Update 2011/dlowe + including colectomy on README
Remove extraneous colons. Format fixes in README.md. Add links to README.md. Fix file paths in README.md. Add try.me.sh as there are a number of commands to run in the try section. Add to README.md note that the URL is dead and the Internet Wayback Machine archived it but it did not archive the scripts. This was also added to the bugs.md file.
This commit is contained in:
Cody Boone Ferguson committed
1 parent
39fbcd536f
commit
afff0496aa
3 files changed
+123
-87
No files matched your search
+99
-87
@@ -1,11 +1,10 @@
|
||||
# Most self deprecating
|
||||
|
||||
David Lowe
|
||||
434 Tenney Drive
|
||||
Rogue River, OR
|
||||
97537
|
||||
<j.david.lowe@gmail.com>
|
||||
<http://www.pootpoot.net/>
|
||||
David Lowe
|
||||
434 Tenney Drive
|
||||
Rogue River, OR
|
||||
97537
|
||||
<j.david.lowe@gmail.com>
|
||||
|
||||
## To build:
|
||||
|
||||
@@ -40,19 +39,27 @@ Try these pre-trained networks:
|
||||
./dlowe xor-1/01 < 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
|
||||
```
|
||||
|
||||
You can run `./try.me.sh` to do the same thing.
|
||||
|
||||
NOTE: The `dlowe-aux-data.tar.bz2/` directory was created by:
|
||||
|
||||
|
||||
```sh
|
||||
tar -jxf dlowe-aux-data.tar.bz2
|
||||
```
|
||||
|
||||
## 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.
|
||||
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
|
||||
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
|
||||
rm -f ioccc-winlose-trained.net
|
||||
@@ -70,101 +77,112 @@ rm -f ioccc-winlose-trained.net
|
||||
|
||||
where:
|
||||
|
||||
ioccc_won_training/
|
||||
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
|
||||
- `ioccc_won_training/`
|
||||
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
|
||||
|
||||
ioccc_won_test/
|
||||
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
|
||||
- `ioccc_won_test/`
|
||||
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
|
||||
|
||||
ioccc_lost_training/
|
||||
1/2 of C code from entries that that did not win
|
||||
- `ioccc_lost_training/`
|
||||
1/2 of C code from entries that that did not win
|
||||
|
||||
ioccc_lost_test/
|
||||
1/2 of C code from entries that that did not win
|
||||
- `ioccc_lost_test/`
|
||||
1/2 of C code from entries that that did not win
|
||||
|
||||
NOTE: The above directies were not shipped and the C code from
|
||||
entries that that did not win was flushed to /dev/null.
|
||||
NOTE: The above directories were not shipped and the C code from
|
||||
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 1001 to 2001...
|
||||
prior error = 56.746974766043; current error = 58.095691135305
|
||||
|
||||
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
|
||||
./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
|
||||
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
|
||||
mean it will win or lose a future IOCCC. On the other hand ... it just might!
|
||||
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
|
||||
mean it will win or lose a future IOCCC. On the other hand ... it just might!
|
||||
|
||||
#### other data sets to try
|
||||
|
||||
While we cannot supply you with the losing IOCCC source code, the author did supply a number
|
||||
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
|
||||
./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/
|
||||
Non-English (French) text
|
||||
english-1/
|
||||
English (non-French) text
|
||||
- [dlowe-aux-data/english-0/](dlowe-aux-data/english-0/)
|
||||
Non-English (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
|
||||
./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
|
||||
png-1/
|
||||
|
||||
- [dlowe-aux-data/png-1/](dlowe-aux-data/png-1/)
|
||||
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
|
||||
./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
|
||||
xor-1/
|
||||
|
||||
- [dlowe-aux-data/xor-1/](dlowe-aux-data/xor-1/)
|
||||
Data that XORs to 1
|
||||
|
||||
**NOTE**: The directory args **must end in a /** for them to work.
|
||||
|
||||
## Author's remarks:
|
||||
|
||||
### Synopsis:
|
||||
### Synopsis
|
||||
|
||||
This is an artificially intelligent judging tool to help the IOCCC judges.
