Performance Measurement tool by Compresss
Project description
Compressa Performance Measurement Tool
This tool is designed to measure the performance of Compressa models.
It uses the OpenAI API to run inference tasks and stores the results in a SQLite database.
Installation
git clone https://github.com/compressa-ai/compressa-perf.git
cd compressa-perf
poetry install
Install with Pip
pip install compressa-perf
Usage
1. Run experiment with prompts from a file
❯ compressa-perf measure \
--openai_url https://some-api-url.ru/chat-2/v1/ \
--api_key "${OPENAI_API_KEY}" \
--model_name Compressa-Qwen2.5-14B-Instruct \
--experiment_name "File Prompts Run" \
--prompts_file resources/prompts.csv \
--num_tasks 1000 \
--num_runners 100
2. Run experiment with generated prompts
❯ compressa-perf measure \
--openai_url https://some-api-url.ru/chat-2/v1/ \
--api_key "${OPENAI_API_KEY}" \
--model_name Compressa-Qwen2.5-14B-Instruct \
--experiment_name "Generated Prompts Run" \
--num_tasks 2 \
--num_runners 2 \
--generate_prompts \
--num_prompts 1000 \
--prompt_length 5000
Full parameter list can be obtained with compressa-perf measure -h.
3. Run set of experiments from YAML file
You can describe set of experiments in YAML file and run them on different services in one command:
❯ compressa-perf measure-from-yaml experiments.yaml
Example of YAML file:
- openai_url: https://some-api-url/v1/
model_name: Compressa-Qwen2-72B-Instruct
experiment_name: "File Prompts Run 1"
description: "Experiment using prompts from a file with 10 tasks and 5 runners"
prompts_file: resources/prompts.csv
num_tasks: 10
num_runners: 5
generate_prompts: false
num_prompts: 0
prompt_length: 0
max_tokens: 1000
- openai_url: https://some-api-url/v1/
model_name: Compressa-Qwen2-72B-Instruct
experiment_name: "Qwen2-72B Long Input / Short Output"
description: "Experiment using prompts from a file with 20 tasks and 10 runners"
prompts_file: resources/prompts.csv
num_tasks: 20
num_runners: 10
generate_prompts: true
num_prompts: 10
prompt_length: 10000
max_tokens: 100
4. List experiments
You can select experiments by name, parameters or metrics (or substrings in these fields) via compressa-perf list command.
For example:
❯ compressa-perf list \
--show-metrics \
--param-filter openai_url=chat-2 \
--param-filter avg_n_input=30
List of Experiments:
+----+----------------------------------------------------------------------------+---------------------+--------+-----------------------+
| | ID | Name | Date | Description |
+====+============================================================================+=====================+========+=======================+
| 25 | Compressa-Qwen2.5-14B-Instruct-Int4 Long Input / Short Output | 5 runners | 2024-10-03 06:21:45 | | ttft: 25.0960 |
| | | | | latency: 52.5916 |
| | | | | tpot: 0.5530 |
| | | | | throughput: 2891.0323 |
+----+----------------------------------------------------------------------------+---------------------+--------+-----------------------+
| 23 | Compressa-Qwen2.5-14B-Instruct-Int4 Long Input / Short Output | 4 runners | 2024-10-03 06:14:57 | | ttft: 17.1862 |
| | | | | latency: 37.9612 |
| | | | | tpot: 0.3954 |
| | | | | throughput: 3230.8769 |
+----+----------------------------------------------------------------------------+---------------------+--------+-----------------------+
Full parameter list:
❯ compressa-perf list -h
usage: compressa-perf list [-h] [--db DB] [--show-parameters] [--show-metrics] [--name-filter NAME_FILTER] [--param-filter PARAM_FILTER]
options:
-h, --help show this help message and exit
--db DB Path to the SQLite database
--show-parameters Show all parameters for each experiment
--show-metrics Show metrics for each experiment
--name-filter NAME_FILTER
Filter experiments by substring in the name
--param-filter PARAM_FILTER
Filter experiments by parameter value (e.g., paramkey=value_substring)
5. Generate a report for an experiment
❯ compressa-perf report <EXPERIMENT_ID>
Output example:
❯ compressa-perf report 3
Experiment Details:
ID: 3
Name: My First Run
Date: 2024-09-24 07:10:39
Description: None
Experiment Parameters:
╒══════════════╤═══════════════════════════════════════════╕
│ Parameter │ Value │
╞══════════════╪═══════════════════════════════════════════╡
│ num_workers │ 2 │
├──────────────┼───────────────────────────────────────────┤
│ num_tasks │ 2 │
├──────────────┼───────────────────────────────────────────┤
│ openai_url │ https://some-api-url.ru/chat-2/v1/ │
├──────────────┼───────────────────────────────────────────┤
│ avg_n_input │ 32 │
├──────────────┼───────────────────────────────────────────┤
│ std_n_input │ 2.8284 │
├──────────────┼───────────────────────────────────────────┤
│ avg_n_output │ 748.5000 │
├──────────────┼───────────────────────────────────────────┤
│ std_n_output │ 2.1213 │
╘══════════════╧═══════════════════════════════════════════╛
Experiment Metrics:
╒═══════════════════════╤══════════╕
│ Metric │ Value │
╞═══════════════════════╪══════════╡
│ MetricName.TTFT │ 0.7753 │
├───────────────────────┼──────────┤
│ MetricName.LATENCY │ 7.5016 │
├───────────────────────┼──────────┤
│ MetricName.TPOT │ 0.01 │
├───────────────────────┼──────────┤
│ MetricName.THROUGHPUT │ 207.84 │
╘═══════════════════════╧══════════╛
For more information on available commands and options, run:
compressa-perf --help
License
This project is licensed under the MIT License. See the LICENSE file for more details.
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