fix log_alpha in modeling_sac: change to nn.parameter

added pretrained vision model in policy

Co-authored-by: Adil Zouitine <adilzouitinegm@gmail.com>

lerobot/configs/env/so100_real.yaml

@@ -1,6 +1,6 @@
 # @package _global_
 
-fps: 30
+fps: 10
 
 env:
   name: real_world
@@ -26,6 +26,6 @@ env:
     joint_masking_action_space: [1, 1, 1, 1, 0, 0] # disable wrist and gripper
 
   reward_classifier:
-    pretrained_path: outputs/classifier/checkpoints/best/pretrained_model
+    pretrained_path:  outputs/classifier/13-02-random-sample-resnet10-frozen/checkpoints/best/pretrained_model
     config_path: lerobot/configs/policy/hilserl_classifier.yaml
     

lerobot/configs/policy/sac_real.yaml

@@ -8,7 +8,7 @@
 #   env.gym.obs_type=environment_state_agent_pos \
 
 seed: 1
-dataset_repo_id: null # aractingi/push_green_cube_hf_cropped_resized
+dataset_repo_id: aractingi/push_cube_square_light_offline_demo_cropped_resized
 
 training:
   # Offline training dataloader
@@ -52,7 +52,7 @@ policy:
   n_action_steps: 1
 
   shared_encoder: true
-  # vision_encoder_name: null
+  vision_encoder_name: "helper2424/resnet10"
   freeze_vision_encoder: true
   input_shapes:
     # # TODO(rcadene, alexander-soare): add variables for height and width from the dataset/env?