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Update 2011/dlowe + including colectomy on README

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Remove extraneous colons.

Format fixes in README.md.

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Fix file paths in README.md.

Add try.me.sh as there are a number of commands to run in the try
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Add to README.md note that the URL is dead and the Internet Wayback
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added to the bugs.md file.
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Cody Boone Ferguson committed 2023-04-15 05:20:47 -07:00
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2011/dlowe/README.md
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@@ -1,11 +1,10 @@
# Most self deprecating # Most self deprecating
David Lowe David Lowe
434 Tenney Drive 434 Tenney Drive
Rogue River, OR Rogue River, OR
97537 97537
<j.david.lowe@gmail.com> <j.david.lowe@gmail.com>
<http://www.pootpoot.net/>
## To build: ## To build:
@@ -40,19 +39,27 @@ Try these pre-trained networks:
./dlowe xor-1/01 < dlowe-aux-data/xor-trained.net ./dlowe xor-1/01 < dlowe-aux-data/xor-trained.net
./dlowe xor-1/10 < dlowe-aux-data/xor-trained.net ./dlowe xor-1/10 < dlowe-aux-data/xor-trained.net
./dlowe hint.html < dlowe-aux-data/english-trained.net ./dlowe README.md < dlowe-aux-data/english-trained.net
./dlowe dlowe-aux-data.tar.bz2 < dlowe-aux-data/png-trained.net ./dlowe dlowe-aux-data.tar.bz2 < dlowe-aux-data/png-trained.net
``` ```
You can run `./try.me.sh` to do the same thing.
NOTE: The `dlowe-aux-data.tar.bz2/` directory was created by: NOTE: The `dlowe-aux-data.tar.bz2/` directory was created by:
```sh ```sh
tar -jxf dlowe-aux-data.tar.bz2 tar -jxf dlowe-aux-data.tar.bz2
``` ```
## Judges' remarks: ## Judges' remarks:
NOTE: the author's website, http://www.pootpoot.net, no longer exists (as the
same) and the Internet Wayback Machine did not load scripts. Do you know if the
domain changed? Please provide us with the proper URL or if you know if it was
shut down for ever, please let us know that. Thank you!
This entry is a ghoulish example of a brain (dead?) neural network classifier. This entry is a ghoulish example of a brain (dead?) neural network classifier.
It comes with a set of corpora for you to try. It comes with a set of corpora for you to try.
@@ -61,7 +68,7 @@ It comes with a set of corpora for you to try.
You can create your own trained networks. For example, we trained a network You can create your own trained networks. For example, we trained a network
on the C code of entries that were supplied to the 20Th IOCCC. on the C code of entries that were supplied to the 20Th IOCCC.
The ioccc-winlose-trained.net was trained using the earlystop.pl tool: The ioccc-winlose-trained.net was trained using the [earlystop.pl](earlystop.pl) tool:
```sh ```sh
rm -f ioccc-winlose-trained.net rm -f ioccc-winlose-trained.net
@@ -70,101 +77,112 @@ rm -f ioccc-winlose-trained.net
where: where:
ioccc_won_training/ - `ioccc_won_training/`
1/2 of C code of the 20th IOCCC winners (except for dlowe.c from 2011) 1/2 of C code of the 20th IOCCC winners (except for dlowe.c from 2011)
plus 1/2 of the C code winners from prior IOCCC contests plus 1/2 of the C code winners from prior IOCCC contests
ioccc_won_test/ - `ioccc_won_test/`
1/2 of C code of the 20th IOCCC winners (except for dlowe.c from 2011) 1/2 of C code of the 20th IOCCC winners (except for dlowe.c from 2011)
plus 1/2 of the C code winners from prior IOCCC contests plus 1/2 of the C code winners from prior IOCCC contests
ioccc_lost_training/ - `ioccc_lost_training/`
1/2 of C code from entries that that did not win 1/2 of C code from entries that that did not win
ioccc_lost_test/ - `ioccc_lost_test/`
1/2 of C code from entries that that did not win 1/2 of C code from entries that that did not win
NOTE: The above directies were not shipped and the C code from NOTE: The above directories were not shipped and the C code from
entries that that did not win was flushed to /dev/null. entries that that did not win were flushed to /dev/null.
