feat(train_page): 启动 TensorBoard 进程并确保训练结束后终止

- 在训练页面中添加 TensorBoard 进程启动代码
- 创建日志目录并启动 TensorBoard 子进程
- 在训练结束后终止 TensorBoard 进程

frontend/train_page.py

@@ -1,3 +1,4 @@
+import subprocess
 import os
 import gradio as gr
 import sys
@@ -55,10 +56,25 @@ def train_page():
             next_dir_number = max([int(d) for d in existing_dirs], default=0) + 1
             new_training_dir = os.path.join(training_dir, str(next_dir_number))
 
-            train_model(get_model(), get_tokenizer(),
+            # 启动 TensorBoard 子进程
-                        dataset, new_training_dir, 
+            tensorboard_logdir = os.path.join(new_training_dir, "logs")
-                        learning_rate, per_device_train_batch_size, epoch,
+            os.makedirs(tensorboard_logdir, exist_ok=True)  # 确保日志目录存在
-                        save_steps, lora_rank)
+            tensorboard_process = subprocess.Popen(
+                ["tensorboard", "--logdir", tensorboard_logdir, "--port", "6006"],
+                stdout=subprocess.PIPE,
+                stderr=subprocess.PIPE
+            )
+            print("TensorBoard 已启动，日志目录:", tensorboard_logdir)
+
+            try:
+                train_model(get_model(), get_tokenizer(),
+                            dataset, new_training_dir, 
+                            learning_rate, per_device_train_batch_size, epoch,
+                            save_steps, lora_rank)
+            finally:
+                # 确保训练结束后终止 TensorBoard 子进程
+                tensorboard_process.terminate()
+                print("TensorBoard 子进程已终止")
 
         train_button.click(
             fn=start_training,