Lua-Fann ERROR: attempt to call field 'create_standard' (a nil value)

[Linsque]

Hey, I'm trying to run the example from the repository (https://github.com/msva/lua-fann/tree/master/test) but i'm having some issues.

Running module.lua i'm receiving the error attempt to call field 'create_standard' (a nil value).

I'm using Lua 5.1.5 and the most recent ZeroBrane. I downloaded the lua-fann module with LuaRocks 3.9.1 and, for install lua-fann, I installed fann library 2.2.0 from the developers website.

And even switch to another IDE wasn't a solution for me... seems that the module isn't loading right.

StackOverflow: https://stackoverflow.com/questions/73169113/lua-fann-error-in-zerobrane-attempt-to-call-field-create-standard-a-nil-valu

[msva]

It seems, you have either installed lua-module (lua-fann) or libfan incorrectly. Or both.

I've just even tried with currenf FANN's git HEAD, and all works fine 🤷

$  lua module.lua
Max epochs   500000. Desired error: 0.0010000000.
Epochs            1. Current error: 0.3085455298. Bit fail 4.
Epochs           27. Current error: 0.0000248633. Bit fail 0.
MSE: 7.2449183790013e-05
Layer / Neuron 012345
L   1 / N    3 CCC...
L   1 / N    4 ddD...
L   1 / N    5 ......
L   2 / N    6 ...EDd
L   2 / N    7 ......
Input layer                          :   2 neurons, 1 bias
  Hidden layer                       :   2 neurons, 1 bias
Output layer                         :   1 neurons
Total neurons and biases             :   7
Total connections                    :   9
Connection rate                      :   1.000
Network type                         :   FANN_NETTYPE_LAYER
Training algorithm                   :   FANN_TRAIN_RPROP
Training error function              :   FANN_ERRORFUNC_TANH
Training stop function               :   FANN_STOPFUNC_BIT
Bit fail limit                       :   0.010
Learning rate                        :   0.700
Learning momentum                    :   0.000
Quickprop decay                      :  -0.000100
Quickprop mu                         :   1.750
RPROP increase factor                :   1.200
RPROP decrease factor                :   0.500
RPROP delta min                      :   0.000
RPROP delta max                      :  50.000
Cascade output change fraction       :   0.010000
Cascade candidate change fraction    :   0.010000
Cascade output stagnation epochs     :  12
Cascade candidate stagnation epochs  :  12
Cascade max output epochs            : 150
Cascade min output epochs            :  50
Cascade max candidate epochs         : 150
Cascade min candidate epochs         :  50
Cascade weight multiplier            :   0.400
Cascade candidate limit              :1000.000
Cascade activation functions[0]      :   FANN_SIGMOID
Cascade activation functions[1]      :   FANN_SIGMOID_SYMMETRIC
Cascade activation functions[2]      :   FANN_GAUSSIAN
Cascade activation functions[3]      :   FANN_GAUSSIAN_SYMMETRIC
Cascade activation functions[4]      :   FANN_ELLIOT
Cascade activation functions[5]      :   FANN_ELLIOT_SYMMETRIC
Cascade activation functions[6]      :   FANN_SIN_SYMMETRIC
Cascade activation functions[7]      :   FANN_COS_SYMMETRIC
Cascade activation functions[8]      :   FANN_SIN
Cascade activation functions[9]      :   FANN_COS
Cascade activation steepnesses[0]    :   0.250
Cascade activation steepnesses[1]    :   0.500
Cascade activation steepnesses[2]    :   0.750
Cascade activation steepnesses[3]    :   1.000
Cascade candidate groups             :   2
Cascade no. of candidates            :  80
Result: -0.96608966588974
Result: 0.99814438819885
Result: -0.9986754655838
Result: 0.99798047542572
Test data read: [[FANN training data]]
MSE on test data: 7.0389745815191e-05