The earlystop.pl tool wrote: The [earlystop.pl](earlystop.pl) tool wrote:
training 1 to 1001... training 1 to 1001...
training 1001 to 2001... training 1001 to 2001...
prior error = 56.746974766043; current error = 58.095691135305 prior error = 56.746974766043; current error = 58.095691135305
The resulting ioccc-winlose-trained.net file was included in the The resulting ioccc-winlose-trained.net file was included in the
dlowe-aux-data.tar.bz2 file in the above mentioned URL. [dlowe-aux-data.tar.bz2](dlowe-aux-data.tar.bz2) tarball.
The dlowe.c was explicitly excluded from this trailing set. So this test is interesting: The [dlowe.c](dlowe.c) was explicitly excluded from this trailing set, so this
test is interesting:
```sh ```sh
./dlowe dlowe.c < ioccc-winlose-trained.net ./dlowe dlowe.c < dlowe-aux-data/ioccc-winlose-trained.net
``` ```
The match of dlowe.c to the lose/win trailed network was: The match of [dlowe.c](dlowe.c) to the lose/win trailed network was:
dlowe.c 0.125108 ```
dlowe.c 0.125108
```
NOTE: The non-artificially intelligent decisions of the IOCCC judges include random NOTE: The non-artificially intelligent decisions of the IOCCC judges include random
quirks and their non-linear judgment calls not found in the ioccc trained network. quirks and their non-linear judgment calls not found in the ioccc trained network.
Just because C code is or isn't scored highly by this network does not Just because C code is or isn't scored highly by this network does not
mean it will win or lose a future IOCCC. On the other hand ... it just might! mean it will win or lose a future IOCCC. On the other hand ... it just might!
#### other data sets to try #### other data sets to try
While we cannot supply you with the losing IOCCC source code, the author did supply a number While we cannot supply you with the losing IOCCC source code, the author did supply a number
data sets on which to test: data sets on which to test:
We created the english-trained.net as follows: We created the [english-trained.net](dlowe-aux-data/english-trained.net) as follows:
```sh ```sh
./dlowe -8000 english-1/ english-0/ < /dev/null > english-trained.net ./dlowe -8000 dlowe-aux-data/english-1/ dlowe-aux-data/english-0/ < /dev/null > dlowe-aux-data/english-trained.net
``` ```
english-0/ - [dlowe-aux-data/english-0/](dlowe-aux-data/english-0/)
Non-English (French) text Non-English (French) text
english-1/
English (non-French) text
We created the png-trained.net as follows: - [dlowe-aux-data/english-1/](dlowe-aux-data/english-1)
English (non-French) text
We created the [png-trained.net](dlowe-aux-data/png-trained.net) as follows:
```sh ```sh
./dlowe -8000 png-1/ png-0/ < /dev/null > png-trained.net ./dlowe -8000 png-1/ png-0/ < /dev/null > dlowe-aux-data/png-trained.net
``` ```
png-0/ - [dlowe-aux-data/png-0/](dlowe-aux-data/png-0/)
Non-png (gif) images Non-png (gif) images
png-1/
- [dlowe-aux-data/png-1/](dlowe-aux-data/png-1/)
png (non-gif) images png (non-gif) images
We created the xor-trained.net as follows: We created the [xor-trained.net](dlowe-aux-data/xor-trained.net) as follows:
```sh ```sh
./dlowe -8000 xor-1/ xor-0/ < /dev/null > xor-trained.net ./dlowe -8000 dlowe-aux-data/xor-1/ dlowe-aux-data/xor-0/ < /dev/null > dlowe-aux-data/xor-trained.net
``` ```
xor-0/ - [dlowe-aux-data/xor-0](dlowe-aux-data/xor-0/)
Data that XORs to 0 Data that XORs to 0
xor-1/
- [dlowe-aux-data/xor-1/](dlowe-aux-data/xor-1/)
Data that XORs to 1 Data that XORs to 1
**NOTE**: The directory args **must end in a /** for them to work.
## Author's remarks: ## Author's remarks:
### Synopsis: ### Synopsis
This is an artificially intelligent judging tool to help the IOCCC judges. This is an artificially intelligent judging tool to help the IOCCC judges.
