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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 | |