fix(config): update vision encoder model name to lerobot/resnet10

src/lerobot/policies/sac/configuration_sac.py

@@ -122,7 +122,7 @@ class SACConfig(PreTrainedConfig):
     device: str = "cpu"
     # Device to store the model on
     storage_device: str = "cpu"
-    # Name of the vision encoder model (Set to "helper2424/resnet10" for hil serl resnet10)
+    # Name of the vision encoder model (Set to "lerobot/resnet10" for hil serl resnet10)
     vision_encoder_name: str | None = None
     # Whether to freeze the vision encoder during training
     freeze_vision_encoder: bool = True

src/lerobot/policies/sac/reward_model/configuration_classifier.py

@@ -31,7 +31,7 @@ class RewardClassifierConfig(PreTrainedConfig):
     latent_dim: int = 256
     image_embedding_pooling_dim: int = 8
     dropout_rate: float = 0.1
-    model_name: str = "helper2424/resnet10"
+    model_name: str = "lerobot/resnet10"
     device: str = "cpu"
     model_type: str = "cnn"  # "transformer" or "cnn"
     num_cameras: int = 2

tests/policies/hilserl/test_modeling_classifier.py

@@ -14,7 +14,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import pytest
 import torch
 
 from lerobot.configs.types import FeatureType, NormalizationMode, PolicyFeature
@@ -38,9 +37,6 @@ def test_classifier_output():
 
 
 @skip_if_package_missing("transformers")
-@pytest.mark.skip(
-    reason="helper2424/resnet10 needs to be updated to work with the latest version of transformers"
-)
 def test_binary_classifier_with_default_params():
     from lerobot.policies.sac.reward_model.modeling_classifier import Classifier
 
@@ -82,9 +78,6 @@ def test_binary_classifier_with_default_params():
 
 
 @skip_if_package_missing("transformers")
-@pytest.mark.skip(
-    reason="helper2424/resnet10 needs to be updated to work with the latest version of transformers"
-)
 def test_multiclass_classifier():
     from lerobot.policies.sac.reward_model.modeling_classifier import Classifier
 
@@ -124,9 +117,6 @@ def test_multiclass_classifier():
 
 
 @skip_if_package_missing("transformers")
-@pytest.mark.skip(
-    reason="helper2424/resnet10 needs to be updated to work with the latest version of transformers"
-)
 def test_default_device():
     from lerobot.policies.sac.reward_model.modeling_classifier import Classifier
 
@@ -139,9 +129,6 @@ def test_default_device():
 
 
 @skip_if_package_missing("transformers")
-@pytest.mark.skip(
-    reason="helper2424/resnet10 needs to be updated to work with the latest version of transformers"
-)
 def test_explicit_device_setup():
     from lerobot.policies.sac.reward_model.modeling_classifier import Classifier
 

tests/policies/test_sac_policy.py

@@ -304,7 +304,7 @@ def test_sac_training_with_visual_input(batch_size: int, state_dim: int, action_
 
 @pytest.mark.parametrize(
     "batch_size,state_dim,action_dim,vision_encoder_name",
-    [(1, 6, 6, "helper2424/resnet10"), (1, 6, 6, "facebook/convnext-base-224")],
+    [(1, 6, 6, "lerobot/resnet10"), (1, 6, 6, "facebook/convnext-base-224")],
 )
 @pytest.mark.skipif(not TRANSFORMERS_AVAILABLE, reason="Transformers are not installed")
 def test_sac_policy_with_pretrained_encoder(