Here's to shorter, more frequent contests! Here's to shorter, more frequent contests!
### Description: ### Description
This is a multilayer perceptron (a feedforward artificial neural network) This is a multilayer [perceptron](https://en.wikipedia.org/wiki/Perceptron) (a
which can be trained, using on-line backpropagation, to classify input files. [feedforward artificial neural
network](https://en.wikipedia.org/wiki/Feedforward_neural_network))
which can be trained, using on-line
[backpropagation](https://en.wikipedia.org/wiki/Backpropagation), to classify input files.
It has a fixed topology of 2^16 input neurons, 6 hidden neurons and 1 output It has a fixed topology of `2^16` input neurons, 6 hidden neurons and 1 output
neuron. neuron.
The neurons' activation function is the logistic function 1 / (1 + e ^ -x). The neurons' activation function is the logistic function `1 / (1 + e ^ -x)`.
### Classifying ### Classifying
@@ -188,7 +206,7 @@ trained, but it's geared toward interpretation as a *probability* or a
./dlowe -<n_iterations> corpus1/ [...] corpus0/ < start.net > end.net ./dlowe -<n_iterations> corpus1/ [...] corpus0/ < start.net > end.net
``` ```
NOTE: The directory args must end in a / for them to work. **NOTE**: The directory args **must end in a /** for them to work.
To train a network, one specifies a starting network (on stdin), two or more To train a network, one specifies a starting network (on stdin), two or more
corpora (directories containing training data), and the number of training corpora (directories containing training data), and the number of training
@@ -214,15 +232,15 @@ https://images.google.com search for "obfuscate filetype:gif".
Results: Results:
* using these corpora as a training set * using these corpora as a training set.
* using several hundred random *.gif and *.png files from my home computer as * using several hundred random `*.gif` and `*.png` files from my home computer as
a test set a test set
* using the included "earlystop.pl" script, which stopped after 67000 iterations. * using the included [earlystop.pl](earlystop.pl) script, which stopped after 67000 iterations.
* interpreting output of "> 0.5" as "probably a .png" and "< 0.5" as "probably * interpreting output of `> 0.5` as "probably a .png" and `< 0.5` as "probably
a .gif" a .gif"
* produced a network with about 87% accuracy * produced a network with about 87% accuracy
#### english corpora #### English corpora
The english-1 corpus was obtained by manually scraping the first results from The english-1 corpus was obtained by manually scraping the first results from
a https://www.google.com/webhp?lr=lang_en search for "paris filetype:txt". a https://www.google.com/webhp?lr=lang_en search for "paris filetype:txt".
@@ -230,16 +248,16 @@ a https://www.google.com/webhp?lr=lang_en search for "paris filetype:txt".
The english-0 corpus was obtained by manually scraping the first results from The english-0 corpus was obtained by manually scraping the first results from
a https://www.google.com/webhp?lr=lang_fr search for "paris filetype:txt". a https://www.google.com/webhp?lr=lang_fr search for "paris filetype:txt".
Results: ##### Results:
* using these corpora as a training set * using these corpora as a training set.
* using several dozen additional text files (obtained by the same methods) * using several dozen additional text files (obtained by the same methods)
as a test set as a test set.
* using the included "earlystop.pl" script, which stopped after 10000 * using the included [earlystop.pl](earlystop.pl) script, which stopped after 10000
iterations. iterations.
* interpreting output of "> 0.5" as "probably english" and "< 0.5" as * interpreting output of `> 0.5` as "probably English" and `< 0.5` as
"probably french" "probably French"
* produced a network with 100% accuracy * produced a network with 100% accuracy
#### xor corpora #### xor corpora
@@ -247,15 +265,15 @@ The xor-1 corpus consists of two files containing '01' and '10' respectively.
The xor-0 corpus consists of two files containing '00' and '11' respectively. The xor-0 corpus consists of two files containing '00' and '11' respectively.
Results: ##### Results:
* using these corpora as a training set * using these corpora as a training set.
