Add Llama3.1 1B HTP to benchmark #7398
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/7398
Note: Links to docs will display an error until the docs builds have been completed. ❌ 2 New FailuresAs of commit 2c5f9dc with merge base b2a680b ( NEW FAILURES - The following jobs have failed:
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The HTP path is expected to take much longer due to calibration. Need to bump up the timeout threshold. I guess there is no harm to bump it up for ALL as most will finish within 30mins anyway. |
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| docker-image: executorch-ubuntu-22.04-qnn-sdk | ||
| submodules: 'true' | ||
| timeout: 60 | ||
| timeout: 240 |
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Set to 120 still timed out.
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| @@ -132,10 +132,10 @@ jobs: | |||
| matrix: ${{ fromJson(needs.set-parameters.outputs.benchmark_configs) }} | |||
| fail-fast: false | |||
| with: | |||
| runner: linux.2xlarge.memory | |||
| runner: linux.4xlarge.memory | |||
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Locally on devserver, quantization is taking "INFO:root:Time for quantizing: 1203.9422521591187", but on CI it's 4x slower, bump up to use the 4x runner.
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Llama3.2 QNN HTP: https://github.com/pytorch/executorch/actions/runs/12426136559/job/34693953714