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base: SethTrowbridge:574c6704823f31b200e73dc51ac9ec6e18744674
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SethTrowbridge:master
SethTrowbridge:cleanup
SethTrowbridge:network
SethTrowbridge:debug
SethTrowbridge:typescript
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compare: SethTrowbridge:329c5f5f819c5d8a4ebab827b61de42a3aa6bc26
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SethTrowbridge:cleanup
SethTrowbridge:master
SethTrowbridge:network
SethTrowbridge:debug
SethTrowbridge:typescript

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3 changed files with 22 additions and 29 deletions
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9
m.test.js
View File

@ -136,15 +136,6 @@ Deno.test("Batch.Scale", ()=>
assertEquals(t[0].length, 2, "correct dimensions");
assertEquals(t[1][0], 1.5, "correct placement");
});
Deno.test("Batch.Subtract", ()=>
{
const c = [[1, 2], [3, 4]];
const s = [[0.5, 0.5], [0.5, 0.5]];
const t = M.Batch.Subtract(c, s);
assertEquals(t.length, 2, "correct count");
assertEquals(t[0].length, 2, "correct dimensions");
assertEquals(t[1][0], 2.5, "correct placement");
});
Deno.test("Batch.Sigmoid", ()=>
{
const m = [[-1000, 1000]];

31
nn.test.js
View File

@ -2,9 +2,16 @@ import { assert, assertEquals } from "https://deno.land/std@0.102.0/testing/asse
import { Label, Forward, Backward } from "./nn.ts";
import { default as M } from "./m.ts";
let training = [];
let stages = [];
let layers = [];
const input = [
[ 0.1, 0.05],
[ 0.0, -0.06]
[ 0.99, 0.85],
[ 1.2, 1.05]
];
const training = [];
const stages = [];
const layers = [];
Deno.test("NN.Label", ()=>
{
@ -31,28 +38,24 @@ Deno.test("NN.Label", ()=>
Deno.test("NN.Backward", ()=>
{
let layer1 = M.Create.Box([0, 0, 0], [1, 1, 1], 2);
let layer2 = M.Create.Box([0, 0, 0], [1, 1, 1], 1);
let copy1 = M.Create.Clone(layer1);
let copy2 = M.Create.Clone(layer2);
layers.push(M.Create.Box([0, 0, 0], [1, 1, 1], 4));
layers.push(M.Create.Box([0, 0, 0, 0, 0], [1, 1, 1, 1, 1], 1));
layers.push(layer1);
layers.push(layer2);
let copy1 = M.Create.Clone(layers[0]);
let copy2 = M.Create.Clone(layers[1]);
for(let i=0; i<100; i++)
for(let i=0; i<1000; i++)
{
Backward(stages, layers, training[1], 0.1);
}
assert(layers[0][0][0] != copy1[0][0], "first matrix has changed");
assert(layers[1][0][0] != copy2[0][0], "second matrix has changed");
assert(layers[0][0][0] != copy1[0][0][0], "first matrix has changed");
assert(layers[1][0][0] != copy2[0][0][0], "second matrix has changed");
});
Deno.test("NN.Forward", ()=>
{
console.log(Forward(stages, layers));
console.log(training[1]);
});

11
nn.ts
View File

@ -28,26 +28,25 @@ const Forward = (inStages:N, inLayers:N):Cloud.M =>
inStages[i+1] = process(i);
return inStages[i+1];
};
const Backward = (inStages:N, inLayers:N, inGoals:Cloud.M, inRate:number):N =>
const Backward = (inStages:N, inLayers:N, inGoals:Cloud.M, inRate:number):void =>
{
let i:number;
let errorBack:Cloud.M = M.Batch.Subtract(Forward(inStages, inLayers), inGoals);
for(i=inLayers.length-1; i>=0; i--)
{
let layerMatrix:Cloud.M = inLayers[i];
let layerInput:Cloud.M = inStages[i];
let layerOutput:Cloud.M = inStages[i+1];
let errorScaled:Cloud.M = M.Batch.Multiply(errorBack, M.Batch.Derivative(layerOutput));
errorBack = M.Batch.Affine(errorScaled, M.Create.Transpose(inLayers[i]));
errorBack = M.Batch.Affine(errorScaled, M.Create.Transpose(layerMatrix));
errorScaled.forEach((inScaledError:Cloud.V, inIndex:number)=> {
const deltas = M.Batch.Scale(M.Create.Outer(layerInput[inIndex], inScaledError), inRate);
inLayers[i] = M.Batch.Subtract(inLayers[i], deltas);
layerMatrix = M.Batch.Subtract(layerMatrix, deltas);
});
}
return inLayers;
};
export { Label, Forward, Backward };