Built-in observation aggregators drop bounds-preserving specifications
評估
研究方向
Start by locating base.AGGREGATORS and Updater.observation_spec(), then reproduce the AttributeError and the bounded Generic observable case described in the issue. Check that min, max, mean and median retain scalar or per-element bounds while sum remains unbounded, without changing value, shape/dtype, custom-aggregator or unbounded-input behavior.
由索引模型根據 Issue 內容生成。
描述
Reproduction
Built-in observation aggregators declare a bounds_reserving attribute, while Updater.observation_spec() reads preserves_bounds. Consequently, even min, max, mean and median are treated as having unknown bound behavior: the updater logs a warning and returns an unbounded Array instead of retaining a BoundedArray specification.
The problem is visible directly:
from dm_control.composer.observation.observable import base
assert base.AGGREGATORS['mean'].preserves_bounds is True
# AttributeError: functools.partial has no attribute preserves_bounds
A bounded Generic observable reduced with the built-in mean loses its limits through the actual Updater. Returned values remain in bounds, but the resulting specification no longer rejects out-of-bounds inputs.
Expected behavior
Use the attribute name already documented and consumed by Updater. The four bounds-preserving reducers should retain scalar or per-element limits, while sum must remain unbounded. Preserve reduced values, shape/dtype inference, custom-aggregator behavior and unbounded inputs.
Reproduced on main at a04e3e4cf56c12117d2294bb090f9acec21e5c67, including a native MuJoCo observation sequence. No renderer, external services or model inference is needed.
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