add retry to avoid runtime error

app.py

@@ -199,6 +199,18 @@ def load_javascript(dir="javascript"):
     gr.routes.templates.TemplateResponse = template_response
 
 
+def hf_hub_download_retry(repo_id, filename):
+    retry = 0
+    err = None
+    while retry < 30:
+        try:
+            return hf_hub_download(repo_id=repo_id, filename=filename)
+        except Exception as e:
+            err = e
+            retry += 1
+    if err:
+        raise err
+
 number2drum_kits = {-1: "None", 0: "Standard", 8: "Room", 16: "Power", 24: "Electric", 25: "TR-808", 32: "Jazz",
                     40: "Blush", 48: "Orchestra"}
 patch2number = {v: k for k, v in MIDI.Number2patch.items()}
@@ -210,7 +222,7 @@ if __name__ == "__main__":
     parser.add_argument("--port", type=int, default=7860, help="gradio server port")
     parser.add_argument("--max-gen", type=int, default=1024, help="max")
     opt = parser.parse_args()
-    soundfont_path = hf_hub_download(repo_id="skytnt/midi-model", filename="soundfont.sf2")
+    soundfont_path = hf_hub_download_retry(repo_id="skytnt/midi-model", filename="soundfont.sf2")
     models_info = {"generic pretrain model": ["skytnt/midi-model", ""],
                    "j-pop finetune model": ["skytnt/midi-model-ft", "jpop/"],
                    "touhou finetune model": ["skytnt/midi-model-ft", "touhou/"],
@@ -219,8 +231,8 @@ if __name__ == "__main__":
     tokenizer = MIDITokenizer()
     providers = ['CUDAExecutionProvider', 'CPUExecutionProvider']
     for name, (repo_id, path) in models_info.items():
-        model_base_path = hf_hub_download(repo_id=repo_id, filename=f"{path}onnx/model_base.onnx")
-        model_token_path = hf_hub_download(repo_id=repo_id, filename=f"{path}onnx/model_token.onnx")
+        model_base_path = hf_hub_download_retry(repo_id=repo_id, filename=f"{path}onnx/model_base.onnx")
+        model_token_path = hf_hub_download_retry(repo_id=repo_id, filename=f"{path}onnx/model_token.onnx")
         model_base = rt.InferenceSession(model_base_path, providers=providers)
         model_token = rt.InferenceSession(model_token_path, providers=providers)
         models[name] = [model_base, model_token]