Repository for the Computational Intelligence Lab course project at ETH Zurich
Step 1: Clone the repository:
git clone https://github.com/AlessandroRuzzi/Computational-Intelligence-Lab-2021
Step 2: Copy new .env file and modify it by adding your environment variables:
cp .env.tmp .env
vim .env
Example of .env
file:
COMET_API_KEY=Your Key
COMET_WORKSPACE=alessandroruzzi
KAGGLE_USERNAME=alessandroruzzi
KAGGLE_KEY=Your kaggle Key
GOOGLE_MAPS_API_KEY= leave this blank
Step 3: Create virtual environment called venv
:
python -m venv venv
Step 4: Run the script to install modules, activate virtual environment, and install packages from requirements.txt
:
source ./leonhard_init.sh
Step 5: Open the file configs/config.yaml and insert your eth username at line 10.
Step 6: Train the model on experiment 14 without Google API:
bsub -W 24:00 -R "rusage[mem=64000, ngpus_excl_p=1]" -R "select[gpu_mtotal0>=10240]" python3 ./run.py +experiment=exp__f014
Step 7: Train the model on experiment 15 without Google API:
bsub -W 24:00 -R "rusage[mem=64000, ngpus_excl_p=1]" -R "select[gpu_mtotal0>=10240]" python3 ./run.py +experiment=exp__f015
Step 8: Add the Google API key in the .env file (you can find it in the CMT3 submission's comment)
COMET_API_KEY=Your Key
COMET_WORKSPACE=alessandroruzzi
KAGGLE_USERNAME=alessandroruzzi
KAGGLE_KEY=Your kaggle Key
GOOGLE_MAPS_API_KEY= PUT THE API KEY HERE
Step 9: Train the model on experiment 14:
bsub -W 24:00 -R "rusage[mem=64000, ngpus_excl_p=1]" -R "select[gpu_mtotal0>=10240]" python3 ./run.py +experiment=exp__f014
Step 10: Download the predictions from comet, you will find a file called submission.csv
in the comet section called Assets & Artifacts
, inside the folder others
.
Step 11: Combine the predictions with the run_ensemble.py script (replace file1, file2 and file3 with the actual CSV files' paths):
python3 ./run_ensemble.py file1,file2,file3
-
Clone repository into cluster.
-
Copy new .env file and modify it by adding your environment variables:
cp .env.tmp .env
vim .env
- Make
leonhard_init.sh
executable:
chmod +x leonhard_init.sh
- Create virtual environment called
venv
:
python -m venv venv
- Run
leonhard_init.sh
to install modules, activate virtual environment, and install packages fromrequirements.txt
:
./leonhard_init.sh
- Run model on a single GPU:
bsub -R "rusage[ngpus_excl_p=1]" ./run.py trainer.gpus=1
The following command will download a zipped prediction into your current local folder.
scp your_username@login.leonhard.ethz.ch:/Computational-Intelligence-Lab-2021/preds/DATE/preds.zip .