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Torchmetrics usage improvements with classes instead of functionals #2095

Torchmetrics usage improvements with classes instead of functionals

Torchmetrics usage improvements with classes instead of functionals #2095

Workflow file for this run

name: test
on:
push:
branches: ["main"]
tags: ["*"]
pull_request:
branches:
- "*"
- "!gh-pages"
schedule:
- cron: "0 4 * * *"
jobs:
test:
strategy:
fail-fast: false
matrix:
python-version: ["3.8", "3.9", "3.10"]
pytorch-version: ["2.0"]
runs-on: "ubuntu-latest"
timeout-minutes: 30
defaults:
run:
shell: bash -l {0}
name: |
regular_env -
python=${{ matrix.python-version }} -
pytorch=${{ matrix.pytorch-version }}
steps:
- name: Checkout the code
uses: actions/checkout@v3
- name: Setup mamba
uses: mamba-org/setup-micromamba@v1
with:
environment-file: env.yml
environment-name: graphium
cache-environment: true
cache-downloads: true
create-args: >-
python=${{ matrix.python-version }}
pytorch=${{ matrix.pytorch-version }}
- name: Install library
run: python -m pip install --no-deps -e . # `-e` required for correct `coverage` run.
- name: Run tests
run: pytest -m 'not ipu'
- name: Test CLI
run: graphium --help
- name: Test building the doc
run: mkdocs build
- name: Codecov Upload
uses: codecov/codecov-action@v3
with:
files: ./coverage.xml
flags: unittests
name: codecov-umbrella
fail_ci_if_error: false
verbose: false
env_vars: ${{ matrix.python-version }},${{ matrix.pytorch-version }}