llama-fit-params: free memory target per device (#18679)
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-6
@@ -332,12 +332,14 @@ struct common_params {
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// offload params
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std::vector<ggml_backend_dev_t> devices; // devices to use for offloading
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int32_t n_gpu_layers = -1; // number of layers to store in VRAM, -1 is auto, <= -2 is all
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int32_t main_gpu = 0; // the GPU that is used for scratch and small tensors
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float tensor_split[128] = {0}; // how split tensors should be distributed across GPUs
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bool fit_params = true; // whether to fit unset model/context parameters to free device memory
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size_t fit_params_target = 1024 * 1024*1024; // margin per device in bytes for fitting parameters to free memory
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int32_t fit_params_min_ctx = 4096; // minimum context size to set when trying to reduce memory use
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int32_t n_gpu_layers = -1; // number of layers to store in VRAM, -1 is auto, <= -2 is all
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int32_t main_gpu = 0; // the GPU that is used for scratch and small tensors
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float tensor_split[128] = {0}; // how split tensors should be distributed across GPUs
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bool fit_params = true; // whether to fit unset model/context parameters to free device memory
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int32_t fit_params_min_ctx = 4096; // minimum context size to set when trying to reduce memory use
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// margin per device in bytes for fitting parameters to free memory:
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std::vector<size_t> fit_params_target = std::vector<size_t>(llama_max_devices(), 1024 * 1024*1024);
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enum llama_split_mode split_mode = LLAMA_SPLIT_MODE_LAYER; // how to split the model across GPUs
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