Merge branch 'tensorflow-name' into 'preview'

Fix naming of tensorflow and pytorch docs

See merge request zih/hpc-compendium/hpc-compendium!219

doc.zih.tu-dresden.de/docs/jobs_and_resources/hpcda.md

@@ -56,11 +56,11 @@ Additional hardware:
 - [Get started with HPC-DA](../software/get_started_with_hpcda.md)
 - [IBM Power AI](../software/power_ai.md)
 - [Work with Singularity Containers on Power9]**todo** Cloud
-- [TensorFlow on HPC-DA (native)](../software/tensor_flow.md)
-- [Tensorflow on Jupyter notebook](../software/tensor_flow_on_jupyter_notebook.md)
+- [TensorFlow on HPC-DA (native)](../software/tensorflow.md)
+- [Tensorflow on Jupyter notebook](../software/tensorflow_on_jupyter_notebook.md)
 - Create and run your own TensorFlow container for HPC-DA (Power9) (todo: no link at all in old compendium)
 - [TensorFlow on x86](../software/deep_learning.md)
-- [PyTorch on HPC-DA (Power9)](../software/py_torch.md)
+- [PyTorch on HPC-DA (Power9)](../software/pytorch.md)
 - [Python on HPC-DA (Power9)](../software/python.md)
 - [JupyterHub](../access/jupyterhub.md)
 - [R on HPC-DA (Power9)](../software/data_analytics_with_r.md)

doc.zih.tu-dresden.de/docs/software/deep_learning.md

@@ -22,14 +22,14 @@ recommend using Ml partition [HPC-DA](../jobs_and_resources/hpcda.md). For examp
 module load TensorFlow
 ```
 
-There are numerous different possibilities on how to work with [TensorFlow](tensor_flow.md) on
+There are numerous different possibilities on how to work with [TensorFlow](tensorflow.md) on
 Taurus. On this page, for all examples default, scs5 partition is used. Generally, the easiest way
 is using the [modules system](modules.md)
 and Python virtual environment (test case). However, in some cases, you may need directly installed
 Tensorflow stable or night releases. For this purpose use the
-[EasyBuild](custom_easy_build_environment.md), [Containers](tensor_flow_container_on_hpcda.md) and see
+[EasyBuild](custom_easy_build_environment.md), [Containers](tensorflow_container_on_hpcda.md) and see
 [the example](https://www.tensorflow.org/install/pip). For examples of using TensorFlow for ml partition
-with module system see [TensorFlow page for HPC-DA](tensor_flow.md).
+with module system see [TensorFlow page for HPC-DA](tensorflow.md).
 
 Note: If you are going used manually installed Tensorflow release we recommend use only stable
 versions.
@@ -42,7 +42,7 @@ environments [ml environment and scs5 environment](modules.md#module-environment
 name "Keras".
 
 On this page for all examples default scs5 partition used. There are numerous different
-possibilities on how to work with [TensorFlow](tensor_flow.md) and Keras
+possibilities on how to work with [TensorFlow](tensorflow.md) and Keras
 on Taurus. Generally, the easiest way is using the [module system](modules.md) and Python
 virtual environment (test case) to see Tensorflow part above.
 For examples of using Keras for ml partition with the module system see the

doc.zih.tu-dresden.de/docs/software/get_started_with_hpcda.md

@@ -283,7 +283,7 @@ Several Tensorflow and PyTorch examples for the Jupyter notebook have been prepa
 simple tasks and models which will give you an understanding of how to work with ML frameworks and
 JupyterHub. It could be found as the [attachment] **todo** %ATTACHURL%/machine_learning_example.py
 in the bottom of the page. A detailed explanation and examples for TensorFlow can be found
-[here](tensor_flow_on_jupyter_notebook.md). For the Pytorch - [here](py_torch.md).  Usage information
+[here](tensorflow_on_jupyter_notebook.md). For the Pytorch - [here](pytorch.md).  Usage information
 about the environments for the JupyterHub could be found [here](../access/jupyterhub.md) in the chapter
 *Creating and using your own environment*.
 

doc.zih.tu-dresden.de/docs/software/keras.md

@@ -47,7 +47,7 @@ system.
 
 The information about the Jupyter notebook and the **JupyterHub** could
 be found [here](../access/jupyterhub.md). The use of
-Containers is described [here](tensor_flow_container_on_hpcda.md).
+Containers is described [here](tensorflow_container_on_hpcda.md).
 
 Keras contains numerous implementations of commonly used neural-network
 building blocks such as layers,
@@ -71,7 +71,7 @@ Keras (using the module system). To get started, import [tf.keras](https://www.t
 as part of your TensorFlow program setup.
 tf.keras is TensorFlow's implementation of the [Keras API
 specification](https://keras.io/). This is a modified example that we
-used for the [Tensorflow page](./tensor_flow.md).
+used for the [Tensorflow page](./tensorflow.md).
 
 ```bash
 srun -p ml --gres=gpu:1 -n 1 --pty --mem-per-cpu=8000 bash

doc.zih.tu-dresden.de/docs/software/tensor_flow.md → doc.zih.tu-dresden.de/docs/software/tensorflow.md

@@ -33,7 +33,7 @@ HPC-DA system.
 
 The information about the Jupyter notebook and the **JupyterHub** could
 be found [here](../access/jupyterhub.md). The use of
-Containers is described [here](tensor_flow_container_on_hpcda.md).
+Containers is described [here](tensorflow_container_on_hpcda.md).
 
 On Taurus, there exist different module environments, each containing a set
 of software modules. The default is *modenv/scs5* which is already loaded,

doc.zih.tu-dresden.de/mkdocs.yml

@@ -47,13 +47,13 @@ nav:
       - Data Analytics with R: software/data_analytics_with_r.md
       - Data Analytics with Python: software/python.md
       - TensorFlow: 
-        - TensorFlow Overview: software/tensor_flow.md
-        - TensorFlow in Container: software/tensor_flow_container_on_hpcda.md
-        - TensorFlow in JupyterHub: software/tensor_flow_on_jupyter_notebook.md 
+        - TensorFlow Overview: software/tensorflow.md
+        - TensorFlow in Container: software/tensorflow_container_on_hpcda.md
+        - TensorFlow in JupyterHub: software/tensorflow_on_jupyter_notebook.md 
       - Keras: software/keras.md
       - Dask: software/dask.md
       - Power AI: software/power_ai.md
-      - PyTorch: software/py_torch.md
+      - PyTorch: software/pytorch.md
       - Apache Spark, Apache Flink, Apache Hadoop: software/big_data_frameworks.md
     - SCS5 Migration Hints: software/scs5_software.md
     - Virtual Machines: software/virtual_machines.md