nada

app.py

@@ -15,19 +15,16 @@ from huggingface_hub import snapshot_download
 weights_dir = './allegro_weights'
 os.makedirs(weights_dir, exist_ok=True)
 
-# Check if running in a shared UI environment
-is_shared_ui = "rhymes-ai-Allegro-textToVideo" in os.environ.get('SPACE_ID', "")
-is_gpu_associated = torch.cuda.is_available()
 
 # Download the necessary model files if not in shared UI
-if not is_shared_ui:
-    print(f"Downloading models to {weights_dir}...")
-    snapshot_download(
-        repo_id='rhymes-ai/Allegro',
-        local_dir=weights_dir,
-        allow_patterns=['**']  # Download all required files
-    )
-    print(f"Downloaded models to {weights_dir}.")
+
+print(f"Downloading models to {weights_dir}...")
+snapshot_download(
+    repo_id='rhymes-ai/Allegro',
+    local_dir=weights_dir,
+    allow_patterns=['**']
+    
+print(f"Downloaded models to {weights_dir}.")
 
 # Check if the directories exist
 required_dirs = ['vae', 'text_encoder', 'tokenizer', 'scheduler', 'transformer']
@@ -38,9 +35,7 @@ if missing_dirs:
 else:
     print(f"All required directories are present in {weights_dir}.")
 
-if is_gpu_associated:
-    gpu_info = getoutput('nvidia-smi')
-    print(f"GPU Info: {gpu_info}")
+
 
 # Check directory structure
 required_dirs = ['vae', 'text_encoder', 'tokenizer', 'scheduler', 'transformer']
@@ -50,6 +45,11 @@ if missing_dirs:
 
 @spaces.GPU(duration=120)  # Request GPU for the entire process
 def process_pipeline(user_prompt, guidance_scale, num_sampling_steps, seed, enable_cpu_offload):
+#    is_gpu_associated = torch.cuda.is_available()
+#    if is_gpu_associated:
+#        gpu_info = getoutput('nvidia-smi')
+#        print(f"GPU Info: {gpu_info}")
+
     # Define dtype
     dtype = torch.bfloat16