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https://github.com/Lizonghang/prima.cpp.git
synced 2025-09-05 20:09:10 +00:00
fix n_embd cannot be divided by quantized block size
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2 changed files with 32 additions and 5 deletions
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@ -1588,6 +1588,7 @@ struct llama_init_result llama_init_from_gpt_params(gpt_params & params) {
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if (n_world == 1) {
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uint32_t n_layers = llama_model_n_layers(model);
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// assign all layers to this device
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params.n_layer_window[0] = n_layers;
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cparams.n_layer_window[0] = n_layers;
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@ -1596,6 +1597,8 @@ struct llama_init_result llama_init_from_gpt_params(gpt_params & params) {
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#if defined(GGML_USE_METAL) || defined(GGML_USE_CUDA)
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params.n_gpu_layers = std::min((int32_t)n_layers, params.n_gpu_layers);
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cparams.n_gpu_layers = params.n_gpu_layers;
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mparams.n_gpu_layers = params.n_gpu_layers;
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#endif
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} else {
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@ -48,6 +48,16 @@
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#include <dirent.h>
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static int gcd_int(int a, int b) {
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while (b != 0) {
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int t = b;
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b = a % b;
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a = t;
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}
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return a;
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}
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static size_t get_page_size() {
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size_t page_size = 0;
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@ -154,8 +164,25 @@ uint32_t device_cpu_cores() {
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static float device_flops(struct llama_model * model, enum ggml_type src0t, enum ggml_type src1t, enum profiler_backend_type btype, int n_threads) {
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int n_repeat = 1;
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int n_embd = std::min(llama_n_embd(model), 4096);
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if (btype == PROFILER_BACKEND_TYPE_CPU) n_embd /= 8; // simulate small tensor calculation on cpu
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int n_embd = std::min(llama_n_embd(model), 4096);
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// simulate small tensor calculation on cpu
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if (btype == PROFILER_BACKEND_TYPE_CPU) n_embd /= 8;
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// ensure that the block sizes of the tensors are compatible
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int bs0 = ggml_blck_size(src0t);
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int bs1 = ggml_blck_size(src1t);
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int gcd = gcd_int(bs0, bs1);
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int lcm = bs0 / gcd * bs1;
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if (n_embd % bs0 != 0 || n_embd % bs1 != 0) {
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if (n_embd < lcm) {
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n_embd = 2 * lcm;
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} else {
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n_embd = 2 * (n_embd / lcm) * lcm;
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}
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}
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std::vector<float> matrix_A(n_embd * n_embd, 1.0f);
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std::vector<float> matrix_B(n_embd * n_embd, 1.0f / n_embd);
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@ -188,9 +215,6 @@ static float device_flops(struct llama_model * model, enum ggml_type src0t, enum
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};
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struct ggml_context * ctx = ggml_init(params);
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if(n_embd < ggml_blck_size(src0t)){
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n_embd = 2 * ggml_blck_size(src0t);
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}
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struct ggml_tensor * tensor_a = ggml_new_tensor_2d(ctx, src0t, n_embd, n_embd);
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struct ggml_tensor * tensor_b = ggml_new_tensor_2d(ctx, src1t, n_embd, n_embd);
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