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🚀 Bump version and CHANGELOG for release 0.7.3 (#223)
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github-actions authored and Galileo-Galilei committed Aug 16, 2021
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8 changes: 6 additions & 2 deletions CHANGELOG.md
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## [Unreleased]

## [0.7.3] - 2021-08-16

### Added

- :sparkles: Update the ``MlflowArtifactDataSet.load()`` method to download the data from the ``run_id`` if it is specified instead of using the local filepath. This can be used for instance to continue training from a pretrained model or to retrieve the best model from an hyperparameter search ([#95](https://github.com/Galileo-Galilei/kedro-mlflow/issues/95))
- :sparkles: Update the `MlflowArtifactDataSet.load()` method to download the data from the `run_id` if it is specified instead of using the local filepath. This can be used for instance to continue training from a pretrained model or to retrieve the best model from an hyperparameter search ([#95](https://github.com/Galileo-Galilei/kedro-mlflow/issues/95))

## [0.7.2] - 2021-05-02

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- Add `MlflowDataSet` for artifacts autologging
- Add `PipelineMl` class and its `pipeline_ml` factory for pipeline packaging and service

[Unreleased]: https://github.com/Galileo-Galilei/kedro-mlflow/compare/0.7.2...HEAD
[Unreleased]: https://github.com/Galileo-Galilei/kedro-mlflow/compare/0.7.3...HEAD

[0.7.3]: https://github.com/Galileo-Galilei/kedro-mlflow/compare/0.7.2...0.7.3

[0.7.2]: https://github.com/Galileo-Galilei/kedro-mlflow/compare/0.7.1...0.7.2

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2 changes: 1 addition & 1 deletion README.md
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----------------------------------------------------------
| Branch | Tests | Coverage | Documentation | Deployment | Activity |
|--------|-------|----------|---------------|------------|------------|
| `master` | [![test](https://github.com/Galileo-Galilei/kedro-mlflow/workflows/test/badge.svg?branch=master)](https://github.com/Galileo-Galilei/kedro-mlflow/actions?query=workflow%3Atest+branch%3Amaster) | [![codecov](https://codecov.io/gh/Galileo-Galilei/kedro-mlflow/branch/master/graph/badge.svg)](https://codecov.io/gh/Galileo-Galilei/kedro-mlflow/branch/master)|[![Documentation](https://readthedocs.org/projects/kedro-mlflow/badge/?version=stable)](https://kedro-mlflow.readthedocs.io/en/stable/)|[![publish](https://github.com/Galileo-Galilei/kedro-mlflow/workflows/publish/badge.svg?branch=master)](https://github.com/Galileo-Galilei/kedro-mlflow/actions?query=branch%3Amaster+workflow%3Apublish)|[![commit](https://img.shields.io/github/commits-since/Galileo-Galilei/kedro-mlflow/0.7.2)](https://github.com/Galileo-Galilei/kedro-mlflow/compare/0.7.2...master)|
| `master` | [![test](https://github.com/Galileo-Galilei/kedro-mlflow/workflows/test/badge.svg?branch=master)](https://github.com/Galileo-Galilei/kedro-mlflow/actions?query=workflow%3Atest+branch%3Amaster) | [![codecov](https://codecov.io/gh/Galileo-Galilei/kedro-mlflow/branch/master/graph/badge.svg)](https://codecov.io/gh/Galileo-Galilei/kedro-mlflow/branch/master)|[![Documentation](https://readthedocs.org/projects/kedro-mlflow/badge/?version=stable)](https://kedro-mlflow.readthedocs.io/en/stable/)|[![publish](https://github.com/Galileo-Galilei/kedro-mlflow/workflows/publish/badge.svg?branch=master)](https://github.com/Galileo-Galilei/kedro-mlflow/actions?query=branch%3Amaster+workflow%3Apublish)|[![commit](https://img.shields.io/github/commits-since/Galileo-Galilei/kedro-mlflow/0.7.3)](https://github.com/Galileo-Galilei/kedro-mlflow/compare/0.7.3...master)|

