When should we update dvc.lock and dvc push in GitHub Actions?

^{Originally posted by **Hongbo-Miao** September 6, 2021}
Currently, my GitHub Actions workflow looks like this: when I open a pull request (change some model codes / params), CML creates a AWS EC2 instance, and DVC pull the data.

Here is my [current GitHub Actions workflow](https://github.com/Hongbo-Miao/hongbomiao.com/blob/078e097d71213f9a0e24b884c4d65fd78bf0ccfd/.github/workflows/cml.yaml#L53-L129):

Click to expand!

```yaml
cml-cloud-set-up-cloud:
name: CML (Cloud) - Set up cloud
runs-on: ubuntu-20.04
steps:
- name: Cancel previous runs
uses: styfle/cancel-workflow-action@0.9.1
with:
access_token: ${{ github.token }}
- name: Checkout
uses: actions/checkout@v2
- name: Set up CML
uses: iterative/setup-cml@v1
- name: Set up cloud
shell: bash
env:
REPO_TOKEN: ${{ secrets.CML_ACCESS_TOKEN }}
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
run: |
cml-runner \
--cloud=aws \
--cloud-region=us-west-2 \
--cloud-type=t2.small \
--labels=cml-runner
cml-cloud-train:
name: CML (Cloud) - Train
needs: cml-cloud-set-up-cloud
runs-on: [self-hosted, cml-runner]
# container: docker://iterativeai/cml:0-dvc2-base1-gpu
container: docker://iterativeai/cml:0-dvc2-base1
steps:
- name: Cancel previous runs
uses: styfle/cancel-workflow-action@0.9.1
with:
access_token: ${{ github.token }}
- name: Checkout
uses: actions/checkout@v2
- name: Set up Miniconda
uses: conda-incubator/setup-miniconda@v2
with:
miniconda-version: "latest"
activate-environment: hm-cnn
- name: Install requirements
working-directory: convolutional-neural-network
shell: bash -l {0}
run: |
conda install pytorch torchvision torchaudio --channel=pytorch
conda install pandas
conda install tabulate
pip install -r requirements.txt
- name: Pull Data
working-directory: convolutional-neural-network
env:
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
run: |
dvc pull
- name: Train model
working-directory: convolutional-neural-network
shell: bash -l {0}
env:
WANDB_API_KEY: ${{ secrets.WANDB_API_KEY }}
run: |
dvc repro
- name: Write CML report
working-directory: convolutional-neural-network
shell: bash -l {0}
env:
REPO_TOKEN: ${{ secrets.CML_ACCESS_TOKEN }}
run: |
echo "# CML (Cloud) Report" >> report.md
echo "## Params" >> report.md
cat output/reports/params.txt >> report.md
cml-send-comment report.md
```

My [dvc.yaml](https://github.com/Hongbo-Miao/hongbomiao.com/blob/078e097d71213f9a0e24b884c4d65fd78bf0ccfd/convolutional-neural-network/dvc.yaml) looks like this:

```yaml
stages:
prepare:
cmd: tar -xf data/raw/cifar-10-python.tar.gz --dir=data/processed
deps:
- data/raw/cifar-10-python.tar.gz
outs:
- data/processed/cifar-10-batches-py/
main:
cmd: python main.py
deps:
- data/processed/cifar-10-batches-py/
- evaluate.py
- main.py
- model/
- train.py
params:
- lr
- train.epochs
outs:
- output/models/model.pt
```

After training, if I think the change is good because the performance is better based on the reports,

- the [dvc.lock](https://github.com/Hongbo-Miao/hongbomiao.com/blob/078e097d71213f9a0e24b884c4d65fd78bf0ccfd/convolutional-neural-network/dvc.lock) I feel needs to get update.
- the new model `model.pt` needs to be uploaded to AWS S3 in my case.

My question is, after `dvc repro`, am I supposed to add `dvc push` and then commit? Something like

```yaml
- name: Train model
working-directory: convolutional-neural-network
shell: bash -l {0}
env:
WANDB_API_KEY: ${{ secrets.WANDB_API_KEY }}
run: |
dvc repro
dvc push # New added
git add . # New added
git commit -m "update dvc.lock, etc." # New added
git push origin current_pr # New added, need somehow get the current pull request name
```

This above method will apply when the pull request is open.
However, I kind of feeling the best moment adding would be when I decide merging because I think this is a good pull request that actually improves the machine learning performance. But at this moment, the EC2 instance has been destroyed.

Any suggestion? Thanks!