Skip to content

utilize memory mapped numpy arrays for sharding to reduce memory burden #189

utilize memory mapped numpy arrays for sharding to reduce memory burden

utilize memory mapped numpy arrays for sharding to reduce memory burden #189

# This is a basic workflow to help you get started with Actions
name: Build Documentation
on: [push]
jobs:
build-linux:
runs-on: ubuntu-latest
strategy:
max-parallel: 5
steps:
- uses: actions/checkout@v2
- name: Set up Python 3.10
uses: actions/setup-python@v2
with:
python-version: '3.10'
- name: Add conda to system path
run: |
# $CONDA is an environment variable pointing to the root of the miniconda directory
echo $CONDA/bin >> $GITHUB_PATH
- name: Install Dependencies with Mamba
run: |
conda env update -n base --file .github/workflows/environment.yml
- name: Install Repository Module
run: |
pip install ./