This file contains hidden or 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
#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
""" | |
Strips the pHYs chunk (resolution information) of a .png file. | |
Handy if pdflatex fails with "dimension too large" due to the | |
PNG resolution being set to 1. | |
For usage information, call without any parameters. |
This file contains hidden or 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
# -*- coding: utf-8 -*- | |
""" | |
Preliminary implementation of batch normalization for Lasagne. | |
Does not include a way to properly compute the normalization factors over the | |
full training set for testing, but can be used as a drop-in for training and | |
validation. | |
Author: Jan Schlüter | |
""" |
This file contains hidden or 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
#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
""" | |
Compares some algorithms for computing a sliding median of an array. | |
Results: | |
scipy.signal.medfilt2d is a bit faster than scipy.ndimage.filter.median_filter | |
and significantly faster than scipy.signal.medfilt. | |
Maintaining a sorted list of the window becomes faster than that for a filter |
This file contains hidden or 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
#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
""" | |
Demonstrates that cuDNN does not choose the fastest code path internally. | |
It first asks cuDNN to compute a particular full convolution as a forward | |
pass with sufficient zero padding of the input. | |
It then asks cuDNN to compute the same as a backward pass of a valid convolution | |
without zero padding of the input. |
NewerOlder