update webUI, fix #179

Former-commit-id: f9074fed5e22585679661588befcf266a79009f2

src/llmtuner/webui/utils.py

@@ -3,7 +3,7 @@ import json
 import gradio as gr
 import matplotlib.figure
 import matplotlib.pyplot as plt
-from typing import Tuple
+from typing import Any, Dict, Tuple
 from datetime import datetime
 
 from llmtuner.extras.ploting import smooth
@@ -23,7 +23,7 @@ def get_time() -> str:
     return datetime.now().strftime('%Y-%m-%d-%H-%M-%S')
 
 
-def can_preview(dataset_dir: str, dataset: list) -> dict:
+def can_preview(dataset_dir: str, dataset: list) -> Dict[str, Any]:
     with open(os.path.join(dataset_dir, DATA_CONFIG), "r", encoding="utf-8") as f:
         dataset_info = json.load(f)
     if (
@@ -36,7 +36,7 @@ def can_preview(dataset_dir: str, dataset: list) -> dict:
         return gr.update(interactive=False)
 
 
-def get_preview(dataset_dir: str, dataset: list) -> Tuple[int, list, dict]:
+def get_preview(dataset_dir: str, dataset: list) -> Tuple[int, list, Dict[str, Any]]:
     with open(os.path.join(dataset_dir, DATA_CONFIG), "r", encoding="utf-8") as f:
         dataset_info = json.load(f)
     data_file = dataset_info[dataset[0]]["file_name"]
@@ -45,6 +45,13 @@ def get_preview(dataset_dir: str, dataset: list) -> Tuple[int, list, dict]:
     return len(data), data[:2], gr.update(visible=True)
 
 
+def can_quantize(finetuning_type: str) -> Dict[str, Any]:
+    if finetuning_type != "lora":
+        return gr.update(value="", interactive=False)
+    else:
+        return gr.update(interactive=True)
+
+
 def get_eval_results(path: os.PathLike) -> str:
     with open(path, "r", encoding="utf-8") as f:
         result = json.dumps(json.load(f), indent=4)
@@ -66,6 +73,10 @@ def gen_plot(base_model: str, finetuning_type: str, output_dir: str) -> matplotl
             if log_info.get("loss", None):
                 steps.append(log_info["current_steps"])
                 losses.append(log_info["loss"])
+
+    if len(losses) == 0:
+        return None
+
     ax.plot(steps, losses, alpha=0.4, label="original")
     ax.plot(steps, smooth(losses), label="smoothed")
     ax.legend()