bench: add --tensor-read-lazy (#27881)
* bench: add --tensor-read-lazy * rm the alias * rename to LLAMA_LAZY_MODE_*
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@@ -214,10 +214,10 @@ extern "C" {
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LLAMA_API const char * llama_load_mode_name(enum llama_load_mode load_mode);
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LLAMA_API enum llama_load_mode llama_load_mode_from_str(const char * str);
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enum llama_tensor_read_lazy {
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LLAMA_TENSOR_READ_LAZY_OFF = 0, // always read the whole tensor up front
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LLAMA_TENSOR_READ_LAZY_AUTO = 1, // lazy only for marked tensors larger than 4 GiB (requires mmap)
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LLAMA_TENSOR_READ_LAZY_ON = 2, // read the rows of tensors marked by the arch on demand (requires mmap)
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enum llama_lazy_mode {
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LLAMA_LAZY_MODE_OFF = 0, // always read the whole tensor up front
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LLAMA_LAZY_MODE_AUTO = 1, // lazy only for marked tensors larger than 4 GiB (requires mmap)
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LLAMA_LAZY_MODE_ON = 2, // read the rows of tensors marked by the arch on demand (requires mmap)
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};
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enum llama_context_type {
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@@ -321,7 +321,7 @@ extern "C" {
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enum llama_split_mode split_mode; // how to split the model across multiple GPUs
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enum llama_load_mode load_mode; // how to load the model
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enum llama_tensor_read_lazy tensor_read_lazy; // on-demand reading of tensors marked by the arch
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enum llama_lazy_mode lazy_mode; // on-demand reading of tensors marked by the arch
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// the GPU that is used for the entire model when split_mode is LLAMA_SPLIT_MODE_NONE
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int32_t main_gpu;
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