Merge pull request #2 from Fraunhofer-IMS/update_v1.0.1

Update v1.0.1

LICENSE

@@ -1,3 +1,18 @@
+This work is provided under the terms of GNU General Public 
+License Version 3 (see below). As a special exception, you may 
+create a larger work that contains
+part or all of the tinyHLS hardware compiler and distribute that 
+work under the terms of your choice, so long as that work is not 
+itself a hardware compiler or template-based code generator or a 
+modified version thereof. Alternatively, if you modify or re-
+distribute the hardware compiler itself, you may (at your option) 
+remove this special exception, which will cause the hardware compi-
+ler and the resulting output files to be licensed under the GNU 
+General Public License Version 3 without this special exception.
+
+
+
+
                     GNU GENERAL PUBLIC LICENSE
                        Version 3, 29 June 2007
 

README.md

@@ -29,8 +29,6 @@ The conv1D layer is configurable either as a resource-efficient or as performanc
 > Contributions and feedback are highly welcome!
 
 ## Quickstart 
-Detailed documentation is available as [HTML](https://fraunhofer-ims.github.io/tinyHLS/) and [PDF](https://github.com/Fraunhofer-IMS/tinyHLS/blob/main/docs/public/pdf/tinyHLS.pdf). 
-
 
 ### Conda Installation
 
@@ -40,7 +38,6 @@ To setup the environment and activate it, the following commands have to be run
 ```
 $ conda env create -f environment.yml
 $ conda activate tinyHLS
-$ pip install
 ```
 
 
@@ -63,14 +60,16 @@ tinyhls.translate_model()
 tinyhls.create_testbench()
 ```
 
-### Example
+### Examples
 
 An example of a small CNN is provided in the [`test.py`](test.py) file.
 This example is also executed by the project's [GitHub actions workflow](https://github.com/Fraunhofer-IMS/tinyHLS/actions).
 
 > [!TIP]
 > See the action's artifacts for tool logs and the generated HDL example.
 
+Further examples are provided under [examples/](https://github.com/Fraunhofer-IMS/tinyHLS/examples), which include the application on PPG and ECG biosignals using public datasets as well as a workaround to use this tool in combination with PyTorch. More details are provided in the userguide. 
+
 ### Simulation
 
 The generated Verilog code can be simulated using any open-source or commercial HDL simulator tools.
@@ -94,7 +93,7 @@ modified version thereof. Alternatively, if you modify or re-
 distribute the hardware compiler itself, you may (at your option) 
 remove this special exception, which will cause the hardware compi-
 ler and the resulting output files to be licensed under the GNU 
-General Public License without this special exception.
+General Public License Version 3 without this special exception.
 
 ```
 

docs/legal.adoc

@@ -39,5 +39,5 @@ modified version thereof. Alternatively, if you modify or re-
 distribute the hardware compiler itself, you may (at your option) 
 remove this special exception, which will cause the hardware compi-
 ler and the resulting output files to be licensed under the GNU 
-General Public License without this special exception.
+General Public License Version 3 without this special exception.
 ----

docs/ug/content.adoc

@@ -66,7 +66,6 @@ Clone the https://github.com/Fraunhofer-IMS/tinyHLS[tinyHLS] im Github on your c
 *Step 5*: Activate the virtual environment 
 
  $ conda activate tinyHLS
- $ pip install 
 
 
 === Use
@@ -184,8 +183,9 @@ About arguments:
 
 
 
-=== Test Example
+=== Examples 
 
+*Simple Test example*: 
 An example of a small convolutional neural network (CNN) is provided for test in the https://github.com/Fraunhofer-IMS/tinyHLS/test.py[test.py] file. It consists of nine cells that effectively showcase the capabilities of tinyHLS.
 
 . Import the necessary packages.
@@ -208,6 +208,17 @@ An example of a small convolutional neural network (CNN) is provided for test in
 
 . Generate the testbench for the convolutional neural network (CNN) model with ``tinyhls.create_testbench()``.
 
+*Biosignal (ECG) Example*: 
+To provide insights into how this can be used in a realistic application an open-source example is provided in the https://github.com/Fraunhofer-IMS/tinyHLS/examples/ecg_example.py[ecg_example.py] file. Please make sure that you tinyHLS conda environment is activated. Then simply execute ``python ecg_example.py`` in the ``examples`` folder.
+
+*PyTorch (PPG) Example*: 
+Though we recommend the use of TensorFlow Keras and depreciate the use of PyTorch, a PyTorch example was included in the https://github.com/Fraunhofer-IMS/tinyHLS/examples/ppg_example.py[ppg_example.py] file. Since other packages are required, it is neccessary to create a new environment using 
+
+ $ cd examples/
+ $ conda env create -f environment_torch.yml
+ $ conda activate tinyHLS_torch
+
+As usual, the example can then be executed with ``python ppg_example.py``. Please note that the wrapper function ``convert_model_to_json()`` simply exchanges the layer names from PyTorch to the TensorFlow Keras naming scheme. Hence, it is considered experimental and not part of tinyHLS yet. 
 
 === Requirements