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new 4bf3d01 [MXNET-307] Extend tutorial instructions (#10658)
4bf3d01 is described below
commit 4bf3d01d7e3868807f9c562084565c9eeeedd7b0
Author: ThomasDelteil <[email protected]>
AuthorDate: Wed Apr 25 08:37:21 2018 -0700
[MXNET-307] Extend tutorial instructions (#10658)
* extend tutorial instructions
* trigger build
* trigger build
---
example/README.md | 14 ++++++++++++++
1 file changed, 14 insertions(+)
diff --git a/example/README.md b/example/README.md
index 5e64126..542162c 100644
--- a/example/README.md
+++ b/example/README.md
@@ -30,8 +30,14 @@ Example applications or scripts should be submitted in this
`example` folder.
If you have a tutorial idea for the website, download the [ Jupyter notebook
tutorial
template](https://github.com/dmlc/mxnet/tree/master/example/MXNetTutorialTemplate.ipynb).
+#### Tutorial location
+
Notebook tutorials should be submitted in the `docs/tutorials` folder, so that
they maybe rendered in the [web site's tutorial
section](https://mxnet.incubator.apache.org/tutorials/index.html).
+Do not forget to udpdate the `docs/tutorials/index.md` for your tutorial to
show up on the website.
+
+#### Tutorial formatting
+
The site expects the format to be markdown, so export your notebook as a .md
via the Jupyter web interface menu (File > Download As > Markdown). Then, to
enable the download notebook button in the web site's UI
([example](https://mxnet.incubator.apache.org/tutorials/python/linear-regression.html)),
add the following as the last line of the file
([example](https://github.com/apache/incubator-mxnet/blame/master/docs/tutorials/python/linear-regression.md#L194)):
```
@@ -44,6 +50,14 @@ If you want some lines to show-up in the markdown but not in
the generated noteb
```
Typically when you have a `plt.imshow()` you want the image tag
`[png](img.png)` in the `.md` but not in the downloaded notebook as the user
will re-generate the plot at run-time.
+#### Tutorial tests
+
+As part of making sure all our tutorials are running correctly with the latest
version of MXNet, each tutorial is run automatically through a python2 and
python3 jupyter notebook kernel in the CI, in a GPU environment, checking for
errors and warnings.
+
+Add your own test here `tests/tutorials/test_tutorials.py`. (If you forget,
don't worry your PR will not pass the sanity check).
+
+If your tutorial depends on specific packages, simply add them to this
provisionning script: `ci/docker/install/ubuntu_tutorials.sh`
+
## <a name="list-of-examples"></a>List of examples
### <a name="language-binding-examples"></a>Languages Binding Examples
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