new dist file and updated file links

.gitlab/issue_templates/release.md

@@ -15,7 +15,7 @@ vX.Y.Z
 * [ ] Update version number in `mlair/__ init__.py`
 * [ ] Create new dist file: `python3 setup.py sdist bdist_wheel`
 * [ ] Update file link `distribution file (current version)` in `README.md`
-* [ ] Update file link in `docs/_source/get-started.rst`
+* [ ] Update file link in `docs/_source/installation.rst`
 * [ ] Commit + push
 * [ ] Merge `release_vX.Y.Z` into `master`
 * [ ] Create new tag with

README.md

@@ -31,7 +31,7 @@ HPC systems, see [here](#special-instructions-for-installation-on-jülich-hpc-sy
 * Installation of **MLAir**:
     * Either clone MLAir from the [gitlab repository](https://gitlab.version.fz-juelich.de/toar/mlair.git) 
       and use it without installation (beside the requirements) 
-    * or download the distribution file ([current version](https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/dist/mlair-1.2.1-py3-none-any.whl)) 
+    * or download the distribution file ([current version](https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/dist/mlair-1.3.0-py3-none-any.whl)) 
       and install it via `pip install <dist_file>.whl`. In this case, you can simply import MLAir in any python script 
       inside your virtual environment using `import mlair`.
 * (tf) Currently, TensorFlow-1.13 is mentioned in the requirements. We already tested the TensorFlow-1.15 version and couldn't

docs/_source/installation.rst

@@ -26,7 +26,7 @@ Installation of MLAir
 * Install all requirements from `requirements.txt <https://gitlab.version.fz-juelich.de/toar/machinelearningtools/-/blob/master/requirements.txt>`_
   preferably in a virtual environment
 * Either clone MLAir from the `gitlab repository <https://gitlab.version.fz-juelich.de/toar/machinelearningtools.git>`_
-* or download the distribution file (`current version <https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/dist/mlair-1.2.0-py3-none-any.whl>`_)
+* or download the distribution file (`current version <https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/dist/mlair-1.3.0-py3-none-any.whl>`_)
   and install it via :py:`pip install <dist_file>.whl`. In this case, you can simply
   import MLAir in any python script inside your virtual environment using :py:`import mlair`.
 * (tf) Currently, TensorFlow-1.13 is mentioned in the requirements. We already tested the TensorFlow-1.15 version and couldn't

mlair/__init__.py

 __version_info__ = {
     'major': 1,
-    'minor': 2,
-    'micro': 1,
+    'minor': 3,
+    'micro': 0,
 }
 
 from mlair.run_modules import RunEnvironment, ExperimentSetup, PreProcessing, ModelSetup, Training, PostProcessing