ci: bench: more resilient, more metrics
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2 changed files with 56 additions and 24 deletions
62
.github/workflows/bench.yml
vendored
62
.github/workflows/bench.yml
vendored
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@ -12,6 +12,15 @@ on:
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- Standard_NC4as_T4_v3
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- Standard_NC24ads_A100_v4
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- Standard_NC80adis_H100_v5
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sha:
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description: 'Commit SHA1 to build'
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required: false
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type: string
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duration:
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description: 'Duration of the bench'
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type: string
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default: 10m
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push:
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branches:
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- master
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@ -31,6 +40,7 @@ jobs:
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runs-on: Standard_NC4as_T4_v3
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env:
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RUNNER_LABEL: Standard_NC4as_T4_v3 # FIXME Do not find a way to not duplicate it
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N_USERS: 8
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if: ${{ github.event.inputs.gpu-series == 'Standard_NC4as_T4_v3' || github.event.schedule || github.event.pull_request || github.event.push.ref == 'refs/heads/master' }}
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steps:
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- name: Clone
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@ -38,6 +48,7 @@ jobs:
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uses: actions/checkout@v3
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with:
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fetch-depth: 0
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ref: ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha || github.head_ref || github.ref_name }}
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- name: Install python env
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id: pipenv
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@ -100,13 +111,13 @@ jobs:
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--runner-label ${{ env.RUNNER_LABEL }} \
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--name ${{ github.job }} \
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--branch ${{ github.head_ref || github.ref_name }} \
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--commit ${{ github.sha }} \
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--commit ${{ github.event.inputs.sha || github.event.pull_request.head.sha || github.sha }} \
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--scenario script.js \
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--duration 10m \
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--duration ${{ github.event.inputs.duration || "10m" }} \
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--hf-repo ggml-org/models \
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--hf-file phi-2/ggml-model-q4_0.gguf \
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--model-path-prefix /models \
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--parallel 8 \
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--parallel ${{ env.N_USERS }} \
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-ngl 33 \
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--batch-size 2048 \
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--ubatch-size 256 \
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@ -125,7 +136,7 @@ jobs:
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name: benchmark-results
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compression-level: 9
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path: |
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examples/server/bench/*.png
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examples/server/bench/*.jpg
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examples/server/bench/*.json
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examples/server/bench/*.log
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@ -133,6 +144,7 @@ jobs:
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uses: Sibz/github-status-action@v1
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with:
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authToken: ${{secrets.GITHUB_TOKEN}}
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sha: ${{ inputs.sha || github.event.pull_request.head.sha || github.sha }}
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context: bench-server-baseline
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description: |
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${{ env.BENCH_RESULTS }}
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@ -145,10 +157,10 @@ jobs:
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with:
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client_id: ${{secrets.IMGUR_CLIENT_ID}}
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path: |
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examples/server/bench/prompt_tokens_seconds.png
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examples/server/bench/predicted_tokens_seconds.png
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examples/server/bench/kv_cache_usage_ratio.png
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examples/server/bench/requests_processing.png
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examples/server/bench/prompt_tokens_seconds.jpg
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examples/server/bench/predicted_tokens_seconds.jpg
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examples/server/bench/kv_cache_usage_ratio.jpg
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examples/server/bench/requests_processing.jpg
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- name: Extract mermaid
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id: set_mermaid
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@ -176,24 +188,40 @@ jobs:
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echo "$REQUESTS_PROCESSING" >> $GITHUB_ENV
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echo "EOF" >> $GITHUB_ENV
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- name: Extract image url
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id: extrac_image_url
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continue-on-error: true
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run: |
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set -eux
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echo "IMAGE_O=${{ fromJSON(steps.imgur_step.outputs.imgur_urls)[0] }}" >> $GITHUB_ENV
