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Adding 2 fixes, for using batched ptensorlayers #9

Adding 2 fixes, for using batched ptensorlayers

Adding 2 fixes, for using batched ptensorlayers #9

Workflow file for this run

# Runs all the Python SDK tests within the `tests/` directory to check our code
name: CI Tests with GPU/CUDA build
permissions: read-all
on:
workflow_dispatch:
push:
branches:
- main
- master
pull_request:
branches:
- main
- master
- dev**
concurrency:
# github.workflow: name of the workflow
# github.event.pull_request.number || github.ref: pull request number or branch name if not a pull request
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
# Cancel in-progress runs when a new workflow with the same group name is triggered
cancel-in-progress: true
jobs:
pytest-gpu:
name: pytest (${{ matrix.python-version }}, ${{ matrix.os }})
runs-on: ${{ matrix.os }}
defaults:
run:
shell: bash -l {0}
strategy:
fail-fast: false
matrix:
os: ["ubuntu-latest"]
python-version: ["3.10", "3.12"]
steps:
- name: Checkout
uses: actions/checkout@v4
- uses: conda-incubator/setup-miniconda@v3
with:
auto-update-conda: true
python-version: ${{ matrix.python-version }}
environment-file: environment-gpu.yml
activate-environment: ptens
- name: Install Missing Developper packages
# We use pip here, since conda isn't very happy with the total env, but it works...
run: pip install pytest
- name: Install cnine
run: |
git clone https://github.com/risi-kondor/cnine.git
cd cnine
git checkout dev
# pip install python/
cd ..
- name: Install and build
run: |
export CNINE_FOLDER="/../cnine/"
export WITH_CUDA=True
export CUDA_HOME=$CONDA_PREFIX
# Pretending we have a CUDA capable card on the runner
export TORCH_CUDA_ARCH_LIST="7.5"
pip install python/
# TODO activate pytests when ready
- name: Test with pytest
run: |
# pytest python/tests
mkdir ./tmp-run/
cd ./tmp-run/
# This fails due to actually missing CUDA driver, but that's OK
# Testing for build alone is nice already
# python -c "import ptens"