Pointer assignment of index is being consistently inconsistent within addData(..)
. I expect memory address is moving around as underlying array increases in size.
Behavior: I assign to variable A
, then assign B = A*0.2
, then assign y = sig(B)
, finally B = y
. Sometimes on the next loop B == y
|| B == A*0.2
. It is perfectly consistent across multiple executions.
I made a simpler and more full version of the code.
package main
import(
"fmt"
"math"
)
func main(){
//Structure setup
l := lots{}; l.addData(2); l.addData(2); l.addData(2); l.addData(2)
l.val[0].y[0] = 0.20700021
l.val[0].y[1] = 0.30003001
l.propagate()
}
type data struct{
y []float64
}
type pair struct {
one *data
two *data
}
// lots is the biggest part of the structure
// the problem seems to occure when this is introduced
type lots struct{
val []data
join []pair
}
// addData appends a data struct and a pair struct to
// the corresponding parts of lots struct
func (l *lots)addData(size int){
l.val = append(l.val, data{make([]float64, size)})
// should be skipped first call only
if(len(l.join) < len(l.val)-1){
fmt.Println("len of l.val: ", len(l.val))
l.join = append(l.join, pair{})
l.join[len(l.join)-1].one = &l.val[len(l.val)-2]
l.join[len(l.join)-1].two = &l.val[len(l.val)-1]
}
}
// propagate
func (l *lots)propagate(){
for _, v := range l.join{
v.travel()
}
}
// travel modifies values going from p.one -> p.two
func (p *pair) travel(){
fmt.Println("p.one.y: ", p.one.y)
p.mathy()
fmt.Println("p.two.y: ", p.two.y)
p.two.y = sigmoid(p.two.y)
fmt.Println("p.two.y: ", p.two.y)
}
func (p *pair) mathy(){
for i := range p.one.y {
p.two.y[i] = p.one.y[i] * p.one.y[i]
}
}
// sigmoid seems to be causing some problems.
// Works fine on it's own though
func sigmoid(x []float64)(y []float64){
y = make([]float64, len(x))
for i := range x{
y[i] = 1./(1.+math.Exp(-x[i]))
}
return
}
I expect the #'s of p.two.y: [#'s]
to equal the following lines #'s of p.one.y: [#'s]
all the time. The output I am getting is not consistently equal. Sometimes the p.one.y: [#'s]
#'s are equal to the p.two.y: [#'s]
from the line preceding line; that value was over written and then that value came back.
p.one.y: [0.20700021 0.30003001]
p.two.y: [0.04284908694004409 0.0900180069006001]/////// bad
p.two.y: [0.5107106330188076 0.5224893174114301] // overwritten
p.one.y: [0.04284908694004409 0.0900180069006001]/////// reappeared
p.two.y: [0.0018360442515954571 0.008103241566356488]
p.two.y: [0.5004590109339528 0.5020257993066767]//// overwritten
p.one.y: [0.5004590109339528 0.5020257993066767]//// good
p.two.y: [0.25045922162499035 0.25202990316950763]
p.two.y: [0.5622895277500193 0.5626760660176802]
I have tried to reduce function nesting, and it worked when I put everything into the Propagate()
function and assigned directly to p.two.y[i]
with the sigmoid function. (below)
// propagate
func (l *lots)propagate(){
for _, p := range l.join{
fmt.Println("p.one.y: ", p.one.y)
for i := range p.one.y {
p.two.y[i] = p.one.y[i] * p.one.y[i]
}
fmt.Println("p.two.y: ", p.two.y)
// using this extra variable causes the problem of inconsistent assignment
//y := make([]float64, len(p.two.y))
for i := range p.two.y{
//y[i] = 1./(1.+math.Exp(-p.two.y[i]))
p.two.y[i] = 1./(1.+math.Exp(-p.two.y[i]))
}
//p.two.y = y
fmt.Println("p.two.y: ", p.two.y)
}
}
This version provides good data, but takes away so much of the specialization I like.
p.one.y: [0.20700021 0.30003001]
p.two.y: [0.04284908694004409 0.0900180069006001]
p.two.y: [0.5107106330188076 0.5224893174114301]////
p.one.y: [0.5107106330188076 0.5224893174114301]//// Good
p.two.y: [0.2608253506784712 0.27299508680906215]
p.two.y: [0.564839170446528 0.5678280461350629]////
p.one.y: [0.564839170446528 0.5678280461350629]//// Good
p.two.y: [0.3190432884707219 0.3224286899775631]
p.two.y: [0.5790910765397528 0.5799160282084651]
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