[mikasenghaas]

Summary

• node_policy_versions counts sampled tokens with np.count_nonzero(node.mask) instead of sum(node.mask). MessageNode.mask is a numpy bool array since perf(v1): per-token node streams as numpy arrays verifiers#2961, which perf: per-token streams as numpy arrays, micro batches as raw buffers #4226 pulled into main. Python's sum() walks that array one token at a time and returns an np.int64. np.count_nonzero is vectorized, accepts lists too, and the int() cast keeps the metric values as plain ints.
• test_token_policy_ages builds its masks as numpy arrays, which is the type main now produces.

Targets #4141.

Checks: ruff check and ruff format --check pass. I also ran token_policy_ages on the test case with list masks and with numpy masks. Both returned (20, 8, 3) as plain ints. I did not run pytest, because the import chain needs torch and the test machine (macOS) does not have it.

🤖 Generated with Claude Code

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Note

Low Risk
Small metric-calculation fix for numpy masks; behavior unchanged aside from correct int types and performance.

Overview
Fixes sampled-token counting now that MessageNode.mask is a numpy bool array (from verifiers): node_policy_versions uses int(np.count_nonzero(node.mask)) instead of sum(node.mask), avoiding slow element-wise summation and keeping metrics as plain Python ints rather than np.int64.

The unit test builds trace masks with np.array(...) to match production types.

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