llama: model_loader: add TENSOR_READ_LAZY (#27794)
* llama: model_loader: add TENSOR_GET_ROW_LAZY * add --tensor-read-lazy * rename to TENSOR_READ_LAZY * gen docs * address comments
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@@ -2720,6 +2720,19 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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else { throw std::invalid_argument("invalid value"); }
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}
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).set_env("LLAMA_ARG_LOAD_MODE"));
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add_opt(common_arg(
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{"--tensor-read-lazy"}, "MODE",
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"on-demand reading of certain tensors, for example per-layer embeddings (default: auto)\n"
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"- on: read the rows of such tensors from disk on demand instead of keeping them resident (requires mmap)\n"
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"- auto: on, but only for tensors larger than 4 GiB\n"
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"- off: always keep them resident",
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[](common_params & params, const std::string & value) {
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/**/ if (value == "on") { params.tensor_read_lazy = LLAMA_TENSOR_READ_LAZY_ON; }
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else if (value == "auto") { params.tensor_read_lazy = LLAMA_TENSOR_READ_LAZY_AUTO; }
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else if (value == "off") { params.tensor_read_lazy = LLAMA_TENSOR_READ_LAZY_OFF; }
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else { throw std::invalid_argument("invalid value"); }
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}
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).set_env("LLAMA_ARG_TENSOR_READ_LAZY"));
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add_opt(common_arg(
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{"--numa"}, "TYPE",
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"attempt optimizations that help on some NUMA systems\n"
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@@ -1688,6 +1688,7 @@ struct llama_model_params common_model_params_to_llama(common_params & params) {
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mparams.main_gpu = params.main_gpu;
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mparams.split_mode = params.split_mode;
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mparams.load_mode = params.load_mode;
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mparams.tensor_read_lazy = params.tensor_read_lazy;
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mparams.tensor_split = params.tensor_split;
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mparams.check_tensors = params.check_tensors;
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mparams.use_extra_bufts = !params.no_extra_bufts;
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@@ -483,6 +483,8 @@ struct common_params {
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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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enum llama_load_mode load_mode = LLAMA_LOAD_MODE_AUTO; // how to load the model
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enum llama_tensor_read_lazy tensor_read_lazy = LLAMA_TENSOR_READ_LAZY_AUTO; // on-demand reading of tensors marked by the arch
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common_cpu_params cpuparams;
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common_cpu_params cpuparams_batch;
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