| #SBATCH --partition=h100 | |
| #SBATCH --gres=gpu:1 | |
| #SBATCH --cpus-per-task=24 | |
| #SBATCH --time=24:00:00 | |
| #SBATCH --job-name=no_TSDL_old_mixtures | |
| #SBATCH --output=no_TSDL_old_mixtures.%j.out | |
| echo "Hello from $(hostname)!" | |
| source "$(conda info --base)/etc/profile.d/conda.sh" | |
| conda activate semhear_emma2 | |
| echo "Job running on node: $(hostname)" | |
| echo "SLURM_JOB_ID=$SLURM_JOB_ID" | |
| srun --gres=gpu:1 bash -lc ' | |
| source "$(conda info --base)/etc/profile.d/conda.sh" | |
| conda activate semhear_emma2 | |
| which python | |
| python -V | |
| echo CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES | |
| python - <<PY | |
| import numpy as np | |
| import torch | |
| print("numpy", np.__version__) | |
| print("torch", torch.__version__) | |
| print("cuda avail", torch.cuda.is_available()) | |
| print("device count", torch.cuda.device_count()) | |
| PY | |
| python -m src.training.train experiments/no_TSDL_old_mixtures --use_cuda | |
| ' || echo "Command failed, keeping job alive for debugging..." | |