| from datetime import datetime | |
| import matplotlib.pyplot as plt | |
| import torch | |
| def freeze_module(module): | |
| for param in module.parameters(): | |
| param.requires_grad = False | |
| def get_device(): | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| if torch.backends.mps.is_available() and torch.backends.mps.is_built(): | |
| device = "mps" | |
| if device == "mps": | |
| print( | |
| "WARNING: MPS currently doesn't seem to work, and messes up backpropagation without any visible torch" | |
| " errors. I recommend using CUDA on a colab notebook or CPU instead if you're facing inexplicable issues" | |
| " with generations." | |
| ) | |
| return device | |
| def show_pil(img): | |
| fig = plt.imshow(img) | |
| fig.axes.get_xaxis().set_visible(False) | |
| fig.axes.get_yaxis().set_visible(False) | |
| plt.show() | |
| def get_timestamp(): | |
| current_time = datetime.now() | |
| timestamp = current_time.strftime("%H:%M:%S") | |
| return timestamp | |