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| class Arithmetic(GrammarDataSet): | |
| open_par = '(' | |
| close_par = ')' | |
| def __init__(self, maxnest=4, maxlength=50, size=250, | |
| vars=None, operators=None): | |
| """Initialize an Arithmetic objective with a nesting depth of at most | |
| maxnest, words up to a size of length and size items in the training and | |
| test datasets. |
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| double* derivs_p = get_derivatives(); | |
| for (int i = 0; i < outdim; i++) | |
| { | |
| for (int j = 0; j < indim; j++) | |
| { | |
| derivs_p[i * indim + j] += source_p[i] * input_p[j]; | |
| } | |
| } |
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| import pylab | |
| import scipy | |
| pylab.clf() | |
| pylab.imshow(scipy.eye(100, 100)) | |
| pylab.Rectangle((10, 10), 20, 20, fill=True) | |
| pylab.show() |
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| import pylab | |
| import scipy | |
| pylab.clf() | |
| pylab.imshow(scipy.eye(100, 100)) | |
| pylab.Rectangle((10, 10), 20, 20, fill=True) | |
| pylab.show() |
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| def plot_prediction(result, sample, target, filename=None): | |
| sample.shape = 512, 512 | |
| fig = pylab.figure() | |
| plot = fig.add_subplot(111) | |
| pylab.imshow(sample, cmap=pylab.cm.gray) | |
| denormalize = lambda x, rng: (x + 1.) * rng / 2 | |
| def getcoords(normalized): |
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| #include <vector> | |
| int main(int argc, char **argv) | |
| { | |
| std::vector<const double*> blubber; | |
| blubber.push_back(0); | |
| blubber.push_back(0); | |
| blubber.push_back(0); | |
| blubber.push_back(0); | |
| std::vector<const double*>::const_reverse_iterator output_iter; |
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| # -*- coding: utf-8 -*- | |
| """This module is an evolino implementation alternative to the current | |
| PyBrain one.""" | |
| __author__ = 'Justin S Bayer, [email protected]' | |
| import scipy as sp |
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| {'coords': False} | |
| input filename inputs-bam.txt | |
| data filename bla.nc | |
| reading 1 data files | |
| Sample file: 0-sample.arr | |
| Target file: 0-target.arr | |
| 16384 | |
| createNcDim: numSeqs 1 | |
| createNcDim: numTimesteps 262144 | |
| createNcDim: inputPattSize 1 |
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| Subsequently, we attempt to solve the following task: | |
| SphereFunction | |
| fmin (array([ -1.96718823e-05, 3.87550180e-05, 2.20982432e-05]), 2.3772667291947832e-09) | |
| CMA (array([ 5.40759177e-07, -7.63606211e-06, -3.86932335e-06]), 7.3573528137241625e-11) | |
| NES (array([ -1.37096352e-04, -1.85657434e-05, 2.32781642e-05]), 1.9681969576692007e-08) | |
| FEM (array([ -2.41800088e-05, -1.40246886e-05, 3.84758011e-05]), 2.2617519878581808e-09) | |
| Finite Differences (array([-0.06813254, -0.02855401, -0.03060486]), 0.006394031410795596) | |
| SPSA (array([-1.42769912, 0.7243347 , -1.59992138]), 5.1227339471421285) | |
| PGPE (array([ -3.93519227e-06, -4.87915817e-06, 5.98595533e-06]), 7.5123583874849896e-11) | |
| HillClimber (array([ 0.00796732, 0.00024254, 0.0114661 ]), 0.00019500840909555657) |
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| Neueste Änderungen vom central holen | |
| $ git fetch central | |
| In entfernten Branch central/master wechseln | |
| $ git checkout central/master | |
| Lokale Kopie davon erzeugen |
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