Skip to content

A technical report on convolution arithmetic in the context of deep learning

License

Notifications You must be signed in to change notification settings

lizhangscience/conv_arithmetic

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Convolution arithmetic

A technical report on convolution arithmetic in the context of deep learning.

The code and/or the images of this tutorial are free to use for non-commercial purposes with proper attribution:

Convolution animations

N.B.: Blue maps are inputs, and cyan maps are outputs.

No padding, no strides Arbitrary padding, no strides Half padding, no strides Full padding, no strides
No padding, strides Padding, strides Padding, strides (odd)

Transposed convolution animations

N.B.: Blue maps are inputs, and cyan maps are outputs.

No padding, no strides, transposed Arbitrary padding, no strides, transposed Half padding, no strides, transposed Full padding, no strides, transposed
No padding, strides, transposed Padding, strides, transposed Padding, strides, transposed (odd)

Dilated convolution animations

N.B.: Blue maps are inputs, and cyan maps are outputs.

No padding, no stride, dilation

Generating the Makefile

From the repository's root directory:

$ ./bin/generate_makefile

Generating the animations

From the repository's root directory:

$ make all_animations

The animations will be output to the gif directory. Individual animation steps will be output in PDF format to the pdf directory and in PNG format to the png directory.

Compiling the document

From the repository's root directory:

$ make

About

A technical report on convolution arithmetic in the context of deep learning

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • TeX 79.7%
  • Python 20.3%