Update docs for use cases with EURAC (#253)

* begin updating the use case documentation * add eurac use case to the documentation and small cleanup * remove reference to doc file that doesn't exist yet * update documentation for the use cases * add plugins back
interTwin-eu · Nov 28, 2024 · d05fb75 · d05fb75
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diff --git a/docs/use-cases/3dgan_doc.rst b/docs/use-cases/3dgan_doc.rst
@@ -1,7 +1,9 @@
 3DGAN
 =====
 
-This section covers the CERN use case that utilizes the `torch-lightning` framework for training and evaluation. Following you can find instructions to execute CERN use case and its integral scripts:
+This section covers the CERN use case that utilizes the `torch-lightning` framework 
+for training and evaluation. Following you can find instructions to execute CERN use 
+case and its integral scripts:
 
 itwinai x 3DGAN
 ---------------
@@ -10,128 +12,16 @@ itwinai x 3DGAN
    :parser: myst_parser.sphinx_
    :start-line: 2
 
-.. toctree::
-   :maxdepth: 5
-
-model.py
-++++++++
-
-.. literalinclude:: ../../use-cases/3dgan/model.py
-   :language: python
-
-
-trainer.py
-++++++++++
-.. literalinclude:: ../../use-cases/3dgan/trainer.py
-   :language: python
-
-
-saver.py
-++++++++
-
-.. literalinclude:: ../../use-cases/3dgan/saver.py
-   :language: python
-
-
-dataloader.py
-+++++++++++++
-
-.. literalinclude:: ../../use-cases/3dgan/dataloader.py
-   :language: python
-
-
-config.yaml
-+++++++++++
-
-This YAML file defines the pipeline configuration for the CERN use case.
-
-.. literalinclude:: ../../use-cases/3dgan/config.yaml
-   :language: yaml
-
-
-create_inference_sample.py
-++++++++++++++++++++++++++
-
-This file defines a pipeline configuration for the CERN use case inference.
-
-.. literalinclude:: ../../use-cases/3dgan/create_inference_sample.py
-   :language: python
-
-
-Dockerfile
-++++++++++
-
-.. literalinclude:: ../../use-cases/3dgan/Dockerfile
-   :language: bash
-
-
-SLURM job script for JSC (HDFML system)
-+++++++++++++++++++++++++++++++++++++++++
-
-.. literalinclude:: ../../use-cases/3dgan/slurm.jsc.sh
-   :language: bash
-
-
-SLURM job script for Vega Supercomputer (GPU partition)
-++++++++++++++++++++++++++++++++++++++++++++++++++++++++
-
-.. literalinclude:: ../../use-cases/3dgan/slurm.vega.sh
-   :language: bash
-
 
 interLink x 3DGAN
 -----------------
 
-This section covers the CERN use case integration with `interLink <https://github.com/interTwin-eu/interLink>`_ using ``itwinai``. The following files are integral to this use case:
-
-
-.. toctree::
-   :maxdepth: 5
-
-
-3dgan-inference-cpu.yaml
-++++++++++++++++++++++++
-
-.. literalinclude:: ../../use-cases/3dgan/interLink/3dgan-inference-cpu.yaml
-   :language: yaml
-
+The CERN use case also has an integration with the ``interLink`` tool. You can find
+the relevant files in the 
+`interLink folder on Github <https://github.com/interTwin-eu/itwinai/tree/main/use-cases/3dgan/interLink>`_.
+You can also look at the README for more information:
 
-3dgan-inference.yaml
-++++++++++++++++++++
 
-.. literalinclude:: ../../use-cases/3dgan/interLink/3dgan-inference.yaml
-   :language: yaml
-
-
-3dgan-train.yaml
-++++++++++++++++
-
-.. literalinclude:: ../../use-cases/3dgan/interLink/3dgan-train.yaml
-   :language: yaml
-
-
-
-.. .. automodule:: 3dgan.model
-..     :members:
-..     :undoc-members:
-..     :show-inheritance:
-
-.. .. automodule:: 3dgan.train
-..     :members:
-..     :undoc-members:
-..     :show-inheritance:
-
-.. .. automodule:: 3dgan.trainer
-..     :members:
-..     :undoc-members:
-..     :show-inheritance:
-
-.. .. automodule:: 3dgan.saver
-..     :members:
-..     :undoc-members:
-..     :show-inheritance:
-
-.. .. automodule:: 3dgan.dataloader
-..     :members:
-..     :undoc-members:
-..     :show-inheritance:
+.. include:: ../../use-cases/3dgan/interLink/README.md
+   :parser: myst_parser.sphinx_
+   :start-line: 0
diff --git a/docs/use-cases/cyclones_doc.rst b/docs/use-cases/cyclones_doc.rst
@@ -3,47 +3,14 @@ Tropical Cyclones Detection
 
