Merge pull request #5 from scaleoutsystems/feature/compute-package

Manual virutal env

README.md

@@ -148,5 +148,5 @@ In this tutorial, you have learned how to implement Ultralytics YOLOv8 models in
 # Note
 Steps 1, 2, 5, 6, 7 and 8 only need to be done once to set up the federated learning environment in FEDn.
 
-To connect a new client, the only steps that needs to be followed are step 3, 4 and 9.
-Each client can have different configurations in the client_config.yaml file. This file needs to be downloaded from the repository separately for each client.
+To connect a new client, the only steps that needs to be followed are step 2, 3, 4 and 9.
+Each client can have different configurations in the client_config.yaml file to account for different hardware and training requirements.

client/fedn.yaml

@@ -1,11 +1,9 @@
-python_env: python_env.yaml
-
 entry_points:
     build:
-        command: python model.py
+        command: python3 model.py
     startup:
-        command: python data.py
+        command: python3 data.py
     train:
-        command: python train.py
+        command: python3 train.py
     validate:
-        command: python validate.py
+        command: python3 validate.py

requirements.txt

@@ -1,2 +1,3 @@
 fedn==0.16.0
 ultralytics==8.2.91
+torch==2.4.1