Add skiplist and more robust calculation on val

[maocheng23]

Summary

• Add weight_versions and metadata to the skiplist in log_rollout_data to avoid logging non-metric fields
• Handle nested lists (e.g. from async rollout) by flattening before averaging
• Skip non-numeric values gracefully instead of crashing

Test plan

• Verify logging works correctly with fully async rollout (which produces weight_versions and metadata fields)
• Confirm no regression in standard rollout logging

🤖 Generated with Claude Code

[gemini-code-assist]

Code Review

This pull request updates the rollout data logging utility to include 'weight_versions' and 'metadata' in the exclusion list and improves the handling of nested lists during data processing. The reviewer identified potential runtime errors in the new logic, including risks of IndexError, TypeError, and ZeroDivisionError, and provided a more robust implementation to filter numeric items and safely calculate averages.

[gemini-code-assist]

The current logic for processing list values has a few potential issues that could lead to runtime errors:

• IndexError: isinstance(val[0], ...) on line 158 will fail if val is an empty list.
• TypeError: sum(flat) on line 163 will fail if flat contains a mix of numeric and non-numeric types (e.g., [1, 2, 'a']), as the type check on line 161 only inspects the first element.
• ZeroDivisionError: len(flat) on line 163 can be zero if val is an empty list or a list of empty lists, leading to a division by zero.

To make this more robust, I suggest checking if the list is empty before accessing elements, filtering all items for numeric types, and then calculating the average only if there are numeric items.

flat = val
if val and isinstance(val[0], (list, tuple)):
    flat = [x for sublist in val for x in sublist]
numeric_items = [item for item in flat if isinstance(item, (int, float))]
if not numeric_items:
    continue
val = sum(numeric_items) / len(numeric_items)