 The code is adapted from the CMCC use case's
 `repository <https://github.com/CMCC-Foundation/ml-tropical-cyclones-detection>`_.
-
-To know more on the interTwin tropical cyclones detection use case and its DT, please visit the published deliverables,
-`D4.1 <https://zenodo.org/records/10417135>`_, 
-`D7.1 <https://zenodo.org/records/10417158>`_ and `D7.3 <https://zenodo.org/records/10224252>`_.
+To know more on the interTwin tropical cyclones detection use case and its DT, please 
+visit the published deliverables, `D4.1 <https://zenodo.org/records/10417135>`_, 
+`D7.1 <https://zenodo.org/records/10417158>`_ and 
+`D7.3 <https://zenodo.org/records/10224252>`_.
+You can find the relevant code in the
+`use case's folder on Github <https://github.com/interTwin-eu/itwinai/tree/main/use-cases/cyclones>`_,
+or by consulting the use case's README: 
 
 .. include:: ../../use-cases/cyclones/README.md
    :parser: myst_parser.sphinx_
    :start-line: 5
-
-pipeline.yaml
-+++++++++++++
-
-This YAML file defines the pipeline configuration for the CMCC use case.
-
-.. literalinclude:: ../../use-cases/cyclones/pipeline.yaml
-   :language: yaml
-
-train.py
-++++++++++
-.. literalinclude:: ../../use-cases/cyclones/train.py
-   :language: python
-
-dataloader.py
-+++++++++++++
-
-.. literalinclude:: ../../use-cases/cyclones/dataloader.py
-   :language: python
-
-trainer.py
-++++++++++
-.. literalinclude:: ../../use-cases/cyclones/trainer.py
-   :language: python
-
-startscript
-+++++++++++
-
-.. literalinclude:: ../../use-cases/cyclones/startscript.sh
-   :language: bash
-
-cyclones_vgg.py
-+++++++++++++++
-
-.. literalinclude:: ../../use-cases/cyclones/cyclones_vgg.py
-   :language: python
diff --git a/docs/use-cases/eurac_doc.rst b/docs/use-cases/eurac_doc.rst
@@ -0,0 +1,11 @@
+
+EURAC
+=====
+You can find the relevant code for the EURAC use case in the 
+`use case's folder on Github <https://github.com/interTwin-eu/itwinai/tree/main/use-cases/eurac>`_,
+or by consulting the use case's README: 
+
+
+.. include:: ../../use-cases/eurac/README.md
+   :parser: myst_parser.sphinx_
+   :start-line: 2
diff --git a/docs/use-cases/mnist_doc.rst b/docs/use-cases/mnist_doc.rst
@@ -1,7 +1,12 @@
 MNIST
 =====
 
-This section covers the MNIST use case, which utilizes the `torch-lightning` framework for training and evaluation. The following files are integral to this use case:
+This section covers the MNIST use case. This use case has been implemented using three
+different strategies, ``TensorFlow``, ``PyTorch`` and ``PyTorch Lightning``. You can 
+find the files relevant to this use case
+in the `use case's folder on Github <https://github.com/interTwin-eu/itwinai/tree/main/use-cases/mnist>`_.
+
+For more information on each implementation, consult their respective READMEs:
 
 Torch Lightning
 ---------------
@@ -11,169 +16,9 @@ Torch Lightning
    :start-line: 2
 
 
-.. toctree::
-   :maxdepth: 5
-
-dataloader.py
-+++++++++++++
-
-The `dataloader.py` script is responsible for loading the MNIST dataset and preparing it for training.
-
-.. literalinclude:: ../../use-cases/mnist/torch-lightning/dataloader.py
-   :language: python
-
-.. .. automodule:: torch-lightning.dataloader
-..    :members:
-..    :undoc-members:
-..    :show-inheritance:
-
-config.yaml
-+++++++++++
-
-This YAML file defines the pipeline configuration for the MNIST use case. It includes settings for the model, training, and evaluation.
-
-.. literalinclude:: ../../use-cases/mnist/torch-lightning/config.yaml
-   :language: yaml
-
-startscript
-+++++++++++
-
-The `startscript` is a shell script to initiate the training process. It sets up the environment and starts the training using the `train.py` script.
-
-.. literalinclude:: ../../use-cases/mnist/torch-lightning/startscript
-   :language: bash
-
-
-utils.py
-++++++++
-
-The `utils.py` script includes utility functions and classes that are used across the MNIST use case.
-
-.. literalinclude:: ../../use-cases/mnist/torch-lightning/utils.py
-   :language: python
-
-
-
-This section covers the MNIST use case, which utilizes the `torch` framework for training and evaluation. The following files are integral to this use case:
-
 PyTorch
 -------
 
 .. include:: ../../use-cases/mnist/torch/README.md
    :parser: myst_parser.sphinx_
    :start-line: 2
-
-
-
-.. toctree::
-   :maxdepth: 5
-
-dataloader.py
-+++++++++++++
-
-The `dataloader.py` script is responsible for loading the MNIST dataset and preparing it for training.
-
-.. literalinclude:: ../../use-cases/mnist/torch/dataloader.py
-   :language: python
-
-
-Dockerfile
-++++++++++
-
-.. literalinclude:: ../../use-cases/mnist/torch/Dockerfile
-   :language: bash
-
-
-create_inference_sample.py
-++++++++++++++++++++++++++
-
-This file defines a pipeline configuration for the MNIST use case inference.
-
-.. literalinclude:: ../../use-cases/mnist/torch/create_inference_sample.py
-   :language: python
-
-model.py
-++++++++
-
-The `model.py` script is responsible for loading a simple model.
-
-.. literalinclude:: ../../use-cases/mnist/torch/model.py
-   :language: python
-
-config.yaml
-+++++++++++
-
-This YAML file defines the pipeline configuration for the MNIST use case. It includes settings for the model, training, and evaluation.
-
-.. literalinclude:: ../../use-cases/mnist/torch/config.yaml
-   :language: yaml
-
-startscript.sh
-++++++++++++++
-
-The `startscript` is a shell script to initiate the training process. It sets up the environment and starts the training using the `train.py` script.
-
-.. literalinclude:: ../../use-cases/mnist/torch/startscript.sh
-   :language: bash
-
-
-saver.py
-++++++++
-...
-
-.. literalinclude:: ../../use-cases/mnist/torch/saver.py
-   :language: python
-
-
-runall.sh
-+++++++++
-
-.. literalinclude:: ../../use-cases/mnist/torch/runall.sh
-   :language: bash
-
-
-slurm.sh
-++++++++
-
-.. literalinclude:: ../../use-cases/mnist/torch/slurm.sh
-   :language: bash
-
-
-
-This section covers the MNIST use case, which utilizes the `tensorflow` framework for training and evaluation. The following files are integral to this use case:
-
-Tensorflow
-----------
-
-.. toctree::
-   :maxdepth: 5
-
-dataloader.py
-+++++++++++++
-
-The `dataloader.py` script is responsible for loading the MNIST dataset and preparing it for training.
-
-.. literalinclude:: ../../use-cases/mnist/tensorflow/dataloader.py
-   :language: python
-
-
-pipeline.yaml
-+++++++++++++
-
-This YAML file defines the pipeline configuration for the MNIST use case. It includes settings for the model, training, and evaluation.
-
-.. literalinclude:: ../../use-cases/mnist/tensorflow/pipeline.yaml
-   :language: yaml
-
-
-startscript.sh
-++++++++++++++
-
-The `startscript` is a shell script to initiate the training pipeline.
-
-.. literalinclude:: ../../use-cases/mnist/tensorflow/startscript.sh
-   :language: bash
-
-
-
-