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fix dinov3

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Pepijn
2025-08-31 19:44:27 +02:00
parent e1d433cbfc
commit 79c3466f0f
1 changed files with 1 additions and 3 deletions
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src/lerobot/policies/rlearn/modeling_rlearn.py
+1 -3
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@@ -377,9 +377,7 @@ class RLearNPolicy(PreTrainedPolicy):
inputs = {k: v.to(device) for k, v in inputs.items()} inputs = {k: v.to(device) for k, v in inputs.items()}
# Process in batch through DINOv3 model # Process in batch through DINOv3 model
# Use inference mode for stable, fast frozen encoder forward vision_outputs = self.vision_model(**inputs)
with torch.inference_mode():
vision_outputs = self.vision_model(**inputs)
# Prefer mean-pooled patch tokens over pooler/CLS to ensure input-dependent variation # Prefer mean-pooled patch tokens over pooler/CLS to ensure input-dependent variation
if hasattr(vision_outputs, 'last_hidden_state') and vision_outputs.last_hidden_state is not None: if hasattr(vision_outputs, 'last_hidden_state') and vision_outputs.last_hidden_state is not None: