This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
%===================================================================== | |
% jhwhw.cls | |
% Provide jhwhw.cls class | |
%===================================================================== | |
%===================================================================== | |
% Identification | |
%===================================================================== | |
\NeedsTeXFormat{LaTeX2e} | |
\ProvidesClass{jhwhw}[2009/02/11 Justin Wilson's Homework Class] |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import matplotlib.pyplot as plt | |
import keras.backend as K | |
from keras.callbacks import Callback | |
class LRFinder(Callback): | |
''' | |
A simple callback for finding the optimal learning rate range for your model + dataset. | |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
from keras.callbacks import Callback | |
import keras.backend as K | |
import numpy as np | |
class SGDRScheduler(Callback): | |
'''Cosine annealing learning rate scheduler with periodic restarts. | |
# Usage | |
```python | |
schedule = SGDRScheduler(min_lr=1e-5, |