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Merge pull request #342 from mlf-core/release/1.11.1
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release/1.11.1
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Zethson committed Apr 16, 2021
2 parents 77ec9a5 + eab3ce2 commit 2a5ea34
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2 changes: 1 addition & 1 deletion .cookietemple.yml
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Expand Up @@ -15,7 +15,7 @@ full_name: Lukas Heumos
email: lukas.heumos@posteo.net
project_name: mlf-core
project_short_description: Reproducible machine learning pipelines using mlflow.
version: 1.11.0
version: 1.11.1
license: Apache2.0
command_line_interface: Click
testing_library: pytest
14 changes: 14 additions & 0 deletions CHANGELOG.rst
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Expand Up @@ -6,6 +6,20 @@ Changelog

This project adheres to `Semantic Versioning <https://semver.org/>`_.

1.11.1 (2021-04-16)
-------------------

**Added**

**Fixed**

* XGBoost cudatoolkit channel

**Dependencies**

**Deprecated**


1.11.0 (2021-03-30)
-------------------

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2 changes: 1 addition & 1 deletion cookietemple.cfg
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@@ -1,5 +1,5 @@
[bumpversion]
current_version = 1.11.0
current_version = 1.11.1

[bumpversion_files_whitelisted]
setup_file = setup.py
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4 changes: 2 additions & 2 deletions docs/conf.py
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Expand Up @@ -53,9 +53,9 @@
# the built documents.
#
# The short X.Y version.
version = '1.11.0'
version = '1.11.1'
# The full version, including alpha/beta/rc tags.
release = '1.11.0'
release = '1.11.1'

# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
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42 changes: 33 additions & 9 deletions docs/tutorial.rst
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Expand Up @@ -7,9 +7,6 @@ Tutorial
Disclaimer
-----------

.. warning:: **This page is currently under development. Please check back later.**


.. warning:: This document serves as a single page tutorial for mlf-core, the issue of deterministic machine learning and everything related.
It is **not** supposed to be used as a reference documentation for specific pieces of information.
Please use the remaining mlf-core or the respective tools' documentation for this purpose.
Expand Down Expand Up @@ -139,10 +136,10 @@ To create a mlf-core project run:
The project creation process will now end with mlf-core lint verifying the successful creation if your project and the link to your Github repository being printed.
| You are now ready to start training deterministic machine learning models, but first let us have a look at the template's architecture and functionality.
.. figure:: images/project_github.png
:alt: Project on Github
.. figure:: images/mlf_core_create_tutorial.gif
:alt: Create process

A created project using the mlflow-pytorch template on Github
The project creation process with mlf-core

mlf-core project overview
----------------------------
Expand Down Expand Up @@ -324,10 +321,37 @@ Public Docker container on Github Packages
mlf-core by default pushes the Docker container using the ``publish_docker.yml`` Github Actions workflow to `Github Packages <https://github.com/features/packages>`_.
If you want to push your Docker container to a different registry you need to adapt the workflow and potentially update the username and add a Github secret for your password.
By default, containers pushed to Github are private. As a result you would need to log in to pull the container.


Hence, you have to make your Docker container public by navigating to the used Github account, selecting ``Packages`` and then your package.
On the right you will find a button ``package settings``. Scroll down on the package settings page and at the bottom you will find a button ``make public``.
Click it, authenticate and your Github container is now public!
Be aware of the fact that building the Docker container usually takes 15-20 minutes and therefore your Docker container will not immidiately show up in the Packages tab.

.. figure:: images/public_docker/step_1.png
:alt: Creating a public docker image

As of writing this, there is a bug with the GitHub UI, that doesn't show private images without selecting the visibility. Click visibility, and then private, and select your docker image.

.. figure:: images/public_docker/step_2.png
:alt: Private image bug

.. figure:: images/public_docker/step_3.png
:alt: Click your image

On the right you will find a button ``package settings``.

.. figure:: images/public_docker/step_4.png
:alt: Click Package Settings

Scroll down on the package settings page and at the bottom you will find a button ``Change visibility``.

.. figure:: images/public_docker/step_5.png
:alt: Click Change visibility

Select Public, type in your project name, click it, authenticate and your Github container is now public!

.. figure:: images/public_docker/step_6.png
:alt: Click Public

Be aware of the fact that building the Docker container usually takes 15-20 minutes and therefore your Docker container will not immediately show up in the Packages tab.

Publish documentation on Github Pages or Read the Docs
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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2 changes: 1 addition & 1 deletion mlf_core/__init__.py
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Expand Up @@ -2,4 +2,4 @@

__author__ = """Lukas Heumos"""
__email__ = 'lukas.heumos@posteo.net'
__version__ = '1.11.0'
__version__ = '1.11.1'
2 changes: 1 addition & 1 deletion setup.py
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Expand Up @@ -72,6 +72,6 @@ def walker(base, *paths):
test_suite='tests',
tests_require=test_requirements,
url='https://github.com/mlf-core/mlf-core',
version='1.11.0',
version='1.11.1',
zip_safe=False,
)

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