* takes about 8000 iterations to learn xor to within a tolerance of <0.01 * takes about 8000 iterations to learn xor to within a tolerance of `<0.01`.
### Limitations ### Limitations
The program can't tell you anything meaningful about files with less than two The program can't tell you anything meaningful about files with less than two
bytes in them (I'm looking at you, smr.c!) bytes in them (I'm looking at you, [smr.c](/1994/smr/smr.c)!)
You must include the trailing directory separator on training directories You must include the trailing directory separator on training directories
(this allows the program to be portable without wasting precious bytes on (this allows the program to be portable without wasting precious bytes on
@@ -265,7 +283,7 @@ Serialized network files are only portable between systems with the same
floating-point representation and endianness. floating-point representation and endianness.
Making sure not to overfit the network to the training data is a bit of a Making sure not to overfit the network to the training data is a bit of a
black art. I have enclosed 'earlystop.pl', a wrapper script that implements black art. I have enclosed [earlystop.pl](earlystop.pl), a wrapper script that implements
a simple 'early stopping' algorithm; other techniques are possible. a simple 'early stopping' algorithm; other techniques are possible.
Bad input (e.g. nonexistent files, non-numeric number of iterations, etc.) Bad input (e.g. nonexistent files, non-numeric number of iterations, etc.)
@@ -284,24 +302,18 @@ library (untested, but they do exist).
Backpropagation doesn't always converge: if you play with this long enough, Backpropagation doesn't always converge: if you play with this long enough,
you'll eventually have a training session that completely fails to converge. you'll eventually have a training session that completely fails to converge.
### Obfuscation: ### Obfuscation
Zombies! (Since neural networks are modeled after BRAINS, ya know? And - Zombies! (Since neural networks are modeled after BRAINS, ya know? And
corpus sounds a lot like corpse. And I have 4- and 7-year-old kids ;) corpus sounds a lot like corpse. And I have 4- and 7-year-old kids ;) )
- Neural networks are interesting, and while the math isn't terribly difficult,
Neural networks are interesting, and while the math isn't terribly difficult,
their behavior is difficult to fully understand. their behavior is difficult to fully understand.
- Had some extra space in one of the major data structures, and it seemed a
Had some extra space in one of the major data structures, and it seemed a
shame to waste it. shame to waste it.
- Similarly, I think three file pointers ought to be enough for anyone.
Similarly, I think three file pointers ought to be enough for anyone. - Lots of magic numbers expressed in various ways.
- Random abuse of random C trivia.
Lots of magic numbers expressed in various ways. - Some textual changes were made to maximize the classification of this program
Random abuse of random C trivia.
Some textual changes were made to maximize the classification of this program
by a network trained to recognize ioccc winners ;) by a network trained to recognize ioccc winners ;)
... but mostly zombies! ... but mostly zombies!
2011/dlowe/try.me.sh
Executable
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#!/usr/bin/env bash
make clobber dlowe || exit 1
./dlowe dlowe.c < dlowe-aux-data/ioccc-winlose-trained.net
./dlowe dlowe < dlowe-aux-data/ioccc-winlose-trained.net
./dlowe xor-0/00 < dlowe-aux-data/xor-trained.net
./dlowe xor-0/11 < dlowe-aux-data/xor-trained.net
./dlowe xor-1/01 < dlowe-aux-data/xor-trained.net
./dlowe xor-1/10 < dlowe-aux-data/xor-trained.net
./dlowe README.html < dlowe-aux-data/english-trained.net
./dlowe dlowe-aux-data.tar.bz2 < dlowe-aux-data/png-trained.net
bugs.md
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@@ -1123,6 +1123,13 @@ These years did not have an IOCCC.
# 2011 # 2011
## [2011/dlowe](2011/dlowe/dlowe.c) ([README.md](2011/dlowe/README.md))
## STATUS: missing or dead link - please provide them
The author's website, http://www.pootpoot.net, no longer exists as it once did,
instead being something else entirely. The Internet Wayback Machine, although it
archived it, did not load scripts. Do you know if the domain was moved? Do you
have an archive or mirror? Please provide us it! Thank you.
# 2012 # 2012