Giux22/semana1-bw-1

class TrainingConfig: image_size = 128 # the generated image resolution train_batch_size = 16 eval_batch_size = 16 # how many images to sample during evaluation num_epochs = 10000 gradient_accumulation_steps = 1 learning_rate = 1e-4 lr_warmup_steps = 500 save_image_epochs = 50 save_model_epochs = 50 mixed_precision = "fp16" # no for float32, fp16 for automatic mixed precision output_dir = "semana1-bw-1" # the model name locally and on the HF Hub

push_to_hub = True  # whether to upload the saved model to the HF Hub
hub_private_repo = False
overwrite_output_dir = True  # overwrite the old model when re-running the notebook
seed = 22

preprocess = transforms.Compose( [ transforms.Resize((config.image_size, config.image_size)), transforms.Grayscale(), # transforms.RandomHorizontalFlip(), transforms.RandomRotation(4), transforms.ToTensor(), transforms.Normalize([0.5], [0.5]), ] )