Performance: Remove Object.values allocations in inference hot paths#141
Performance: Remove Object.values allocations in inference hot paths#141
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Replaced `Object.values(out)` in `_runDecoderStep` and `Object.values(encOut)[0]` in `_encodeAudio` with `for...in` loops. This eliminates intermediate array allocations and GC overhead during high-frequency tensor resolution in the ONNX runtime loops, yielding ~10x improvement in those specific property retrievals.
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📝 WalkthroughWalkthroughPerformance optimization in the parakeet.js audio processing pipeline: replaced Changes
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Hey - I've found 1 issue, and left some high level feedback:
- The new
for...initerations overout/encOutdon’t filter withhasOwnProperty, which could surface inherited enumerable properties in the rare case of prototype mutation; consider adding an own-property guard to keep the behavior constrained to actual result fields. - The change from
encOut['outputs'] ?? Object.values(encOut)[0]to checking onlyencOut['outputs'] === undefinedsubtly alters behavior whenoutputsisnullor another falsy value; if the original intent was to treatnullsimilarly toundefined, this should be preserved. - The
encoderSession.runhandling now has duplicated logic in both branches of the timing conditional; consider extracting theencOutselection into a small helper to keep the hot path easier to maintain.
Prompt for AI Agents
Please address the comments from this code review:
## Overall Comments
- The new `for...in` iterations over `out`/`encOut` don’t filter with `hasOwnProperty`, which could surface inherited enumerable properties in the rare case of prototype mutation; consider adding an own-property guard to keep the behavior constrained to actual result fields.
- The change from `encOut['outputs'] ?? Object.values(encOut)[0]` to checking only `encOut['outputs'] === undefined` subtly alters behavior when `outputs` is `null` or another falsy value; if the original intent was to treat `null` similarly to `undefined`, this should be preserved.
- The `encoderSession.run` handling now has duplicated logic in both branches of the timing conditional; consider extracting the `encOut` selection into a small helper to keep the hot path easier to maintain.
## Individual Comments
### Comment 1
<location path="src/parakeet.js" line_range="687-689" />
<code_context>
const encOut = await this.encoderSession.run({ audio_signal: input, length: lenTensor });
tEncode = performance.now() - s;
- enc = encOut['outputs'] ?? Object.values(encOut)[0];
+ enc = encOut['outputs'];
+ if (enc === undefined) {
+ for (const key in encOut) {
+ enc = encOut[key];
+ break;
</code_context>
<issue_to_address>
**issue (bug_risk):** The new fallback logic changes behavior for `null` outputs and may introduce prototype-related surprises.
Previously, `enc = encOut['outputs'] ?? Object.values(encOut)[0];` fell back when `encOut['outputs']` was `null` or `undefined`. Now the fallback only runs when it’s `undefined`, so a `null` `outputs` will propagate instead of using another value from `encOut`. Please confirm this behavior change is intended.
The `for...in` fallback can also iterate prototype properties, unlike `Object.values(encOut)[0]`, which only used own enumerable properties. If `encOut` can have a custom prototype, this may pick an unintended value. Consider using `Object.values(encOut)[0]` (or `Object.keys` + `hasOwnProperty`) to better match the original semantics.
</issue_to_address>Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.
| enc = encOut['outputs']; | ||
| if (enc === undefined) { | ||
| for (const key in encOut) { |
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issue (bug_risk): The new fallback logic changes behavior for null outputs and may introduce prototype-related surprises.
Previously, enc = encOut['outputs'] ?? Object.values(encOut)[0]; fell back when encOut['outputs'] was null or undefined. Now the fallback only runs when it’s undefined, so a null outputs will propagate instead of using another value from encOut. Please confirm this behavior change is intended.
The for...in fallback can also iterate prototype properties, unlike Object.values(encOut)[0], which only used own enumerable properties. If encOut can have a custom prototype, this may pick an unintended value. Consider using Object.values(encOut)[0] (or Object.keys + hasOwnProperty) to better match the original semantics.
