating layers to GPU\n", __func__, n_gpu);
@ -4222,10 +4221,11 @@ static bool llm_load_tensors(
const int max_offloadable_layers = hparams.n_layer + 1; const int max_offloadable_layers = hparams.n_layer + 1;
LLAMA_LOG_INFO("%s: offloaded %d/%d layers to GPU\n", __func__, std::min(n_gpu_layers, max_offloadable_layers), max_backend_supported_layers); LLAMA_LOG_INFO("%s: offloaded %d/%d layers to GPU\n", __func__, std::min(n_gpu_layers, max_offloadable_layers), max_backend_supported_layers);
}
for (ggml_backend_buffer_t buf : model.bufs) { // print memory requirements
LLAMA_LOG_INFO("%s: %10s buffer size = %8.2f MiB\n", __func__, ggml_backend_buffer_name(buf), ggml_backend_buffer_get_size(buf) / 1024.0 / 1024.0); for (ggml_backend_buffer_t buf : model.bufs) {
} LLAMA_LOG_INFO("%s: %10s buffer size = %8.2f MiB\n", __func__, ggml_backend_buffer_name(buf), ggml_backend_buffer_get_size(buf) / 1024.0 / 1024.0);
} }
// populate tensors_by_name // populate tensors_by_name