Update api/mdm_loader.py

api/mdm_loader.py

@@ -1,25 +1,25 @@
-import torch
-from mdm_repo.utils.model_util import create_model_and_diffusion, load_saved_model
-from mdm_repo.utils.parser_util import generate_args
-import os
-
-# Load once on startup
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-
-# Load args.json from models directory
-args_path = os.path.join(os.path.dirname(__file__), "..", "models", "args.json")
-args = generate_args()
-if os.path.exists(args_path):
-    import json
-    with open(args_path, "r") as f:
-        args.__dict__.update(json.load(f))
-
-model, diffusion = create_model_and_diffusion(args, data=None)
-model = load_saved_model(model, "models/model000475000.pt")
-model.to(device)
-model.eval()
-
-def generate_motion(prompt: str, num_frames: int, style: str = "default"):
-    # TODO: Implement motion generation using MDM repo's sampling logic
-    # See mdm_repo/sample/generate.py for reference
-    raise NotImplementedError("Motion generation logic needs to be implemented using MDM repo's sampling code.")
+import torch
+from utils.model_util import create_model_and_diffusion, load_saved_model
+from utils.parser_util import generate_args
+import os
+
+# Load once on startup
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+# Load args.json from models directory
+args_path = os.path.join(os.path.dirname(__file__), "..", "models", "args.json")
+args = generate_args()
+if os.path.exists(args_path):
+    import json
+    with open(args_path, "r") as f:
+        args.__dict__.update(json.load(f))
+
+model, diffusion = create_model_and_diffusion(args, data=None)
+model = load_saved_model(model, "models/model000475000.pt")
+model.to(device)
+model.eval()
+
+def generate_motion(prompt: str, num_frames: int, style: str = "default"):
+    # TODO: Implement motion generation using MDM repo's sampling logic
+    # See mdm_repo/sample/generate.py for reference
+    raise NotImplementedError("Motion generation logic needs to be implemented using MDM repo's sampling code.")