# What is kedro-mlflow?

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4 changes: 2 additions & 2 deletions docs/source/01_introduction/02_motivation.md
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|Logging metrics |``catalog.yml`` |``MlflowMetricsDataSet`` |
|Logging Pipeline as model |``hooks.py`` |``KedroPipelineModel`` and ``pipeline_ml_factory``|

In the current version (``kedro_mlflow=0.7.2``), `kedro-mlflow` does not provide interface to set tags outside a Kedro ``Pipeline``. Some of above decisions are subject to debate and design decisions (for instance, metrics are often updated in a loop during each epoch / training iteration and it does not always make sense to register the metric between computation steps, e.g. as a an I/O operation after a node run).
In the current version (``kedro_mlflow=0.7.3``), `kedro-mlflow` does not provide interface to set tags outside a Kedro ``Pipeline``. Some of above decisions are subject to debate and design decisions (for instance, metrics are often updated in a loop during each epoch / training iteration and it does not always make sense to register the metric between computation steps, e.g. as a an I/O operation after a node run).

_**Note:** the version ``0.7.2`` does not need any ``MLProject`` file to use mlflow inside your Kedro project. As seen in the [introduction](./01_introduction.md), this file overlaps with Kedro configuration files._
_**Note:** the version ``0.7.3`` does not need any ``MLProject`` file to use mlflow inside your Kedro project. As seen in the [introduction](./01_introduction.md), this file overlaps with Kedro configuration files._
4 changes: 2 additions & 2 deletions docs/source/02_installation/01_installation.md
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the Kedro initiative at QuantumBlack.

Installed plugins:
kedro_mlflow: 0.7.2 (hooks:global,project)
kedro_mlflow: 0.7.3 (hooks:global,project)
```

The version ``0.7.2`` of the plugin is installed and has both global and project commands.
The version ``0.7.3`` of the plugin is installed and has both global and project commands.

That's it! You are now ready to go!

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```console
conda create -n km_example python=3.6.8 --yes
conda activate km_example
pip install kedro-mlflow==0.7.2
pip install kedro-mlflow==0.7.3
```

## Install the toy project
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## Automatic parameters versioning

Parameters versioning is automatic when the ``MlflowNodeHook`` is added to [the hook list of the ``ProjectContext``](../02_installation/02_setup.md#declaring-kedro-mlflow-hooks). In ``kedro-mlflow==0.7.2``, the `mlflow.yml` configuration file has a parameter called ``flatten_dict_params`` which enables to [log as distinct parameters the (key, value) pairs of a ```Dict`` parameter](../07_python_objects/02_Hooks.md).
Parameters versioning is automatic when the ``MlflowNodeHook`` is added to [the hook list of the ``ProjectContext``](../02_installation/02_setup.md#declaring-kedro-mlflow-hooks). In ``kedro-mlflow==0.7.3``, the `mlflow.yml` configuration file has a parameter called ``flatten_dict_params`` which enables to [log as distinct parameters the (key, value) pairs of a ```Dict`` parameter](../07_python_objects/02_Hooks.md).

You **do not need any additional configuration** to benefit from parameters versioning.

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You can refer to [this issue](https://github.com/Galileo-Galilei/kedro-mlflow/issues/15) for further details.

In ``kedro-mlflow==0.7.2`` you must configure these elements by yourself. Further releases will introduce helpers for configuration.
In ``kedro-mlflow==0.7.3`` you must configure these elements by yourself. Further releases will introduce helpers for configuration.

### Can I log an artifact in a specific run?

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2 changes: 1 addition & 1 deletion kedro_mlflow/__init__.py
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"""kedro-mlflow plugin constants
"""
__version__ = "0.7.2"
__version__ = "0.7.3"
2 changes: 1 addition & 1 deletion setup.cfg
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[bumpversion]
current_version = 0.7.2
current_version = 0.7.3

[tool:pytest]
addopts = --cov=kedro_mlflow --cov-report=html tests/
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2 changes: 1 addition & 1 deletion setup.py
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setup(
name=NAME,
version="0.7.2", # this will be bumped automatically by bump2version
version="0.7.3", # this will be bumped automatically by bump2version
description="A kedro-plugin to use mlflow in your kedro projects",
license="Apache Software License (Apache 2.0)",
long_description=README,
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