Skip to main content

cli

Project description

ANC CLI Tool

Overview

The ANC CLI tool is a comprehensive command line interface designed to facilitate the management of various resources within the company. Initially, it supports managing datasets and their versions, enabling users to interact seamlessly with a remote server for fetching, listing, and adding datasets.

Installation

For User

# Instructions for installing the ANC CLI tool
sudo pip install anc

For cli Develop

# Instructions for installing the ANC CLI tool
cd dev/cli
sudo pip install -r requirements.txt
sudo pip install -e .

for release

For build and release instructions, see Release Guide.

Dataset

  • Fetch Datasets: Retrieve specific versions of datasets from a remote server.
  • List Versions: View all available versions of a dataset.
  • Add Datasets: Upload new datasets along with their versions and descriptions to the remote server.

Usage

list

anc ds list 
# Or you can specify a dataset name.
anc ds list -n <dataset name>

get

# According to the above list result, you can download the specific version dataset.
# Ensure that the destination path for downloads is a permanent storage location(e.g. /mnt/weka/xxx). Currently, downloading data to local storage is not permitted.
anc ds get cifar-10-batches-py -v 1.0

add

# Upload a specific version of a dataset. The dataset name will be determined based on the file or folder name extracted from the specified path.
# Ensure that the dataset is stored in a permanent location recognized by the server (e.g., /mnt/weka/xxx).
anc ds add /mnt/weka/xug/dvc_temp/cifar-10-batches-py -v 1.0

load-test

load test with real data

pip install vllm

# Runload test. this will start the server and send the benchmark requests, save the results to the json file and plot the results
anc loadtest run \
--model /mnt/share/ocean/candidate1 \
--max-model-len 8000 \
--backend vllm \
--port 8004 \
--tensor-parallel-size "4" \
--enable-prefix-caching "True" \
---dataset-name anc \
---dataset-path /mnt/share/infra/hongbo/load_test_data/1000_ocean_prompt_pressure_test_v2_02_25.jsonl \
---num-prompts 300 \
---max-concurrency "1,2,4, 6, 8, 10, 12, 24" \
---dataset-name anc \
---dataset-path /mnt/share/infra/hongbo/load_test_data/1000_ocean_prompt_pressure_test_v2_02_25.jsonl \
---num-prompts 300 \
---max-concurrency "1,2,4, 6, 8, 10, 12, 24" \
--result-dir "./test" \
--gpu-memory-utilization 0.8 \
--seed 10


### you can also plot the results directly from the json file
anc loadtest plot --dataset-name anc ./test/all_results.json
## # if you have multiple json files in the same directory, you can plot all of them by
anc loadtest plot --dataset-name anc ./test

load test with random data

anc loadtest run \
--model /mnt/project/llm/ckpt/stable_ckpts/Llama-3.2-1B/ \
--max-model-len 200 \
--backend vllm \
--port 8004 \
--dataset-name random \
--num-prompts 1 \
--max-concurrency "1" \
--random-input-len "10" \
--result-dir "./test"  \
--skip-server

load test with remote endpoint

grid search with server parametgers won't work with this method. as we won't be able to restart the remote server(i.e. TP will be what ever tp used by the endpoint). Also prefix caching will be controlled by server, so you might end up with very high hit rate if your request sample size is small

anc loadtest run \
--model /mnt/share/ocean/candidate1 \
 --model-id ocean-llm \
--backend vllm \
 --dataset-name anc \
 --dataset-path /mnt/share/infra/hongbo/load_test_data/1000_ocean_prompt_pressure_test_v2_02_25.jsonl \
 --num-prompts 10 \
 --max-concurrency "1,2, 4" \
 --result-dir "./test" \
 --seed 10 \
 --skip-server \
 --base-url "http://ocean-test-2.serving-prod.va-mlp.anuttacon.com" 

load test with remote endpoint

grid search with server parametgers won't work with this method. as we won't be able to restart the remote server(i.e. TP will be what ever tp used by the endpoint). Also prefix caching will be controlled by server, so you might end up with very high hit rate if your request sample size is small

anc loadtest run \
--model /mnt/share/ocean/candidate1 \
 --model-id ocean-llm \
--backend vllm \
 --dataset-name anc \
 --dataset-path /mnt/share/infra/hongbo/load_test_data/1000_ocean_prompt_pressure_test_v2_02_25.jsonl \
 --num-prompts 10 \
 --max-concurrency "1,2, 4" \
 --result-dir "./test" \
 --seed 10 \
 --skip-server \
 --base-url "http://ocean-test-2.serving-prod.va-mlp.anuttacon.com" 

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

anc-0.3.25.tar.gz (74.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

anc-0.3.25-py3-none-any.whl (89.2 kB view details)

Uploaded Python 3

File details

Details for the file anc-0.3.25.tar.gz.

File metadata

  • Download URL: anc-0.3.25.tar.gz
  • Upload date:
  • Size: 74.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.3 CPython/3.12.3 Linux/5.15.0-94-generic

File hashes

Hashes for anc-0.3.25.tar.gz
Algorithm Hash digest
SHA256 c929d5e3db33b2e84d86662627a53be6eae88c95e4faea8cfaadc10c0b46282b
MD5 b7fb9fa62bdad9d57ea78c8b1290dbee
BLAKE2b-256 e7cf3d4044fafab1d17d6c6b06562deb2c3425055fa1f6840bc038e0d48533be

See more details on using hashes here.

File details

Details for the file anc-0.3.25-py3-none-any.whl.

File metadata

  • Download URL: anc-0.3.25-py3-none-any.whl
  • Upload date:
  • Size: 89.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.3 CPython/3.12.3 Linux/5.15.0-94-generic

File hashes

Hashes for anc-0.3.25-py3-none-any.whl
Algorithm Hash digest
SHA256 1d7c52157400d75592e83220572605705ead4050b13d5eb98a48dbe628f332bf
MD5 158075773e220fd9738c9057994912b1
BLAKE2b-256 a4a988f4bedf0c22f430f73d14e6ad9beee3897bf9036abb4ab2af21661bd670

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page