|
||||
Here's to shorter, more frequent contests!
|
||||
|
||||
### Description:
|
||||
### Description
|
||||
|
||||
This is a multilayer perceptron (a feedforward artificial neural network)
|
||||
which can be trained, using on-line backpropagation, to classify input files.
|
||||
This is a multilayer [perceptron](https://en.wikipedia.org/wiki/Perceptron) (a
|
||||
[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.
|
||||
|
||||
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
|
||||
|
||||
@@ -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
|
||||
```
|
||||
|
||||
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
|
||||
corpora (directories containing training data), and the number of training
|
||||
@@ -214,15 +232,15 @@ https://images.google.com search for "obfuscate filetype:gif".
|
||||
|
||||
Results:
|
||||
|
||||
* using these corpora as a training set
|
||||
* using several hundred random *.gif and *.png files from my home computer as
|
||||
a test set
|
||||
* using the included "earlystop.pl" script, which stopped after 67000 iterations.
|
||||
* interpreting output of "> 0.5" as "probably a .png" and "< 0.5" as "probably
|
||||
a .gif"
|
||||
* produced a network with about 87% accuracy
|
||||
* using these corpora as a training set.
|
||||
* using several hundred random `*.gif` and `*.png` files from my home computer as
|
||||
a test set
|
||||
* 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
|
||||
a .gif"
|
||||
* produced a network with about 87% accuracy
|
||||
|
||||
#### english corpora
|
||||
#### English corpora
|
||||
|
||||
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".
|
||||
@@ -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
|
||||
a https://www.google.com/webhp?lr=lang_fr search for "paris filetype:txt".
|
||||
|
||||
Results:
|
||||
##### Results:
|
||||
|
||||
* using these corpora as a training set
|
||||
* using several dozen additional text files (obtained by the same methods)
|
||||
as a test set
|
||||
* using the included "earlystop.pl" script, which stopped after 10000
|
||||
iterations.
|
||||
* interpreting output of "> 0.5" as "probably english" and "< 0.5" as
|
||||
"probably french"
|
||||
* produced a network with 100% accuracy
|
||||
* using these corpora as a training set.
|
||||
* using several dozen additional text files (obtained by the same methods)
|
||||
as a test set.
|
||||
* using the included [earlystop.pl](earlystop.pl) script, which stopped after 10000
|
||||
iterations.
|
||||
* interpreting output of `> 0.5` as "probably English" and `< 0.5` as
|
||||
"probably French"
|
||||
* produced a network with 100% accuracy
|
||||
|
||||
#### 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.
|
||||
|
||||
Results:
|
||||
##### Results:
|
||||
|
||||
* using these corpora as a training set
|
||||
* takes about 8000 iterations to learn xor to within a tolerance of <0.01
|
||||
* using these corpora as a training set.
|
||||
* takes about 8000 iterations to learn xor to within a tolerance of `<0.01`.
|
||||
|
||||
### Limitations
|
||||
|
||||
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
|
||||
(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.
|
||||
|
||||
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.
|
||||
|
||||
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,
|
||||
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
|
||||
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,
|
||||
- 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 ;) )
|
||||
- Neural networks are interesting, and while the math isn't terribly difficult,
|
||||
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.
|
||||
|
||||
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.
|
||||
|
||||
Some textual changes were made to maximize the classification of this program
|
||||
- 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.
|
||||
- Some textual changes were made to maximize the classification of this program
|
||||
by a network trained to recognize ioccc winners ;)
|
||||
|
||||
... but mostly zombies!
|
||||
|
||||
Executable
+17
@@ -0,0 +1,17 @@
|
||||
#!/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
|
||||
|
||||
|
||||
@@ -1123,6 +1123,13 @@ These years did not have an IOCCC.
|
||||
|
||||
# 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
|
||||
|
||||
|
||||
Reference in new issue
Block a user