Hi Denis,
as promised, I pushed enclog 0.5.2-SNAPSHOT to clojars 5 minutes ago and
updated the demo examples on github to show the new code style. tested
all the examples and everything works just fine...if you find anything
unusual feel free to poke me :-)
aaa btw 0.5.2 has nice documentation as well (well, nicer anyway) and
also fixed a small bug with SVM/PNN initialisation. you shouldn't have
any problems copy-pasting the examples now even if you're :using the
entire 'networks' namespace...it is better to :require it though so you
can choose your own names.
hope that helps...
Jim
On 08/09/12 13:00, Jim - FooBar(); wrote:
Hi Denis,
you cannot bring 2 vars named 'network' in the same namespace...It is
partly my fault cos since I changed 'make-network' to 'network' I
should have changed the examples as well...try again but instead of
'network' define your neural-net as 'net' or something cos there is
alaredy a 'network' multi-fn...in any case, I'm assuming you're just
fooling around with enclog...if this is the case, keep in mind that i
will push 0.5.2 later this afternoon which includes some
changes...I'll try fix the examples as well...
thanks for trying out enclog and for reporting what you thought was a
bug...
Jim
On 08/09/12 10:12, Denis Labaye wrote:
On Tue, Sep 4, 2012 at 9:05 PM, Jim - FooBar(); <jimpil1...@gmail.com
<mailto:jimpil1...@gmail.com>> wrote:
Hi all,
just wanted to let you know that I renamed 'clojure-encog' to
*enclog* ...release 0.5.0 does not add anything but several
'library coding standards' that i was previously not aware of,
have been addressed...
I created a brand new repo here :
https://github.com/jimpil/enclog
and a new jar here:
https://clojars.org/enclog <https://clojars.org/clojure-encog>
I also added a simple example of KMeans clustering and soon I
will have the famous TSP problem solved...
cheers,
Jim
Seems cool
But when I tried to run the example:
(let[xor-input [[0.0 0.0] [1.0 0.0] [0.0 0.1] [1.0 1.0]]
xor-ideal [[0.0] [1.0] [1.0] [0.0]]
dataset (data :basic-dataset xor-input xor-ideal)
trainer ((trainer :back-prop) network dataset)])
I got :
clojure.lang.MultiFn cannot be cast to
org.encog.neural.networks.ContainsFlat
[Thrown class java.lang.ClassCastException]
Restarts:
0: [QUIT] Quit to the SLIME top level
Backtrace:
0: training.clj:156 enclog.training/trainer[fn]
1: NO_SOURCE_FILE:1 clojure-station.lib-example.enclog/fn
2: AFn.java:159 clojure.lang.AFn.applyToHelper
3: AFn.java:151 clojure.lang.AFn.applyTo
4: Compiler.java:3382 clojure.lang.Compiler$InvokeExpr.eval
5: Compiler.java:398 clojure.lang.Compiler$DefExpr.eval
6: Compiler.java:6516 clojure.lang.Compiler.eval
7: Compiler.java:6477 clojure.lang.Compiler.eval
8: core.clj:2797 clojure.core/eval
9: core.clj:532 swank.core/eval786[fn]
10: MultiFn.java:163 clojure.lang.MultiFn.invoke
11: basic.clj:54 swank.commands.basic/eval-region
12: basic.clj:44 swank.commands.basic/eval-region
13: basic.clj:78 swank.commands.basic/eval1061[fn]
14: Var.java:415 clojure.lang.Var.invoke
15: (Unknown Source) clojure-station.lib-example.enclog/eval7620
16: Compiler.java:6511 clojure.lang.Compiler.eval
17: Compiler.java:6477 clojure.lang.Compiler.eval
18: core.clj:2797 clojure.core/eval
19: core.clj:100 swank.core/eval-in-emacs-package
20: core.clj:256 swank.core/eval-for-emacs
21: Var.java:423 clojure.lang.Var.invoke
22: AFn.java:167 clojure.lang.AFn.applyToHelper
23: Var.java:532 clojure.lang.Var.applyTo
24: core.clj:601 clojure.core/apply
25: core.clj:107 swank.core/eval-from-control
26: core.clj:112 swank.core/eval-loop
27: core.clj:341 swank.core/spawn-repl-thread[fn]
28: AFn.java:159 clojure.lang.AFn.applyToHelper
29: AFn.java:151 clojure.lang.AFn.applyTo
30: core.clj:601 clojure.core/apply
31: core.clj:338 swank.core/spawn-repl-thread[fn]
32: RestFn.java:397 clojure.lang.RestFn.invoke
33: AFn.java:24 clojure.lang.AFn.run
34: Thread.java:662 java.lang.Thread.run
(I am on clojure 1.4.0)
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