To run locally, make sure you have an NVIDA GPU in your machine.
- Create a conda environment for example:
conda create --name feddebug
- Activate environment:
conda activate feddebug
- Install necessary packages:
pip install pytorch-lightning
pip install diskcache
pip install dotmap
pip install jupyterlab
pip install torch torchvision torchaudio
pip install jupyterlab
- Clone
FedDebug
repository and switch to it.
git clone https://github.com/SEED-VT/FedDebug.git
cd FedDebug
Note: Make sure you are in project directory
~/FedDebug
.
- Run
jupyter-lab
command inFedDebug
directory. It will open the jupyter-notebook in the project directory.
-
Open
artifact.ipynb
-
Run second cell.
This should work without any errors.
Make sure you configure notebook with GPU: Click Edit->notebook settings->hardware accelerator->GPU
Copy & paste the following commands in the first cell of notebook (e.g., artifact.ipynb
) on Google Colab
.
!pip install pytorch-lightning
!pip install diskcache
!pip install dotmap
!pip install torch torchvision torchaudio
!git clone https://github.com/SEED-VT/FedDebug.git
# appending the path
import sys
sys.path.append("/content/FedDebug")
Now you can run the second cell of artifact.ipynb
. You can run notebooks containing FedDebug
code with the above instructions. Note: You can uncomment the commands instead of copy & pasting if above commands are already in the given notebook.