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Change ScaNN submission to pin version and use all available cores. (… #844

Change ScaNN submission to pin version and use all available cores. (…

Change ScaNN submission to pin version and use all available cores. (… #844

Workflow file for this run

# Contributed by @GuilhemN in https://github.com/erikbern/ann-benchmarks/pull/233
name: Billion-Scale ANN Benchmarks, NeurIPS 2021
on: [push, pull_request]
jobs:
build:
runs-on: ubuntu-latest
strategy:
matrix:
include:
# - algorithm: faiss-ivf
# library: faissconda
# dataset: random-xs
- algorithm: faiss-t1
dataset: random-xs
library: faissconda
# - algorithm: puck-t1
# dataset: random-xs
# library: puck
# - algorithm: faiss-t1
# dataset: random-range-xs
# library: faissconda
# - algorithm: diskann-t2
# dataset: random-xs
# library: diskann
# - algorithm: diskann-t2
# dataset: random-range-xs
# library: diskann
- algorithm: bbann
dataset: random-xs
library: bbann
- algorithm: bbann
dataset: random-range-xs
library: bbann
# - algorithm: httpann_example
# dataset: random-xs
# library: httpann_example
# - algorithm: httpann_example
# dataset: random-range-xs
# library: httpann_example
# - algorithm : kst_ann_t1
# dataset: random-xs
# library: kst_ann_t1
# - algorithm: buddy-t1
# dataset: random-xs
# library: faissconda
# - algorithm: buddy-t1
# dataset: random-range-xs
# library: faissconda
# - algorithm: kota-t2
# dataset: random-xs
# library: kota
# - algorithm: kota-t2
# dataset: random-range-xs
# library: kota
# - algorithm: team11
# dataset: random-xs
# library: faissconda
fail-fast: false
steps:
- uses: actions/checkout@v2 # Pull the repository
- name: Set up Python 3.10
uses: actions/setup-python@v2
with:
python-version: '3.10'
- name: Install dependencies
run: |
pip install -r requirements_py3.10.txt
python install.py
env:
LIBRARY: ${{ matrix.library }}
DATASET: ${{ matrix.dataset }}
- name: Run the benchmark
run: |
python create_dataset.py --dataset $DATASET
python run.py --algorithm $ALGORITHM --max-n-algorithms 2 --dataset $DATASET --timeout 600
sudo chmod -R 777 results/
python plot.py --dataset $DATASET --output plot.png
python data_export.py --output test.csv
env:
ALGORITHM: ${{ matrix.algorithm}}
DATASET: ${{ matrix.dataset }}