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[WIP] RL training infra for primitives #1057

[WIP] RL training infra for primitives

[WIP] RL training infra for primitives #1057

Workflow file for this run

name: Tests
on: [pull_request]
concurrency:
group: ${{ github.workflow }}-${{ github.event_name == 'pull_request' && github.head_ref || github.sha }}
cancel-in-progress: true
jobs:
test:
runs-on: [self-hosted, linux, gpu, dataset-enabled]
defaults:
run:
shell: micromamba run -n omnigibson /bin/bash -leo pipefail {0}
steps:
- name: Fix home
run: echo "HOME=/root" >> $GITHUB_ENV
- name: Checkout source
uses: actions/checkout@v2
with:
submodules: true
path: omnigibson-src
- name: Install dev requirements
working-directory: omnigibson-src
run: pip install -r requirements-dev.txt
- name: Install
working-directory: omnigibson-src
run: pip install -e .
- name: Run tests
working-directory: omnigibson-src
run: source /isaac-sim/setup_conda_env.sh && pytest
# - name: Upload coverage to Codecov
# uses: codecov/[email protected]
# with:
# token: ${{ secrets.CODECOV_TOKEN }}