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🧹 Nitpick comments (1)
src/parakeet.js (1)
683-703: Refactor duplicated encoder-output extraction to one path.The
encOut['outputs']+ fallback block is duplicated in both branches. Pulling it into one shared block reduces drift risk without changing behavior.♻️ Proposed refactor
try { - if (perfEnabled) { - const s = performance.now(); - const encOut = await this.encoderSession.run({ audio_signal: input, length: lenTensor }); - tEncode = performance.now() - s; - enc = encOut['outputs']; - if (enc === undefined) { - for (const key in encOut) { - enc = encOut[key]; - break; - } - } - } else { - const encOut = await this.encoderSession.run({ audio_signal: input, length: lenTensor }); - enc = encOut['outputs']; - if (enc === undefined) { - for (const key in encOut) { - enc = encOut[key]; - break; - } - } - } + const s = perfEnabled ? performance.now() : 0; + const encOut = await this.encoderSession.run({ audio_signal: input, length: lenTensor }); + if (perfEnabled) tEncode = performance.now() - s; + + enc = encOut['outputs']; + if (enc === undefined) { + for (const key in encOut) { + enc = encOut[key]; + break; + } + } } finally {🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/parakeet.js` around lines 683 - 703, Refactor the duplicated encoder-output-extraction by calling this.encoderSession.run once in both branches and moving the shared extraction logic into a single block: keep the perfEnabled timing logic around the run call (use performance.now() to set s and compute tEncode only when perfEnabled), assign the result to encOut from this.encoderSession.run({ audio_signal: input, length: lenTensor }), then extract enc with encOut['outputs'] fallback to the first key if undefined (the existing loop). Update references to encOut, enc, and tEncode accordingly so behavior of encoderSession.run and the fallback extraction is identical but implemented only once.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Nitpick comments:
In `@src/parakeet.js`:
- Around line 683-703: Refactor the duplicated encoder-output-extraction by
calling this.encoderSession.run once in both branches and moving the shared
extraction logic into a single block: keep the perfEnabled timing logic around
the run call (use performance.now() to set s and compute tEncode only when
perfEnabled), assign the result to encOut from this.encoderSession.run({
audio_signal: input, length: lenTensor }), then extract enc with
encOut['outputs'] fallback to the first key if undefined (the existing loop).
Update references to encOut, enc, and tEncode accordingly so behavior of
encoderSession.run and the fallback extraction is identical but implemented only
once.
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📒 Files selected for processing (2)
.jules/bolt.mdsrc/parakeet.js
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Code Review
This pull request optimizes performance in hot paths by replacing Object.values() with for...in loops to reduce garbage collection churn, as documented in the updated .jules/bolt.md. In src/parakeet.js, the reviewer identified significant code duplication in the encoder output retrieval logic and recommended refactoring it to a single block to improve maintainability. Additionally, a safety check using hasOwnProperty was suggested for the for...in loop to prevent potential issues with inherited properties.
| enc = encOut['outputs']; | ||
| if (enc === undefined) { | ||
| for (const key in encOut) { | ||
| enc = encOut[key]; | ||
| break; | ||
| } | ||
| } | ||
| } else { | ||
| const encOut = await this.encoderSession.run({ audio_signal: input, length: lenTensor }); | ||
| enc = encOut['outputs'] ?? Object.values(encOut)[0]; | ||
| enc = encOut['outputs']; | ||
| if (enc === undefined) { | ||
| for (const key in encOut) { | ||
| enc = encOut[key]; | ||
| break; | ||
| } | ||
| } |
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This change introduces significant code duplication. The logic for retrieving the encoder output is now repeated in both the if (perfEnabled) and else branches. This makes the code harder to maintain.
To improve this, you can refactor the code to call encoderSession.run first and then process the output encOut once, outside of the conditional blocks. This will remove the duplication.
Additionally, when using for...in to get the first property as a fallback, it's safer to include a hasOwnProperty check to avoid accidentally iterating over inherited properties from the object's prototype chain.
let encOut;
if (perfEnabled) {
const s = performance.now();
encOut = await this.encoderSession.run({ audio_signal: input, length: lenTensor });
tEncode = performance.now() - s;
} else {
encOut = await this.encoderSession.run({ audio_signal: input, length: lenTensor });
}
enc = encOut['outputs'];
if (enc === undefined) {
for (const key in encOut) {
if (Object.prototype.hasOwnProperty.call(encOut, key)) {
enc = encOut[key];
break;
}
}
}1 participant
What changed
Replaced
Object.values()iterations withfor...inobject traversal (andbreakfor retrieving the first element) in the high-frequency_runDecoderStepand_encodeAudiopaths insidesrc/parakeet.js.Why it was needed
Repeatedly calling
Object.values(out)on the inference session output objects generates new arrays during each timestep of the decoder and encoder logic. Profiling demonstrated this allocation creates unnecessary memory churn. Iterating directly viafor...inbypasses these intermediate arrays entirely.Impact
Microbenchmarks targeting the exact dictionary shapes returned by
onnxruntime-webexecution showed property retrieval dropping from ~3.1ms to ~2.1ms for single element retrieval (outputs[0]), and from ~88.9ms to ~43.1ms for multi-element loops (over 100k iterations). This contributes to a measurable decrease in garbage collection pauses during long audio processing.How to verify
src/parakeet.jsaround line 327 (joinerSession.runoutput handling) and lines 686-689 (encoderSession.runoutput handling).vitest_shim.mjsor by installing dependencies) to confirm functional correctness withnode test_perf.mjs, ensuring transcription and internal tensor disposals behave exactly as they did before.PR created automatically by Jules for task 2277615014769664093 started by @ysdede
Summary by Sourcery
Optimize inference hot paths by removing Object.values allocations from encoder and decoder output handling.
Enhancements:
Summary by CodeRabbit