Skip to content

Commit

Permalink
Merge branch 'main' into ops-bot
Browse files Browse the repository at this point in the history
  • Loading branch information
oliverholworthy authored Jun 2, 2023
2 parents 9d5cdeb + 6dd49c9 commit 4a4e504
Show file tree
Hide file tree
Showing 38 changed files with 1,112 additions and 935 deletions.
45 changes: 25 additions & 20 deletions .github/workflows/docs-sched-rebuild.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,10 @@ jobs:
- name: Install dependencies
run: |
python -m pip install --upgrade pip setuptools==59.4.0 wheel tox
- name: Setup local branches for docs build
run: |
git branch --track main origin/main || true
git branch --track stable origin/stable || true
- name: Building docs (multiversion)
run: |
tox -e docs-multi
Expand Down Expand Up @@ -83,27 +87,28 @@ jobs:
exit 0
fi
# If any of these commands fail, fail the build.
def_branch=$(gh api "repos/${GITHUB_REPOSITORY}" --jq ".default_branch")
def_branch="stable"
html_url=$(gh api "repos/${GITHUB_REPOSITORY}/pages" --jq ".html_url")
# Beware ugly quotation mark avoidance in the foll lines.
echo '<!DOCTYPE html>' > index.html
echo '<html>' >> index.html
echo ' <head>' >> index.html
echo ' <title>Redirect to documentation</title>' >> index.html
echo ' <meta charset="utf-8">' >> index.html
echo ' <meta http=equiv="refresh" content="3; URL='${html_url}${def_branch}'/index.html">' >> index.html
echo ' <link rel="canonical" href="'${html_url}${def_branch}'/index.html">' >> index.html
echo ' <script language="javascript">' >> index.html
echo ' function redirect() {' >> index.html
echo ' window.location.assign("'${html_url}${def_branch}'/index.html")' >> index.html
echo ' }' >> index.html
echo ' </script>' >> index.html
echo ' </head>' >> index.html
echo ' <body onload="redirect()">' >> index.html
echo ' <p>Please follow the link to the <a href="'${html_url}${def_branch}'/index.html">' >> index.html
echo ${def_branch}'</a> branch documentation.</p>' >> index.html
echo ' </body>' >> index.html
echo '</html>' >> index.html
cat > index.html << EOF
<!DOCTYPE html>
<html>
<head>
<title>Redirect to documentation</title>
<meta charset="utf-8">
<meta http=equiv="refresh" content="3; URL="${html_url}${def_branch}/index.html"
<link rel="canonical" href="'${html_url}${def_branch}/index.html">
<script language="javascript">
function redirect() {
window.location.assign("${html_url}${def_branch}/index.html")
}
</script>
</head>
<body onload="redirect()">
<p>Please follow the link to the <a href="${html_url}${def_branch}/index.html">
${def_branch}'</a> branch documentation.</p>
</body>
</html>
EOF
git add index.html
- name: Commit changes to the GitHub Pages branch
run: |
Expand Down
2 changes: 1 addition & 1 deletion CONTRIBUTING.md
Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@ into three categories:

### Your first issue

1. Read the project's [README.md](https://github.com/nvidia/NVTabular/blob/main/README.md)
1. Read the project's [README.md](https://github.com/nvidia/NVTabular/blob/stable/README.md)
to learn how to setup the development environment.
2. Find an issue to work on. The best way is to look for the
[good first issue](https://github.com/nvidia/NVTabular/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22)
Expand Down
20 changes: 10 additions & 10 deletions README.md
Original file line number Diff line number Diff line change
@@ -1,8 +1,8 @@
## [NVTabular](https://github.com/NVIDIA/NVTabular)

[![PyPI](https://img.shields.io/pypi/v/NVTabular?color=orange&label=version)](https://pypi.python.org/pypi/NVTabular/)
[![LICENSE](https://img.shields.io/github/license/NVIDIA-Merlin/NVTabular)](https://github.com/NVIDIA-Merlin/NVTabular/blob/main/LICENSE)
[![Documentation](https://img.shields.io/badge/documentation-blue.svg)](https://nvidia-merlin.github.io/NVTabular/main/Introduction.html)
[![LICENSE](https://img.shields.io/github/license/NVIDIA-Merlin/NVTabular)](https://github.com/NVIDIA-Merlin/NVTabular/blob/stable/LICENSE)
[![Documentation](https://img.shields.io/badge/documentation-blue.svg)](https://nvidia-merlin.github.io/NVTabular/stable/Introduction.html)

NVTabular is a feature engineering and preprocessing library for tabular data that is designed to easily manipulate terabyte scale datasets and train deep learning (DL) based recommender systems. It provides high-level abstraction to simplify code and accelerates computation on the GPU using the [RAPIDS Dask-cuDF](https://github.com/rapidsai/cudf/tree/main/python/dask_cudf) library.

