fix abolute

examples/openarms/evaluate_ee.py

@@ -335,24 +335,31 @@ def run_ee_inference_loop(
                 batch[key] = batch[key].unsqueeze(0)
         
         with torch.inference_mode():
-            action = policy.select_action(batch)
+            action_tensor = policy.select_action(batch)
         
-        # 5. Postprocess to get EE action
-        ee_action = postprocessor(action)
+        # 5. Postprocess and convert tensor to dict
+        action_tensor = postprocessor(action_tensor)
+        
+        # Flatten to 1D: take first timestep if chunks, squeeze batch dims
+        while action_tensor.dim() > 1:
+            action_tensor = action_tensor[0]
+        
+        # Convert tensor to dict using action names from dataset
+        action_names = dataset.features[ACTION]["names"]
+        ee_action = {name: float(action_tensor[i]) for i, name in enumerate(action_names)}
         
         # 6. Convert relative action back to absolute if needed
         if use_relative_actions:
-            # Convert dict to tensor for relative->absolute conversion
-            action_keys = sorted([k for k in ee_action.keys() if "ee." in k or k.endswith(".pos")])
-            action_tensor = torch.tensor([ee_action.get(k, 0.0) for k in action_keys])
+            action_keys = sorted(ee_action.keys())
+            action_vals = torch.tensor([ee_action[k] for k in action_keys])
             
             # Unnormalize if we have a normalizer
             if relative_normalizer is not None:
-                action_tensor = relative_normalizer.unnormalize(action_tensor.unsqueeze(0).unsqueeze(0))
-                action_tensor = action_tensor.squeeze(0).squeeze(0)
+                action_vals = relative_normalizer.unnormalize(action_vals.unsqueeze(0).unsqueeze(0))
+                action_vals = action_vals.squeeze(0).squeeze(0)
             
             # Convert from relative to absolute
-            absolute_action = convert_from_relative_actions(action_tensor.unsqueeze(0), current_ee_pos)
+            absolute_action = convert_from_relative_actions(action_vals.unsqueeze(0), current_ee_pos)
             
             # Convert back to dict
             ee_action = {k: float(absolute_action[0, i]) for i, k in enumerate(action_keys)}