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# How to perftest a model
For each model running inside Firefox, we want to determine its performance
in terms of speed and memory usage and track it over time.
to gather the performance metrics.
Adding a new performance test is done in two steps:
1\. making it work locally
2\. add it in perfherder
## Run locally
To test the performance of a model, you can add in the `tests/browser` a new file
with the following structure and adapt it to your needs:
```javascript
"use strict";
// unfortunately we have to write a full static structure here
const perfMetadata = {
owner: "GenAI Team",
name: "ML Test Model",
description: "Template test for latency for ml models",
options: {
default: {
perfherder: true,
perfherder_metrics: [
{ name: "pipeline-ready-latency", unit: "ms", shouldAlert: true },
{ name: "initialization-latency", unit: "ms", shouldAlert: true },
{ name: "model-run-latency", unit: "ms", shouldAlert: true },
{ name: "pipeline-ready-memory", unit: "MB", shouldAlert: true },
{ name: "initialization-memory", unit: "MB", shouldAlert: true },
{ name: "model-run-memory", unit: "MB", shouldAlert: true },
{ name: "total-memory-usage", unit: "MB", shouldAlert: true },
],
verbose: true,
manifest: "perftest.toml",
manifest_flavor: "browser-chrome",
try_platform: ["linux", "mac", "win"],
},
},
};
requestLongerTimeout(10);
add_task(async function test_ml_generic_pipeline() {
const options = {
taskName: "feature-extraction",
modelId: "Xenova/all-MiniLM-L6-v2",
modelHubUrlTemplate: "{model}/{revision}",
modelRevision: "main",
};
const args = ["The quick brown fox jumps over the lazy dog."];
await perfTest("example", options, args);
});
```
Then add the file in `perftest.toml` and rebuild with `./mach build`.
The test downloads models it uses from the local disk, so you need to prepare them.
We provide a script to automate this.
```bash
$ mach python toolkit/components/ml/tests/tools/create_local_hub.py --list-models
Available git-based models from the YAML:
- xenova-all-minilm-l6-v2 -> path-prefix: onnx-models/Xenova/all-MiniLM-L6-v2/main/
- mozilla-ner -> path-prefix: onnx-models/Mozilla/distilbert-uncased-NER-LoRA/main/
- mozilla-intent -> path-prefix: onnx-models/Mozilla/mobilebert-uncased-finetuned-LoRA-intent-classifier/main/
- mozilla-autofill -> path-prefix: onnx-models/Mozilla/tinybert-uncased-autofill/main/
- distilbart-cnn-12-6 -> path-prefix: onnx-models/Mozilla/distilbart-cnn-12-6/main/
- qwen2.5-0.5-instruct -> path-prefix: onnx-models/Mozilla/Qwen2.5-0.5B-Instruct/main/
- mozilla-smart-tab-topic -> path-prefix: onnx-models/Mozilla/smart-tab-topic/main/
- mozilla-smart-tab-emb -> path-prefix: onnx-models/Mozilla/smart-tab-embedding/main/
(Use `--model <key>` to clone one of these repositories.)
```
You can then use `--model` to download locally models, by specifying the local
`MOZ_ML_LOCAL_DIR` directory, via the env var or command line argument :
```bash
$ mach python toolkit/components/ml/tests/tools/create_local_hub.py --model mozilla-smart-tab-emb --fetches-dir ~/ml-fetches
Found existing file /Users/tarekziade/Dev/fetches/ort-wasm-simd-threaded.jsep.wasm, verifying checksum...
Existing file's checksum matches. Skipping download.
Updated Git hooks.
Git LFS initialized.
Cloning https://huggingface.co/Mozilla/smart-tab-embedding into '/Users/tarekziade/Dev/fetches/onnx-models/Mozilla/smart-tab-embedding/main...
Cloning in '/Users/tarekziade/Dev/fetches/onnx-models/Mozilla/smart-tab-embedding/main'...
Checked out revision '2278e76f67ada584cfd3149fd2661dad03674e4d' in '/Users/tarekziade/Dev/fetches/onnx-models/Mozilla/smart-tab-embedding/main'.
```
Once done, you should then be able to run it locally with :
```bash
MOZ_ML_LOCAL_DIR=~/ml-fetches ./mach perftest toolkit/components/ml/tests/browser/browser_ml_engine_perf.js --mochitest-extra-args=headless
```
Notice that `MOZ_ML_LOCAL_DIR` is an absolute path to the `root` directory.
## Add in the CI
To add the test in the CI you need to add an entry in
- `taskcluster/kinds/perftest/linux.yml`
- `taskcluster/kinds/perftest/windows11.yml`
- `taskcluster/kinds/perftest/macos.yml`
With a unique name that starts with `ml-perf`
Example for Linux:
```yaml
ml-perf:
fetches:
fetch:
- ort.wasm
- ort.jsep.wasm
- ort-training.wasm
- xenova-all-minilm-l6-v2
description: Run ML Models Perf Tests
treeherder:
symbol: perftest(linux-ml-perf)
tier: 2
attributes:
batch: false
cron: false
run-on-projects: [autoland, mozilla-central]
run:
command: >-
mkdir -p $MOZ_FETCHES_DIR/../artifacts &&
cd $MOZ_FETCHES_DIR &&
python3 python/mozperftest/mozperftest/runner.py
--mochitest-binary ${MOZ_FETCHES_DIR}/firefox/firefox-bin
--flavor mochitest
--output $MOZ_FETCHES_DIR/../artifacts
toolkit/components/ml/tests/browser/browser_ml_engine_perf.js
```
You also need to add the models your test uses (like the ones you've downloaded locally) by adding entries in
`taskcluster/kinds/fetch/onnxruntime-web-fetch.yaml` and adapting the `fetches` section.
Once this is done, try it out with:
```bash
./mach try perf --single-run --full --artifact
```
You should then see the results in treeherder.