fit : wrap llama_device_memory_data (#24522)

diff --git a/common/fit.cpp b/common/fit.cpp
index 668d892e908c7aa9ee9ac4787b8f5dc29eb941bd..a8565bfc9123cfee2cd9a181cd709757937f037a 100644 (file)
--- a/common/fit.cpp
+++ b/common/fit.cpp
@@ -26,7 +26,7 @@ class common_params_fit_exception : public std::runtime_error {
     using std::runtime_error::runtime_error;
 };
 
-std::vector<llama_device_memory_data> common_get_device_memory_data(
+static std::vector<llama_device_memory_data> common_get_device_memory_data_impl(
         const char * path_model,
         const llama_model_params * mparams,
         const llama_context_params * cparams,
@@ -150,6 +150,29 @@ std::vector<llama_device_memory_data> common_get_device_memory_data(
     return ret;
 }
 
+common_device_memory_data_vec common_get_device_memory_data(
+        const char * path_model,
+        const llama_model_params * mparams,
+        const llama_context_params * cparams,
+        std::vector<ggml_backend_dev_t> & devs,
+        uint32_t & hp_ngl,
+        uint32_t & hp_n_ctx_train,
+        uint32_t & hp_n_expert,
+        ggml_log_level log_level) {
+    std::vector<llama_device_memory_data> impl = common_get_device_memory_data_impl(
+            path_model, mparams, cparams, devs, hp_ngl, hp_n_ctx_train, hp_n_expert, log_level);
+
+    common_device_memory_data_vec ret(impl.size());
+    for (size_t i = 0; i < impl.size(); i++) {
+        ret[i].total   = impl[i].total;
+        ret[i].free    = impl[i].free;
+        ret[i].model   = impl[i].mb.model;
+        ret[i].context = impl[i].mb.context;
+        ret[i].compute = impl[i].mb.compute;
+    }
+    return ret;
+}
+
 static void common_params_fit_impl(
         const char * path_model, struct llama_model_params * mparams, struct llama_context_params * cparams,
         float * tensor_split, struct llama_model_tensor_buft_override * tensor_buft_overrides,
@@ -169,7 +192,7 @@ static void common_params_fit_impl(
     // step 1: get data for default parameters and check whether any changes are necessary in the first place
 
     LOG_TRC("%s: getting device memory data for initial parameters:\n", __func__);
-    const dmds_t dmds_full = common_get_device_memory_data(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
+    const dmds_t dmds_full = common_get_device_memory_data_impl(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
     const size_t nd = devs.size(); // number of devices
 
     std::vector<int64_t> margins; // this function uses int64_t rather than size_t for memory sizes to more conveniently handle deficits
@@ -304,7 +327,7 @@ static void common_params_fit_impl(
 
                     int64_t sum_projected_used_min_ctx = 0;
                     cparams->n_ctx = n_ctx_min;
-                    const dmds_t dmds_min_ctx = common_get_device_memory_data(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
+                    const dmds_t dmds_min_ctx = common_get_device_memory_data_impl(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
                     if (nd == 0) {
                         sum_projected_used_min_ctx = dmds_min_ctx.back().mb.total();
                     } else {
@@ -482,7 +505,7 @@ static void common_params_fit_impl(
         llama_model_params mparams_copy = *mparams;
         set_ngl_tensor_split_tbo(ngl_per_device, overflow_bufts, mparams_copy);
 
-        const dmds_t dmd_nl = common_get_device_memory_data(
+        const dmds_t dmd_nl = common_get_device_memory_data_impl(
             path_model, &mparams_copy, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
 
         LOG_TRC("%s: memory for test allocation by device:\n", func_name);
@@ -510,7 +533,7 @@ static void common_params_fit_impl(
         mparams->tensor_buft_overrides = tensor_buft_overrides;
 
         LOG_TRC("%s: getting device memory data with all MoE tensors moved to system memory:\n", __func__);
-        const dmds_t dmds_cpu_moe = common_get_device_memory_data(
+        const dmds_t dmds_cpu_moe = common_get_device_memory_data_impl(
             path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level);
 
         for (size_t id = 0; id < nd; id++) {
@@ -940,7 +963,7 @@ void common_fit_print(
     uint32_t hp_nct = 0; // hparams.n_ctx_train
     uint32_t hp_nex = 0; // hparams.n_expert
 
-    auto dmd = common_get_device_memory_data(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, GGML_LOG_LEVEL_ERROR);
+    auto dmd = common_get_device_memory_data_impl(path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, GGML_LOG_LEVEL_ERROR);
     GGML_ASSERT(dmd.size() == devs.size() + 1);
 
     for (size_t id = 0; id < devs.size(); id++) {

diff --git a/common/fit.h b/common/fit.h
index a6ba71b89ecc3dd74e3218a1157b946ed9548043..208fc30694e0375db281c8d5466bf1402ce0ea36 100644 (file)
--- a/common/fit.h
+++ b/common/fit.h
@@ -34,12 +34,18 @@ void common_fit_print(
 
 void common_memory_breakdown_print(const llama_context * ctx);
 
-// TODO: convert this to common_device_memory_data that wraps llama_device_memory_data
-//       add API for accessing the internal `llama-ext.h` information
-struct llama_device_memory_data;
+struct common_device_memory_data {
+    int64_t total;
+    int64_t free;
+    size_t  model;
+    size_t  context;
+    size_t  compute;
+};
+
+using common_device_memory_data_vec = std::vector<common_device_memory_data>;
 
 // Load a model + context with no_alloc and return the per-device memory breakdown.
-std::vector<llama_device_memory_data> common_get_device_memory_data(
+common_device_memory_data_vec common_get_device_memory_data(
                          const char * path_model,
            const llama_model_params * mparams,
          const llama_context_params * cparams,

diff --git a/tools/server/server-context.cpp b/tools/server/server-context.cpp
index 595fc219b28ca9fce9925ef0d6f65dd2b6737db9..986b2f15d59a9581bff93c6ef790f16da46cf0ca 100644 (file)
--- a/tools/server/server-context.cpp
+++ b/tools/server/server-context.cpp
@@ -962,10 +962,7 @@ private:
                     }
 
                     for (size_t j = 0; j < devs.size(); ++j) {
-                        const size_t bytes =
-                            (measure_model_bytes ? dmd[j].mb.model : 0) +
-                            dmd[j].mb.context +
-                            dmd[j].mb.compute;
+                        const size_t bytes = (measure_model_bytes ? dmd[j].model : 0) + dmd[j].context + dmd[j].compute;
                         total += bytes;
                         for (size_t i = 0; i < tgt_devices.size(); i++) {
                             if (tgt_devices[i] == devs[j]) {