feat: structure

README.md

@@ -52,3 +52,46 @@ console.log(await net.predict(new Float32Array([1, 0])));
 console.log(await net.predict(new Float32Array([0, 1])));
 console.log(await net.predict(new Float32Array([1, 1])));
 ```
+
+#### Use the Native Backend
+
+```typescript
+import { DenseLayer, NeuralNetwork } from "https://deno.land/x/netsaur/mod.ts";
+import { Matrix, Native } from "https://deno.land/x/netsaur/backends/native.ts";
+
+const network = await new NeuralNetwork({
+  input: 2,
+  layers: [
+    new DenseLayer({ size: 3, activation: "sigmoid" }),
+    new DenseLayer({ size: 1, activation: "sigmoid" }),
+  ],
+  cost: "crossentropy",
+}).setupBackend(Native);
+
+network.train(
+  [
+    {
+      inputs: Matrix.of([
+        [0, 0],
+        [0, 1],
+        [1, 0],
+        [1, 1],
+      ]),
+      outputs: Matrix.column([0, 1, 1, 0]),
+    },
+  ],
+  5000,
+  0.1,
+);
+
+console.log(
+  await network.predict(
+    Matrix.of([
+      [0, 0],
+      [0, 1],
+      [1, 0],
+      [1, 1],
+    ]),
+  ),
+);
+```

backends/cpu.ts

@@ -0,0 +1 @@
+export { CPU } from "../src/cpu/mod.ts";

backends/gpu.ts

@@ -0,0 +1 @@
+export { GPU } from "../src/gpu/mod.ts";

backends/native.ts

@@ -0,0 +1,4 @@
+export { Native } from "../src/native/mod.ts";
+export { Matrix } from "../src/native/matrix.ts";
+export type { DataType } from "../src/native/matrix.ts";
+export type { Dataset } from "../src/native/backend.ts";

bench/netsaur/xor.ts

@@ -1,6 +1,5 @@
 import { NeuralNetwork, DenseLayer } from "../../mod.ts";
-import { Native } from "../../src/native/mod.ts";
-import { Matrix } from "../../src/native/matrix.ts";
+import { Native, Matrix  } from "../../backends/native.ts";
 
 const start = Date.now();
 

examples/mnist_digits/common.ts

@@ -1,5 +1,5 @@
-import { Dataset } from "../../src/native/backend.ts";
-import { Matrix } from "../../src/native/matrix.ts";
+import type { Dataset } from "../../backends/native.ts";
+import { Matrix } from "../../backends/native.ts";
 
 
 export function assert(condition: boolean, message?: string) {

examples/mnist_digits/predict.ts

@@ -1,5 +1,5 @@
 import { NativeBackend } from "../../src/native/backend.ts";
-import { DataType, Matrix } from "../../src/native/matrix.ts";
+import { DataType, Matrix } from "../../backends/native.ts";
 import { loadDataset } from "./common.ts";
 
 const network = NativeBackend.load("digit_model.bin");

examples/mnist_digits/train.ts

@@ -1,5 +1,5 @@
 import { DenseLayer, NeuralNetwork } from "../../mod.ts";
-import { Native } from "../../src/native/mod.ts";
+import { Native } from "../../backends/native.ts";
 import { loadDataset } from "./common.ts";
 
 const network = await new NeuralNetwork({

examples/train_conv.ts

@@ -3,7 +3,7 @@ import { ConvCPULayer } from "../src/cpu/layers/conv.ts";
 import { PoolCPULayer } from "../src/cpu/layers/pool.ts";
 import { CPUMatrix } from "../src/cpu/matrix.ts";
 import { CPUBackend } from "../src/cpu/backend.ts";
-import { CPU } from "../src/cpu/mod.ts";
+import { CPU } from "../backends/cpu.ts";
 
 const kernel = new Float32Array([
   1,

examples/train_emotion.ts

@@ -1,6 +1,6 @@
 import { DataType, DataTypeArray } from "../deps.ts";
 import { DenseLayer, NeuralNetwork } from "../mod.ts";
-import { CPU } from "../src/cpu/mod.ts";
+import { CPU } from "../backends/cpu.ts";
 
 const character = (string: string): Float32Array =>
   Float32Array.from(string.trim().split("").map(integer));

examples/train_letter.ts

@@ -1,6 +1,6 @@
 import { DataType, DataTypeArray } from "../deps.ts";
 import { DenseLayer, NeuralNetwork } from "../mod.ts";
-import { CPU } from "../src/cpu/mod.ts";
+import { CPU } from "../backends/cpu.ts";
 
 // https://github.com/BrainJS/brain.js/blob/master/examples/typescript/which-letter-simple.ts
 const character = (string: string): Float32Array =>

examples/train_xor_cpu.ts

@@ -1,5 +1,5 @@
 import { DenseLayer, NeuralNetwork } from "../mod.ts";
-import { CPU } from "../src/cpu/mod.ts";
+import { CPU } from "../backends/cpu.ts";
 
 const net = await new NeuralNetwork({
   silent: true,

examples/train_xor_gpu.ts

@@ -1,5 +1,5 @@
 import { DenseLayer, NeuralNetwork } from "../mod.ts";
-import { GPU } from "../src/gpu/mod.ts";
+import { GPU } from "../backends/gpu.ts";
 
 const net = await new NeuralNetwork({
   silent: true,

examples/train_xor_native.ts

@@ -1,6 +1,5 @@
 import { NeuralNetwork, DenseLayer } from "../mod.ts";
-import { Native } from "../src/native/mod.ts";
-import { Matrix } from "../src/native/matrix.ts";
+import { Native, Matrix } from "../backends/native.ts";
 
 const start = Date.now();
 

tests/conv.ts

@@ -1,14 +1,16 @@
 import { ConvLayer, DenseLayer, NeuralNetwork } from "../mod.ts";
 import { ConvCPULayer } from "../src/cpu/layers/conv.ts";
 import { CPUMatrix } from "../src/cpu/matrix.ts";
-import { CPUNetwork } from "../src/cpu/network.ts";
+import { CPUBackend } from "../src/cpu/backend.ts";
+import { CPU } from "../backends/cpu.ts";
+import { PoolCPULayer } from "../src/cpu/layers/pool.ts";
+import { PoolLayer } from "../src/mod.ts";
 
 import { decode } from "https://deno.land/x/[email protected]/mod.ts";
 import { DataTypeArray } from "../deps.ts";
-import { PoolCPULayer } from "../src/cpu/layers/pool.ts";
-import { PoolLayer } from "../src/mod.ts";
 
-import { Canvas } from "https://deno.land/x/[email protected]/canvas/mod.ts";
+
+import { Canvas } from "https://deno.land/x/[email protected]/canvas/mod.ts";
 
 const canvas = new Canvas({
   title: "Netsaur Convolutions",
@@ -58,10 +60,10 @@ const net = await new NeuralNetwork({
   ],
   cost: "crossentropy",
   input: 2,
-}).setupBackend("cpu");
+}).setupBackend(CPU);
 
 const input = new CPUMatrix(buf, dim, dim);
-const network = net.network as CPUNetwork;
+const network = net.backend as CPUBackend;
 const conv = network.layers[0] as ConvCPULayer;
 const pool = network.layers[1] as PoolCPULayer;
 network.initialize({ x: dim, y: dim }, 1);

tests/linear.ts

@@ -1,6 +1,5 @@
 import { NeuralNetwork, DenseLayer } from "../mod.ts";
-import { Native } from "../src/native/mod.ts";
-import { Matrix } from "../src/native/matrix.ts";
+import { Native, Matrix } from "../backends/native.ts";
 
 const start = performance.now();