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echo "IMAGE_1=${{ fromJSON(steps.imgur_step.outputs.imgur_urls)[1] }}" >> $GITHUB_ENV
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echo "IMAGE_2=${{ fromJSON(steps.imgur_step.outputs.imgur_urls)[2] }}" >> $GITHUB_ENV
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echo "IMAGE_3=${{ fromJSON(steps.imgur_step.outputs.imgur_urls)[3] }}" >> $GITHUB_ENV
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- name: Comment PR
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uses: mshick/add-pr-comment@v2
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id: comment_pr
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if: ${{ github.event.pull_request != '' }}
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continue-on-error: true
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with:
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message-id: bench-${{ github.job }}-${{ env.RUNNER_LABEL }}
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message: |
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📈 **llama.cpp server** benchmark for _${{ github.job }}_ on _${{ env.RUNNER_LABEL }}_: **${{ env.BENCH_ITERATIONS}} iterations** 🚀
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📈 **llama.cpp server** for _${{ github.job }}_ on _${{ env.RUNNER_LABEL }}_: **${{ env.BENCH_ITERATIONS}} iterations** 🚀
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- Concurrent users: ${{ env.N_USERS }}
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- HTTP request : avg=${{ env.HTTP_REQ_DURATION_AVG }}ms p(90)=${{ env.HTTP_REQ_DURATION_P_90_ }}ms passes=${{ env.HTTP_REQ_FAILED_FAILS }}reqs fails=${{ env.HTTP_REQ_FAILED_PASSES }}reqs
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- Prompt processing (pp): avg=${{ env.LLAMACPP_PROMPT_TOKENS_AVG }}tk/s p(90)=${{ env.LLAMACPP_PROMPT_TOKENS_P_90_ }}tk/s **total=${{ env.LLAMACPP_PROMPT_TOKENS_TOTAL_COUNTER_RATE }}tk/s**
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- Token generation (tg): avg=${{ env.LLAMACPP_TOKENS_SECOND_AVG }}tk/s p(90)=${{ env.LLAMACPP_TOKENS_SECOND_P_90_ }}tk/s **total=${{ env.LLAMACPP_COMPLETION_TOKENS_TOTAL_COUNTER_RATE }}tk/s**
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- Finish reason : stop=${{ env.LLAMACPP_COMPLETIONS_STOP_RATE_PASSES }}reqs truncated=${{ env.LLAMACPP_COMPLETIONS_TRUNCATED_RATE_PASSES }}
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- ${{ env.BENCH_GRAPH_XLABEL }}
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- req_avg=${{ env.HTTP_REQ_DURATION_AVG }} pp_avg=${{ env.LLAMACPP_PROMPT_TOKENS_AVG }} tks_avg=${{ env.LLAMACPP_TOKENS_SECOND_AVG }}
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<p align="center">
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<img width="100%" height="100%" src="${{ fromJSON(steps.imgur_step.outputs.imgur_urls)[0] }}" alt="prompt_tokens_seconds" />
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<img width="100%" height="100%" src="${{ env.IMAGE_O] }}" alt="prompt_tokens_seconds" />
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<details>
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<summary>More</summary>
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```mermaid
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@ -202,7 +230,7 @@ jobs:
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</details>
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<img width="100%" height="100%" src="${{ fromJSON(steps.imgur_step.outputs.imgur_urls)[1] }}" alt="predicted_tokens_seconds"/>
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<img width="100%" height="100%" src="${{ env.IMAGE_1 }}" alt="predicted_tokens_seconds"/>
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<details>
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<summary>More</summary>
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@ -214,10 +242,14 @@ jobs:
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</details>
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</p>
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<details>
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<summary>Details</summary>
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<p align="center">
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<img width="100%" height="100%" src="${{ fromJSON(steps.imgur_step.outputs.imgur_urls)[2] }}" alt="kv_cache_usage_ratio" />
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<img width="100%" height="100%" src="${{ env.IMAGE_2 }}" alt="kv_cache_usage_ratio" />
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<details>
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<summary>More</summary>
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</details>
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<img width="100%" height="100%" src="${{ fromJSON(steps.imgur_step.outputs.imgur_urls)[3] }}" alt="requests_processing"/>
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<img width="100%" height="100%" src="${{ env.IMAGE_3 }}" alt="requests_processing"/>
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<details>
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<summary>More</summary>
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@ -70,7 +70,7 @@ def main(args_in: list[str] | None = None) -> None:
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for metric_name in data['metrics']:
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for metric_metric in data['metrics'][metric_name]:
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value = data['metrics'][metric_name][metric_metric]
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if isinstance(value, float):
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if isinstance(value, float) or isinstance(value, int):
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value = round(value, 2)
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data['metrics'][metric_name][metric_metric]=value
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github_env.write(
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@ -149,11 +149,11 @@ def main(args_in: list[str] | None = None) -> None:
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plt.gca().spines["right"].set_alpha(0.0)
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plt.gca().spines["left"].set_alpha(0.3)
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# Save the plot as a PNG image
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plt.savefig(f'{metric}.png')
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# Save the plot as a jpg image
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plt.savefig(f'{metric}.jpg', dpi=60)
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plt.close()
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# Mermaid format in case image failed
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# Mermaid format in case images upload failed
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with (open(f"{metric}.mermaid", 'w') as mermaid_f):
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mermaid = (
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f"""---
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