fix argmax axis + fix seed

lerobot/scripts/eval.py

@@ -293,9 +293,7 @@ def eval_policy(
         # this won't be included).
         n_steps = rollout_data["done"].shape[1]
         # Note: this relies on a property of argmax: that it returns the first occurrence as a tiebreaker.
-        done_indices = torch.argmax(
-            rollout_data["done"].to(int), axis=1
-        )  # (batch_size, rollout_steps) TODO: can't find any docs for the axis arg.
+        done_indices = torch.argmax(rollout_data["done"].to(int), dim=1)
 
         # Make a mask with shape (batch, n_steps) to mask out rollout data after the first done
         # (batch-element-wise). Note the `done_indices + 1` to make sure to keep the data from the done step.
@@ -307,7 +305,10 @@ def eval_policy(
         max_rewards.extend(batch_max_rewards.tolist())
         batch_successes = einops.reduce((rollout_data["success"] * mask), "b n -> b", "any")
         all_successes.extend(batch_successes.tolist())
-        all_seeds.extend(seeds)
+        if seeds:
+            all_seeds.extend(seeds)
+        else:
+            all_seeds.append(None)
 
         # FIXME: episode_data is either None or it doesn't exist
         if return_episode_data: