changes related to mac venv scripts

Power-consumption-keras/bin/init_venv_macos.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+
+# Install virtualenv
+python3 -m pip install virtualenv
+
+# Init venv
+python3 -m virtualenv .power-consumption-keras
+
+# Pip deps
+.power-consumption-keras/bin/pip install --upgrade pip
+.power-consumption-keras/bin/pip install -r requirements-osx-m1.txt

Power-consumption-pytorch/bin/init_venv_macos.sh

@@ -0,0 +1,12 @@
+#!/bin/bash
+
+# Install virtualenv
+python3 -m pip install virtualenv
+
+# Init venv
+python3 -m virtualenv .power-consumption-pytorch
+
+# Pip deps
+.power-consumption-pytorch/bin/pip install --upgrade pip
+.power-consumption-pytorch/bin/pip install -e /home/ubuntu/fedn/fedn
+.power-consumption-pytorch/bin/pip install -r requirements-osx-m1.txt

Power-consumption-pytorch/requirements-osx-m1.txt

@@ -0,0 +1,4 @@
+torch==1.13.1
+torchvision==0.14.1
+fire==0.3.1
+docker==6.1.1

README.md

@@ -16,10 +16,14 @@ The example assumes working experience with Docker.
 
 ## Attach clients to an existing FEDn Network (for workshop)
 
-### Using Docker (not for M1, M2 macosx and Windows)
+Important: For the workshop, we will use PyTorch based compute-package. 
+
+### Using Docker (Linux and  MacOS)
 
 Here we assume that the FEDn network is up and running and you have obtained the connection file (client.yaml). In case you are participating in a Scaleout workshop, you will obtain the file from the workshop organizer. If you are working on the tutorial on your own, complete the instructions below before connecting the client.
 
+NOTE: In case you want to run a client on M1 or M2 macOS using TensorFlow and Keras, make sure you have a compatible framework version.
+
 Clone the repository
 
 ```