Merge remote-tracking branch 'origin/main' into user/aliberts/2024_05_04_release_cleanup

README.md

@@ -135,7 +135,7 @@ Or you can achieve the same result by executing our script from the command line
 ```bash
 # TODO: Not working right now, update `lerobot/diffusion_policy_pusht_image` to fix
 python lerobot/scripts/eval.py \
-    -p lerobot/diffusion_policy_pusht_image \
+    -p lerobot/diffusion_pusht \
     eval_episodes=10 \
     hydra.run.dir=outputs/eval/example_hub
 ```

examples/2_evaluate_pretrained_policy.py

@@ -10,7 +10,7 @@ from huggingface_hub import snapshot_download
 from lerobot.scripts.eval import eval
 
 # Get a pretrained policy from the hub.
-pretrained_policy_name = "lerobot/diffusion_policy_pusht_image"
+pretrained_policy_name = "lerobot/diffusion_pusht"
 pretrained_policy_path = Path(snapshot_download(pretrained_policy_name))
 # OR uncomment the following to evaluate a policy from the local outputs/train folder.
 # pretrained_policy_path = Path("outputs/train/example_pusht_diffusion")

lerobot/scripts/eval.py

@@ -2,18 +2,18 @@
 
 Usage examples:
 
-You want to evaluate a model from the hub (eg: https://huggingface.co/lerobot/diffusion_policy_pusht_image)
+You want to evaluate a model from the hub (eg: https://huggingface.co/lerobot/diffusion_pusht)
 for 10 episodes.
 
 ```
-python lerobot/scripts/eval.py -p lerobot/diffusion_policy_pusht_image eval.n_episodes=10
+python lerobot/scripts/eval.py -p lerobot/diffusion_pusht eval.n_episodes=10
 ```
 
 OR, you want to evaluate a model checkpoint from the LeRobot training script for 10 episodes.
 
 ```
 python lerobot/scripts/eval.py \
-    -p outputs/train/diffusion_policy_pusht_image/checkpoints/005000 \
+    -p outputs/train/diffusion_pusht/checkpoints/005000 \
     eval.n_episodes=10
 ```
 
@@ -23,7 +23,7 @@ Note that in both examples, the repo/folder should contain at least `config.json
 Note the formatting for providing the number of episodes. Generally, you may provide any number of arguments
 with `qualified.parameter.name=value`. In this case, the parameter eval.n_episodes appears as `n_episodes`
 nested under `eval` in the `config.yaml` found at
-https://huggingface.co/lerobot/diffusion_policy_pusht_image/tree/main.
+https://huggingface.co/lerobot/diffusion_pusht/tree/main.
 """
 
 import argparse

tests/test_examples.py

@@ -58,7 +58,7 @@ def test_examples_3_and_2():
     file_contents = _find_and_replace(
         file_contents,
         [
-            ('pretrained_policy_name = "lerobot/diffusion_policy_pusht_image"', ""),
+            ('pretrained_policy_name = "lerobot/diffusion_pusht"', ""),
             ("pretrained_policy_path = Path(snapshot_download(pretrained_policy_name))", ""),
             (
                 '# pretrained_policy_path = Path("outputs/train/example_pusht_diffusion")',