Virtual Lab: Wasserstein GAN with Gradient Penalty

root@phd-gpu-cluster:~# python run_wasserstein_gan_with_gradient_penalty_experiment.py --use_cuda=True [INFO] Initializing distributed training environment... [INFO] Loading PhD-level module: Wasserstein GAN with Gradient Penalty [METRIC] CUDA Memory Allocated: 17 GB [METRIC] TFLOPS Achieved: 77.4 [SUCCESS] Model converged successfully. Gradients stable.