feat: show tensor loading progress in MB/s or GB/s

src/model.cpp

@@ -1311,6 +1311,7 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, int n_thread
     std::atomic<int64_t> memcpy_time_ms(0);
     std::atomic<int64_t> copy_to_backend_time_ms(0);
     std::atomic<int64_t> convert_time_ms(0);
+    std::atomic<uint64_t> bytes_processed(0);
 
     int num_threads_to_use = n_threads_p > 0 ? n_threads_p : sd_get_num_physical_cores();
     LOG_DEBUG("using %d threads for model loading", num_threads_to_use);
@@ -1522,6 +1523,8 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, int n_thread
                         t1 = ggml_time_ms();
                         copy_to_backend_time_ms.fetch_add(t1 - t0);
                     }
+
+                    bytes_processed.fetch_add((uint64_t)nbytes_to_read);
                 }
                 if (zip != nullptr) {
                     zip_close(zip);
@@ -1534,8 +1537,12 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, int n_thread
             if (current_idx >= file_tensors.size() || failed) {
                 break;
             }
-            size_t curr_num = total_tensors_processed + current_idx;
-            pretty_progress(static_cast<int>(curr_num), static_cast<int>(total_tensors_to_process), (ggml_time_ms() - t_start) / 1000.0f / (curr_num + 1e-6f));
+            size_t curr_num       = total_tensors_processed + current_idx;
+            float elapsed_seconds = (ggml_time_ms() - t_start) / 1000.0f;
+            pretty_bytes_progress(static_cast<int>(curr_num),
+                                  static_cast<int>(total_tensors_to_process),
+                                  bytes_processed.load(),
+                                  elapsed_seconds);
             std::this_thread::sleep_for(std::chrono::milliseconds(200));
         }
 
@@ -1548,7 +1555,10 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, int n_thread
             break;
         }
         total_tensors_processed += file_tensors.size();
-        pretty_progress(static_cast<int>(total_tensors_processed), static_cast<int>(total_tensors_to_process), (ggml_time_ms() - t_start) / 1000.0f / (total_tensors_processed + 1e-6f));
+        pretty_bytes_progress(static_cast<int>(total_tensors_processed),
+                              static_cast<int>(total_tensors_to_process),
+                              bytes_processed.load(),
+                              (ggml_time_ms() - t_start) / 1000.0f);
         if (total_tensors_processed < total_tensors_to_process) {
             printf("\n");
         }

src/util.cpp

@@ -337,17 +337,13 @@ std::vector<std::string> split_string(const std::string& str, char delimiter) {
     return result;
 }
 
-void pretty_progress(int step, int steps, float time) {
-    if (sd_progress_cb) {
-        sd_progress_cb(step, steps, time, sd_progress_cb_data);
-        return;
-    }
-    if (step == 0) {
-        return;
-    }
+static std::string build_progress_bar(int step, int steps) {
     std::string progress = "  |";
     int max_progress     = 50;
-    int32_t current      = (int32_t)(step * 1.f * max_progress / steps);
+    int32_t current      = 0;
+    if (steps > 0) {
+        current = (int32_t)(step * 1.f * max_progress / steps);
+    }
     for (int i = 0; i < 50; i++) {
         if (i > current) {
             progress += " ";
@@ -358,16 +354,57 @@ void pretty_progress(int step, int steps, float time) {
         }
     }
     progress += "|";
+    return progress;
+}
 
-    const char* lf   = (step == steps ? "\n" : "");
+static void print_progress_line(int step, int steps, const std::string& speed_text) {
+    if (step == 0) {
+        return;
+    }
+    std::string progress = build_progress_bar(step, steps);
+    const char* lf       = (step == steps ? "\n" : "");
+    printf("\r%s %i/%i - %s\033[K%s", progress.c_str(), step, steps, speed_text.c_str(), lf);
+    fflush(stdout);  // for linux
+}
+
+void pretty_progress(int step, int steps, float time) {
+    if (sd_progress_cb) {
+        sd_progress_cb(step, steps, time, sd_progress_cb_data);
+        return;
+    }
+    if (step == 0) {
+        return;
+    }
     const char* unit = "s/it";
     float speed      = time;
     if (speed < 1.0f && speed > 0.f) {
         speed = 1.0f / speed;
         unit  = "it/s";
     }
-    printf("\r%s %i/%i - %.2f%s\033[K%s", progress.c_str(), step, steps, speed, unit, lf);
-    fflush(stdout);  // for linux
+    print_progress_line(step, steps, sd_format("%.2f%s", speed, unit));
+}
+
+void pretty_bytes_progress(int step, int steps, uint64_t bytes_processed, float elapsed_seconds) {
+    if (sd_progress_cb) {
+        float time = elapsed_seconds / (step + 1e-6f);
+        sd_progress_cb(step, steps, time, sd_progress_cb_data);
+        return;
+    }
+    if (step == 0) {
+        return;
+    }
+
+    double bytes_per_second = 0.0;
+    if (elapsed_seconds > 0.0f) {
+        bytes_per_second = bytes_processed / (double)elapsed_seconds;
+    }
+
+    double speed_mb = bytes_per_second / (1024.0 * 1024.0);
+    if (speed_mb >= 1024.0) {
+        print_progress_line(step, steps, sd_format("%.2fGB/s", speed_mb / 1024.0));
+    } else {
+        print_progress_line(step, steps, sd_format("%.2fMB/s", speed_mb));
+    }
 }
 
 std::string ltrim(const std::string& s) {

src/util.h

@@ -64,6 +64,7 @@ class MmapWrapper {
 std::string path_join(const std::string& p1, const std::string& p2);
 std::vector<std::string> split_string(const std::string& str, char delimiter);
 void pretty_progress(int step, int steps, float time);
+void pretty_bytes_progress(int step, int steps, uint64_t bytes_processed, float elapsed_seconds);
 
 void log_printf(sd_log_level_t level, const char* file, int line, const char* format, ...);