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docs: image tags #499

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May 10, 2021
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docs: image tags
casperdcl May 7, 2021
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tag examples
casperdcl May 10, 2021
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27 changes: 18 additions & 9 deletions README.md
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Expand Up @@ -67,7 +67,7 @@ jobs:
run:
runs-on: [ubuntu-latest]
# optionally use a convenient Ubuntu LTS + CUDA + DVC + CML image
# container: docker://dvcorg/cml-py3:latest
# container: docker://dvcorg/cml:0-dvc2-base1-gpu
steps:
- uses: actions/checkout@v2
# may need to setup NodeJS & Python3 on e.g. self-hosted
Expand Down Expand Up @@ -95,9 +95,9 @@ jobs:
We helpfully provide CML and other useful libraries pre-installed on our
[custom Docker images](https://github.com/iterative/cml/blob/master/docker/Dockerfile).
In the above example, uncommenting the field
`container: docker://dvcorg/cml-py3:latest` will make the GitHub Actions runner
pull the CML Docker image. The image already has NodeJS, Python 3, DVC and CML
set up on an Ubuntu LTS base with CUDA libraries and
`container: docker://dvcorg/cml:0-dvc2-base1-gpu` will make the GitHub Actions
runner pull the CML Docker image. The image already has NodeJS, Python 3, DVC
and CML set up on an Ubuntu LTS base with CUDA libraries and
[Terraform](https://www.terraform.io) installed for convenience.

### CML Functions
Expand Down Expand Up @@ -233,7 +233,7 @@ on: [push]
jobs:
run:
runs-on: [ubuntu-latest]
container: docker://dvcorg/cml-py3:latest
container: docker://dvcorg/cml:0-dvc2-base1
steps:
- uses: actions/checkout@v2
- name: Train model
Expand Down Expand Up @@ -403,7 +403,7 @@ jobs:
model-training:
needs: [deploy-runner]
runs-on: [self-hosted, cml-runner]
container: docker://dvcorg/cml-py3:latest
container: docker://dvcorg/cml:0-dvc2-base1-gpu
steps:
- uses: actions/checkout@v2
- name: Train model
Expand All @@ -427,9 +427,18 @@ newly-launched instance.
> favourite training environment in the cloud by pulling the Docker container of
> your choice.

We like the CML container (`docker://dvcorg/cml-py3`) because it comes loaded
with Python, CUDA, `git`, `node` and other essentials for full-stack data
science.
We like the CML container (`docker://dvcorg/cml`) because it comes loaded with
Python, CUDA, `git`, `node` and other essentials for full-stack data science.
Different versions of these essentials are available from different `dvcorg/cml`
image tags. The tag convention is `{CML_VER}-dvc{DVC_VER}-base{BASE_VER}{-gpu}`:

| `{BASE_VER}` | Software included (`-gpu`) |
| ------------ | ----------------------------------------------- |
| 0 | Ubuntu 18.04, Python 2.7 (CUDA 10.1, CuDNN 7) |
| 1 | Ubuntu 20.04, Python 3.8 (CUDA 11.0.3, CuDNN 8) |
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For example, `docker://dvcorg/cml:0-dvc2-base1-gpu`, or
`docker://ghcr.io/iterative/cml:0-dvc2-base1`.

### Arguments

Expand Down