[Fruiterer333]

Link to Issue or Description of Change

1. Link to an existing issue (if applicable):

• Closes: token_usage_v1 averages a turn with no reported usage as 0, so the overall understates tokens per turn #7734
• Related: Live evaluation drops standalone usage metadata, so token_usage_v1 reports n/a #7321

Problem:

token_usage_v1 reports n/a for a turn whose model calls returned no usage metadata, but _TokenUsageV1Evaluator._average still counts that turn in the denominator as 0 tokens. With one turn that used 1,000 tokens and one turn with no reported usage, the overall is 500. The efficiency metrics README says "n/a never means zero", and inference_call_count_v1 and invocation_duration_v1 already leave n/a turns out of their averages.

Solution:

_average now builds its shared denominator from the invocations that reported at least one count. Within those invocations, a missing count still averages as zero (unchanged behavior, covered by test_token_usage_averages_an_unreported_count_as_zero_for_that_turn), and total == input + output still holds after averaging. If no invocation reported usage, every count stays None, as before.

Testing Plan

Unit Tests:

• I have added or updated unit tests for my change.
• All unit tests pass locally.

Added test_token_usage_average_leaves_out_a_turn_that_reported_no_usage. It fails on main (assert 520.0 == 1040.0) and passes with this change.

$ pytest tests/unittests/evaluation/test_efficiency_evaluators.py
40 passed
$ pytest tests/unittests/evaluation
1136 passed

pyink --check, isort --check-only, codespell and mypy pass on the changed files.

Manual End-to-End (E2E) Tests:

Ran the reproduction script from #7734, which gets the evaluators through DEFAULT_METRIC_EVALUATOR_REGISTRY (no model call needed):

# before (main)
token_usage_v1           per turn=[1000.0, None]  overall=500.0
inference_call_count_v1  per turn=[1.0, 1.0]  overall=1.0
 
# after
token_usage_v1           per turn=[1000.0, None]  overall=1000.0
inference_call_count_v1  per turn=[1.0, 1.0]  overall=1.0

Checklist

• I have read the CONTRIBUTING.md document.
• I have performed a self-review of my own code.
• I have commented my code, particularly in hard-to-understand areas.
• I have added tests that prove my fix is effective or that my feature works.
• New and existing unit tests pass locally with my changes.
• I have manually tested my changes end-to-end.
• Any dependent changes have been merged and published in downstream modules.

Additional context

I used Claude Code to help find the issue and draft the change. I reproduced the bug, reviewed every line, and ran the tests above myself.

[adk-bot]

Thank you @Fruiterer333 for your contribution! 🎉

Your changes have been successfully imported and merged via Copybara in commit 5e52b21.

Closing this PR as the changes are now in the main branch.