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# -*- coding: utf-8 -*- | |
import sys | |
import numpy | |
numpy.seterr(all='ignore') | |
''' |
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package main | |
import ( | |
"fmt" | |
"math" | |
"math/rand" | |
) | |
func uniform(min float64, max float64) float64 { |
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.A { | |
position: relative; | |
left: 30px; | |
width: 60px; | |
height: 91px; | |
border-bottom: solid 14px #000000; | |
} | |
.A:before { | |
transform: skew(-19deg, 0); | |
position: absolute; |
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.A { | |
position: relative; | |
left: 30px; | |
width: 60px; | |
height: 91px; | |
border-bottom: solid 14px #000000; | |
} | |
.A:before { | |
-webkit-transform: skew(-19deg, 0); | |
-moz-transform: skew(-19deg, 0); |
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package main | |
import ( | |
"fmt" | |
"math" | |
"math/rand" | |
) | |
func uniform(min float64, max float64) float64 { |
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package main | |
import ( | |
"fmt" | |
"math" | |
) | |
type LogisticRegression struct { | |
N int | |
n_in int |
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// $ scalac SdA.scala | |
// $ scala SdA | |
import scala.util.Random | |
import scala.math | |
class dA(val N: Int, val n_visible: Int, val n_hidden: Int, | |
_W: Array[Array[Double]]=null, _hbias: Array[Double]=null, _vbias: Array[Double]=null, |
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// $ scalac DBN.scala | |
// $ scala DBN | |
import scala.util.Random | |
import scala.math | |
class RBM(val N: Int, val n_visible: Int, val n_hidden: Int, | |
_W: Array[Array[Double]]=null, _hbias: Array[Double]=null, _vbias: Array[Double]=null, |
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#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
import sys | |
import numpy | |
numpy.seterr(all='ignore') | |
def sigmoid(x): |
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// $ scalac RBM.scala | |
// $ scala RBM | |
import scala.util.Random | |
import scala.math | |
class RBM(val N: Int, val n_visible: Int, val n_hidden: Int, | |
_W: Array[Array[Double]]=null, _hbias: Array[Double]=null, _vbias: Array[Double]=null, | |
var rng: Random=null) { | |