From 5207ed05e2f29dc60cd2866fbc0b1e8d3197b284 Mon Sep 17 00:00:00 2001 From: Pierrick Hymbert Date: Sat, 6 Apr 2024 05:40:47 +0200 Subject: [PATCH] ci: bench: support sse and fix prompt processing time / server: add tokens usage in stream OAI response (#6495) * ci: bench: support sse and fix prompt processing time server: add tokens usage in stream mode * ci: bench: README.md EOL * ci: bench: remove total pp and tg as it is not accurate * ci: bench: fix case when there is no token generated * ci: bench: change to the 95 percentile for pp and tg as it is closer to what the server exports in metrics * ci: bench: fix finish reason rate --- .github/workflows/bench.yml | 20 ++++++---- examples/server/bench/README.md | 42 ++++++++++++++++++--- examples/server/bench/bench.py | 11 +++--- examples/server/bench/script.js | 66 +++++++++++++++++++++++---------- examples/server/utils.hpp | 9 +++++ 5 files changed, 111 insertions(+), 37 deletions(-) diff --git a/.github/workflows/bench.yml b/.github/workflows/bench.yml index b974e7facead1f..7587966320c81d 100644 --- a/.github/workflows/bench.yml +++ b/.github/workflows/bench.yml @@ -79,12 +79,18 @@ jobs: sleep 0.1 done - - name: Install k6 + - name: Set up Go + uses: actions/setup-go@v5 + with: + go-version: '1.21' + + - name: Install k6 and xk6-sse id: k6_installation run: | cd examples/server/bench - wget --quiet https://github.com/grafana/k6/releases/download/v0.49.0/k6-v0.49.0-linux-amd64.tar.gz - tar xzf k6*.tar.gz --strip-components=1 + go install go.k6.io/xk6/cmd/xk6@latest + xk6 build master \ + --with github.com/phymbert/xk6-sse - name: Build id: cmake_build @@ -118,7 +124,7 @@ jobs: cd examples/server/bench source venv/bin/activate - BENCH_K6_BIN_PATH=./k6 python bench.py \ + python bench.py \ --runner-label ${{ env.RUNNER_LABEL }} \ --name ${{ github.job }} \ --branch ${{ github.head_ref || github.ref_name }} \ @@ -228,9 +234,9 @@ jobs: Expand details for performance related PR only - Concurrent users: ${{ env.N_USERS }}, duration: ${{ github.event.inputs.duration || env.DURATION }} - - HTTP request : avg=${{ env.HTTP_REQ_DURATION_AVG }}ms p(90)=${{ env.HTTP_REQ_DURATION_P_90_ }}ms fails=${{ env.HTTP_REQ_FAILED_PASSES }}, finish reason: stop=${{ env.LLAMACPP_COMPLETIONS_STOP_RATE_PASSES }} truncated=${{ env.LLAMACPP_COMPLETIONS_TRUNCATED_RATE_PASSES }} - - Prompt processing (pp): avg=${{ env.LLAMACPP_PROMPT_TOKENS_AVG }}tk/s p(90)=${{ env.LLAMACPP_PROMPT_TOKENS_P_90_ }}tk/s **total=${{ env.LLAMACPP_PROMPT_TOKENS_TOTAL_COUNTER_RATE }}tk/s** - - Token generation (tg): avg=${{ 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** + - HTTP request : avg=${{ env.HTTP_REQ_DURATION_AVG }}ms p(95)=${{ env.HTTP_REQ_DURATION_P_95_ }}ms fails=${{ env.HTTP_REQ_FAILED_PASSES }}, finish reason: stop=${{ env.LLAMACPP_COMPLETIONS_STOP_RATE_PASSES }} truncated=${{ env.LLAMACPP_COMPLETIONS_TRUNCATED_RATE_PASSES }} + - Prompt processing (pp): avg=${{ env.LLAMACPP_PROMPT_PROCESSING_SECOND_AVG }}tk/s p(95)=${{ env.LLAMACPP_PROMPT_PROCESSING_SECOND_P_95_ }}tk/s + - Token generation (tg): avg=${{ env.LLAMACPP_TOKENS_SECOND_AVG }}tk/s p(95)=${{ env.LLAMACPP_TOKENS_SECOND_P_95_ }}tk/s - ${{ env.BENCH_GRAPH_XLABEL }} diff --git a/examples/server/bench/README.md b/examples/server/bench/README.md index a53ad64d7359bc..23a3ec97523ef7 100644 --- a/examples/server/bench/README.md +++ b/examples/server/bench/README.md @@ -2,13 +2,15 @@ Benchmark is using [k6](https://k6.io/). -##### Install k6 +##### Install k6 and sse extension -Follow instruction from: https://k6.io/docs/get-started/installation/ +SSE is not supported by default in k6, you have to build k6 with the [xk6-sse](https://github.com/phymbert/xk6-sse) extension. -Example for ubuntu: +Example: ```shell -snap install k6 +go install go.k6.io/xk6/cmd/xk6@latest +xk6 build master \ +--with github.com/phymbert/xk6-sse ``` #### Download a dataset @@ -46,7 +48,7 @@ server --host localhost --port 8080 \ For 500 chat completions request with 8 concurrent users during maximum 10 minutes, run: ```shell -k6 run script.js --duration 10m --iterations 500 --vus 8 +./k6 run script.js --duration 10m --iterations 500 --vus 8 ``` The benchmark values can be overridden with: @@ -86,3 +88,33 @@ K6 metrics might be compared against [server metrics](../README.md), with: ```shell curl http://localhost:8080/metrics ``` + +### Using the CI python script +The `bench.py` script does several steps: +- start the server +- define good variable for k6 +- run k6 script +- extract metrics from prometheus + +It aims to be used in the CI, but you can run it manually: + +```shell +LLAMA_SERVER_BIN_PATH=../../../cmake-build-release/bin/server python bench.py \ + --runner-label local \ + --name local \ + --branch `git rev-parse --abbrev-ref HEAD` \ + --commit `git rev-parse HEAD` \ + --scenario script.js \ + --duration 5m \ + --hf-repo ggml-org/models \ + --hf-file phi-2/ggml-model-q4_0.gguf \ + --model-path-prefix models \ + --parallel 4 \ + -ngl 33 \ + --batch-size 2048 \ + --ubatch-size 256 \ + --ctx-size 4096 \ + --n-prompts 200 \ + --max-prompt-tokens 256 \ + --max-tokens 256 +``` diff --git a/examples/server/bench/bench.py b/examples/server/bench/bench.py index 86eeeccf874cda..6ca637bddc3a12 100644 --- a/examples/server/bench/bench.py +++ b/examples/server/bench/bench.py @@ -76,7 +76,6 @@ def main(args_in: list[str] | None = None) -> None: data['metrics'][metric_name][metric_metric]=value github_env.write( f"{escape_metric_name(metric_name)}_{escape_metric_name(metric_metric)}={value}\n") - token_seconds = data['metrics']['llamacpp_tokens_second']['avg'] iterations = data['root_group']['checks']['success completion']['passes'] except Exception: @@ -181,16 +180,16 @@ def main(args_in: list[str] | None = None) -> None: bench_results = { "i": iterations, "req": { - "p90": round(data['metrics']["http_req_duration"]["p(90)"], 2), + "p95": round(data['metrics']["http_req_duration"]["p(95)"], 2), "avg": round(data['metrics']["http_req_duration"]["avg"], 2), }, "pp": { - "p90": round(data['metrics']["llamacpp_prompt_tokens"]["p(90)"], 2), - "avg": round(data['metrics']["llamacpp_prompt_tokens"]["avg"], 2), + "p95": round(data['metrics']["llamacpp_prompt_processing_second"]["p(95)"], 2), + "avg": round(data['metrics']["llamacpp_prompt_processing_second"]["avg"], 2), "0": round(mean(prometheus_metrics['prompt_tokens_seconds']), 2), }, "tg": { - "p90": round(data['metrics']["llamacpp_tokens_second"]["p(90)"], 2), + "p95": round(data['metrics']["llamacpp_tokens_second"]["p(95)"], 2), "avg": round(data['metrics']["llamacpp_tokens_second"]["avg"], 2), "0": round(mean(prometheus_metrics['predicted_tokens_seconds']), 2), }, @@ -206,7 +205,7 @@ def main(args_in: list[str] | None = None) -> None: def start_benchmark(args): - k6_path = 'k6' + k6_path = './k6' if 'BENCH_K6_BIN_PATH' in os.environ: k6_path = os.environ['BENCH_K6_BIN_PATH'] k6_args = [ diff --git a/examples/server/bench/script.js b/examples/server/bench/script.js index dc41e8d937c1bd..c4c486cdf93d93 100644 --- a/examples/server/bench/script.js +++ b/examples/server/bench/script.js @@ -1,4 +1,4 @@ -import http from 'k6/http' +import sse from 'k6/x/sse' import {check, sleep} from 'k6' import {SharedArray} from 'k6/data' import {Counter, Rate, Trend} from 'k6/metrics' @@ -53,7 +53,9 @@ const data = new SharedArray('conversations', function () { const llamacpp_prompt_tokens = new Trend('llamacpp_prompt_tokens') const llamacpp_completion_tokens = new Trend('llamacpp_completion_tokens') + const llamacpp_tokens_second = new Trend('llamacpp_tokens_second') +const llamacpp_prompt_processing_second = new Trend('llamacpp_prompt_processing_second') const llamacpp_prompt_tokens_total_counter = new Counter('llamacpp_prompt_tokens_total_counter') const llamacpp_completion_tokens_total_counter = new Counter('llamacpp_completion_tokens_total_counter') @@ -86,36 +88,62 @@ export default function () { } ], "model": model, - "stream": false, + "stream": true, "seed": 42, "max_tokens": max_tokens } - const body = JSON.stringify(payload) + const params = {method: 'POST', body: JSON.stringify(payload)}; + + const startTime = new Date() + let promptEvalEndTime = null + let prompt_tokens = 0 + let completions_tokens = 0 + let finish_reason = null + const res = sse.open(`${server_url}/chat/completions`, params, function (client) { + client.on('event', function (event) { + if (promptEvalEndTime == null) { + promptEvalEndTime = new Date() + } - let res = http.post(`${server_url}/chat/completions`, body, { - headers: {'Content-Type': 'application/json'}, - timeout: '300s' - }) + let chunk = JSON.parse(event.data) + let choice = chunk.choices[0] + if (choice.finish_reason) { + finish_reason = choice.finish_reason + } - check(res, {'success completion': (r) => r.status === 200}) + if (chunk.usage) { + prompt_tokens = chunk.usage.prompt_tokens + llamacpp_prompt_tokens.add(prompt_tokens) + llamacpp_prompt_tokens_total_counter.add(prompt_tokens) + + completions_tokens = chunk.usage.completion_tokens + llamacpp_completion_tokens.add(completions_tokens) + llamacpp_completion_tokens_total_counter.add(completions_tokens) + } + }) - if (res.status === 200) { - const completions = res.json() + client.on('error', function (e) { + console.log('An unexpected error occurred: ', e.error()); + throw e; + }) + }) - llamacpp_prompt_tokens.add(completions.usage.prompt_tokens) - llamacpp_prompt_tokens_total_counter.add(completions.usage.prompt_tokens) + check(res, {'success completion': (r) => r.status === 200}) - llamacpp_completion_tokens.add(completions.usage.completion_tokens) - llamacpp_completion_tokens_total_counter.add(completions.usage.completion_tokens) + const endTime = new Date() - llamacpp_completions_truncated_rate.add(completions.choices[0].finish_reason === 'length') - llamacpp_completions_stop_rate.add(completions.choices[0].finish_reason === 'stop') + const promptEvalTime = promptEvalEndTime - startTime + if (promptEvalTime > 0) { + llamacpp_prompt_processing_second.add(prompt_tokens / (promptEvalEndTime - startTime) * 1.e3) + } - llamacpp_tokens_second.add(completions.usage.total_tokens / res.timings.duration * 1.e3) - } else { - console.error(`response: ${res.body} request=${payload}`) + const completion_time = endTime - promptEvalEndTime + if (completions_tokens > 0 && completion_time > 0) { + llamacpp_tokens_second.add(completions_tokens / completion_time * 1.e3) } + llamacpp_completions_truncated_rate.add(finish_reason === 'length') + llamacpp_completions_stop_rate.add(finish_reason === 'stop') sleep(0.3) } diff --git a/examples/server/utils.hpp b/examples/server/utils.hpp index fd8f3d2bdc97a0..fcd85f29599b9f 100644 --- a/examples/server/utils.hpp +++ b/examples/server/utils.hpp @@ -1027,6 +1027,15 @@ static std::vector format_partial_response_oaicompat(json request ,json re {"model", modelname}, {"object", "chat.completion.chunk"} }; + if (!finish_reason.empty()) { + int num_tokens_predicted = json_value(result, "tokens_predicted", 0); + int num_prompt_tokens = json_value(result, "tokens_evaluated", 0); + ret.push_back({"usage", json { + {"completion_tokens", num_tokens_predicted}, + {"prompt_tokens", num_prompt_tokens}, + {"total_tokens", num_tokens_predicted + num_prompt_tokens} + }}); + } return std::vector({ret}); }