Expand All @@ -26,7 +26,7 @@ NVTabular alleviates these challenges and helps data scientists and ML engineers
- prepare datasets quickly and easily for experimentation so that more models can be trained.
- deploy models into production by providing faster dataset transformation

Learn more in the NVTabular [core features documentation](https://nvidia-merlin.github.io/NVTabular/main/core_features.html).
Learn more in the NVTabular [core features documentation](https://nvidia-merlin.github.io/NVTabular/stable/core_features.html).

### Performance

Expand Down Expand Up @@ -74,11 +74,11 @@ The following table summarizes the key information about the containers:
| merlin-tensorflow | https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-tensorflow | NVTabular, Tensorflow and Triton Inference |
| merlin-pytorch | https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-pytorch | NVTabular, PyTorch, and Triton Inference |

To use these Docker containers, you'll first need to install the [NVIDIA Container Toolkit](https://github.com/NVIDIA/nvidia-docker) to provide GPU support for Docker. You can use the NGC links referenced in the table above to obtain more information about how to launch and run these containers. To obtain more information about the software and model versions that NVTabular supports per container, see [Support Matrix](https://github.com/NVIDIA/NVTabular/blob/main/docs/source/resources/support_matrix.rst).
To use these Docker containers, you'll first need to install the [NVIDIA Container Toolkit](https://github.com/NVIDIA/nvidia-docker) to provide GPU support for Docker. You can use the NGC links referenced in the table above to obtain more information about how to launch and run these containers. To obtain more information about the software and model versions that NVTabular supports per container, see [Support Matrix](https://github.com/NVIDIA/NVTabular/blob/stable/docs/source/resources/support_matrix.rst).

### Notebook Examples and Tutorials

We provide a [collection of examples](https://github.com/NVIDIA-Merlin/NVTabular/tree/main/examples) to demonstrate feature engineering with NVTabular as Jupyter notebooks:
We provide a [collection of examples](https://github.com/NVIDIA-Merlin/NVTabular/tree/stable/examples) to demonstrate feature engineering with NVTabular as Jupyter notebooks:

- Introduction to NVTabular's High-Level API
- Advanced workflows with NVTabular
Expand All @@ -87,13 +87,13 @@ We provide a [collection of examples](https://github.com/NVIDIA-Merlin/NVTabular

In addition, NVTabular is used in many of our examples in other Merlin libraries:

- [End-To-End Examples with Merlin](https://github.com/NVIDIA-Merlin/Merlin/tree/main/examples)
- [Training Examples with Merlin Models](https://github.com/NVIDIA-Merlin/models/tree/main/examples)
- [Training Examples with Transformer4Rec](https://github.com/NVIDIA-Merlin/Transformers4Rec/tree/main/examples)
- [End-To-End Examples with Merlin](https://github.com/NVIDIA-Merlin/Merlin/tree/stable/examples)
- [Training Examples with Merlin Models](https://github.com/NVIDIA-Merlin/models/tree/stable/examples)
- [Training Examples with Transformer4Rec](https://github.com/NVIDIA-Merlin/Transformers4Rec/tree/stable/examples)

### Feedback and Support

If you'd like to contribute to the library directly, see the [Contributing.md](https://github.com/NVIDIA/NVTabular/blob/main/CONTRIBUTING.md). We're particularly interested in contributions or feature requests for our feature engineering and preprocessing operations. To further advance our Merlin Roadmap, we encourage you to share all the details regarding your recommender system pipeline in this [survey](https://developer.nvidia.com/merlin-devzone-survey).
If you'd like to contribute to the library directly, see the [Contributing.md](https://github.com/NVIDIA/NVTabular/blob/stable/CONTRIBUTING.md). We're particularly interested in contributions or feature requests for our feature engineering and preprocessing operations. To further advance our Merlin Roadmap, we encourage you to share all the details regarding your recommender system pipeline in this [survey](https://developer.nvidia.com/merlin-devzone-survey).

If you're interested in learning more about how NVTabular works, see
[our NVTabular documentation](https://nvidia-merlin.github.io/NVTabular/main/Introduction.html). We also have [API documentation](https://nvidia-merlin.github.io/NVTabular/main/api/index.html) that outlines the specifics of the available calls within the library.
[our NVTabular documentation](https://nvidia-merlin.github.io/NVTabular/stable/Introduction.html). We also have [API documentation](https://nvidia-merlin.github.io/NVTabular/stable/api/index.html) that outlines the specifics of the available calls within the library.
Loading

0 comments on commit 4a4e504

Please sign in to comment.