FIXED RuntimeError: CUDA has been initialized before importing the `spaces` package (#4)

- FIXED RuntimeError: CUDA has been initialized before importing the `spaces` package (aeacaa2ba716f4681d7a47957b319c5a96c28e22)


Co-authored-by: Xi <[email protected]>

app.py

@@ -1,8 +1,10 @@
+import spaces
 import gradio as gr
 import torch
 torch.jit.script = lambda f: f  # Avoid script error in lambda
 from t2v_metrics import VQAScore, list_all_vqascore_models
 
+
 def update_model(model_name):
     return VQAScore(model=model_name, device="cuda")
 
@@ -11,13 +13,19 @@ global model_pipe, cur_model_name
 cur_model_name = "clip-flant5-xl"
 model_pipe = update_model(cur_model_name)
 
-# Ensure GPU context manager is imported correctly (assuming spaces is a module you have)
-try:
-    from spaces import GPU
-except ImportError:
-    GPU = lambda duration: (lambda f: f)  # Dummy decorator if spaces.GPU is not available
 
-@GPU(duration=20)
+# Ensure GPU context manager is imported correctly (assuming spaces is a module you have)
+#try:
+    #from spaces import GPU # i believe this is wrong, spaces package does not have "GPU"
+#except ImportError:
+    # GPU = lambda duration: (lambda f: f)  # Dummy decorator if spaces.GPU is not available
+
+if torch.cuda.is_available():
+    model_pipe.device = "cuda"
+else:
+    print("CUDA is not available")
+    
+@spaces.GPU # a duration lower than 60 does not work, leave as is.
 def generate(model_name, image, text):
     global model_pipe, cur_model_name
     
@@ -38,7 +46,7 @@ def generate(model_name, image, text):
     
     return result
 
-@GPU(duration=20)
+
 def rank_images(model_name, images, text):
     global model_pipe, cur_model_name