Merge branch 'try-feature-vis' into extend-interpret

Author: PavelCz

src/reward_preprocessing/common/utils.py

@@ -264,7 +264,7 @@ def log_img_wandb(
         )
     else:
         raise ValueError(
-            f"img must be np.ndarray or PIL.Image.Image, type(img)={type(img)}"
+            f"img must be np.ndarray or PIL.Image.Image, {type(img)=}"
         )
     wb_img = wandb.Image(pil_img, caption=caption)
     logger.record(wandb_key, wb_img)

src/reward_preprocessing/interpret.py

@@ -110,7 +110,10 @@ def interpret(
             Limit how many of the transitions from `rollout_path` are used for
             dimensionality reduction. The RL Vision paper uses "a few thousand"
             sampled infrequently from rollouts.
-        pyplot: Whether to plot images as pyplot figures.
+        pyplot:
+            Whether to plot visualizations as pyplot figures. Set to False when running
+            interpret in a non-GUI environment, such as the cluster. In that case, use
+            wandb logging or save images to disk.
         vis_scale: Scale the plotted images by this factor.
         vis_type:
             Type of visualization to use. Either "traditional" for gradient-based
@@ -133,6 +136,9 @@ def interpret(
             this must also not be None.
         img_save_path:
             Directory to save images in. Must end in a /. If None, do not save images.
+        reg:
+            Regularization settings. See reward_preprocessing.scripts.config.interpret
+            for defaults.
     """
     if limit_num_obs <= 0:
         raise ValueError(

src/reward_preprocessing/scripts/config/interpret.py

@@ -13,7 +13,10 @@ def defaults():
     # Limit the number of observations to use for dim reduction.
     # The RL Vision paper uses "a few thousand" observations.
     limit_num_obs = 2048
-    pyplot = False  # Plot images as pyplot figures
+    # Whether to plot visualizations as pyplot figures. Set to False when running
+    # interpret in a non-GUI environment, such as the cluster. In that case, use
+    # wandb logging or save images to disk.
+    pyplot = False
     vis_scale = 4  # Scale the visualization img by this factor
     vis_type = "traditional"  # "traditional" (gradient-based) or "dataset"
     # Name of the layer to visualize. To figure this out run interpret and the
@@ -31,7 +34,7 @@ def defaults():
     # What regularization to use for generated images.
     reg = {
         "no_gan": {
-            "jitter": 8,
+            "jitter": 8,  # Jitter for generated images.
         }
     }