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### QuickStart | ||
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This example shows how to train a neural network to predict the output of the | ||
XOR function our speedy CPU backend written in rust. | ||
XOR function our speedy CPU backend written in [Rust](https://www.rust-lang.org/). | ||
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```typescript | ||
import { | ||
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@@ -253,7 +253,7 @@ console.log(`1 xor 1 = ${out4[0]} (should be close to 0)`); | |
### Documentation | ||
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The full documentation for Netsaur can be found | ||
[here](https://deno.land/x/[email protected].7/mod.ts). | ||
[here](https://deno.land/x/[email protected].10/mod.ts). | ||
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### License | ||
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[package] | ||
edition = "2021" | ||
name = "netsaur" | ||
version = "0.2.9" | ||
version = "0.2.10" | ||
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[lib] | ||
crate-type = ["cdylib"] | ||
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export { CsvParseStream } from "https://deno.land/std@0.198.0/csv/csv_parse_stream.ts"; | ||
export { CsvParseStream } from "https://deno.land/std@0.204.0/csv/csv_parse_stream.ts"; |
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export { dlopen } from "https://deno.land/x/[email protected].2/mod.ts"; | ||
export type { FetchOptions } from "https://deno.land/x/[email protected].2/mod.ts"; | ||
export { dlopen } from "https://deno.land/x/[email protected].3/mod.ts"; | ||
export type { FetchOptions } from "https://deno.land/x/[email protected].3/mod.ts"; |
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@@ -70,20 +70,20 @@ | |
} | ||
], | ||
"source": [ | ||
"import { tensor1D } from \"https://deno.land/x/[email protected].9/mod.ts\";\n", | ||
"import { Visualizer } from \"https://deno.land/x/[email protected].9/visualizer/mod.ts\";\n", | ||
"import { tensor1D } from \"https://deno.land/x/[email protected].10/mod.ts\";\n", | ||
"import { Visualizer } from \"https://deno.land/x/[email protected].10/visualizer/mod.ts\";\n", | ||
"\n", | ||
"import {\n", | ||
" Cost,\n", | ||
" WASM,\n", | ||
" AUTO,\n", | ||
" DenseLayer,\n", | ||
" Sequential,\n", | ||
" setupBackend,\n", | ||
" SigmoidLayer,\n", | ||
" tensor2D,\n", | ||
"} from \"../mod.ts\";\n", | ||
"} from \"https://deno.land/x/[email protected]/mod.ts\";\n", | ||
" \n", | ||
"await setupBackend(WASM);\n", | ||
"await setupBackend(AUTO);\n", | ||
"\n", | ||
"const net = new Sequential({\n", | ||
" size: [4, 2],\n", | ||
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" outputs: tensor2D([[0], [1], [1], [0]]),\n", | ||
" },\n", | ||
" ],\n", | ||
" 50000,\n", | ||
" 1000000,\n", | ||
");\n", | ||
" \n", | ||
"const visualizer = new Visualizer(\"XOR Example\");\n", | ||
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} | ||
], | ||
"source": [ | ||
"import { setupBackend, CPU } from \"https://deno.land/x/[email protected].9/mod.ts\";\n", | ||
"import { setupBackend, CPU } from \"https://deno.land/x/[email protected].10/mod.ts\";\n", | ||
"await setupBackend(CPU);" | ||
] | ||
}, | ||
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@@ -68,7 +68,7 @@ | |
} | ||
], | ||
"source": [ | ||
"import { setupBackend, WASM } from \"https://deno.land/x/[email protected].9/mod.ts\";\n", | ||
"import { setupBackend, WASM } from \"https://deno.land/x/[email protected].10/mod.ts\";\n", | ||
"await setupBackend(WASM);" | ||
] | ||
}, | ||
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@@ -92,7 +92,7 @@ | |
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"import { setupBackend, GPU } from \"https://deno.land/x/[email protected].9/mod.ts\";\n", | ||
"import { setupBackend, GPU } from \"https://deno.land/x/[email protected].10/mod.ts\";\n", | ||
"await setupBackend(GPU);" | ||
] | ||
}, | ||
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@@ -109,7 +109,7 @@ | |
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"import { Sequential, DenseLayer, SigmoidLayer, Cost, tensor2D, tensor1D } from \"https://deno.land/x/[email protected].9/mod.ts\";\n", | ||
"import { Sequential, DenseLayer, SigmoidLayer, Cost, tensor2D, tensor1D } from \"https://deno.land/x/[email protected].10/mod.ts\";\n", | ||
"const net = new Sequential({\n", | ||
" /**\n", | ||
" * The number of minibatches is set to 4 and the output size is set to 2.\n", | ||
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