mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-05-14 20:48:00 +00:00
cd8775f518
### Description The Node JS Samples included in the repository have outdated package references that are broken, which are fixed in this PR. ### Motivation and Context The samples included in this repository should just work, but sadly do not. The reason is that they are using very outdated references for the npm modules. This fix updates the dependencies to the current onnxruntime-node, which fixes the samples. Also adds a small update to the .gitignore to exclude the node_modules directories in the samples directory, which keeps the local repo changelist cleaner.
62 lines
1.8 KiB
JavaScript
62 lines
1.8 KiB
JavaScript
'use strict';
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const Tensor = require('onnxruntime-node').Tensor;
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//
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// create a [2x3x4] float tensor
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//
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const buffer01 = new Float32Array(24);
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buffer01[0] = 0.1; // fill buffer data
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const tensor01 = new Tensor('float32', buffer01, [2, 3, 4]);
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// type 'float32' can be omitted and the type is inferred from data
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const tensor01_B = new Tensor(buffer01, [2, 3, 4]);
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//
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// create a [1x2] boolean tensor
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//
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const buffer02 = new Uint8Array(2);
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buffer02[0] = 1; // true
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buffer02[1] = 0; // false
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const tensor02 = new Tensor('bool', buffer02, [1, 2]); // type 'bool' cannot omit as both 'bool' and 'uint8' uses Uint8Array.
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//
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// create a scaler float64 tensor
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//
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const tensor03 = new Tensor(new Float64Array(1), []);
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tensor03.data[0] = 1.0; // setting data after tensor is created is allowed
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//
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// create a one-dimension tensor
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//
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const tensor04 = new Tensor(new Float32Array(100), [100]);
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const tensor04_B = new Tensor(new Float32Array(100)); // dims can be omitted if it is a 1-D tensor. tensor04.dims = [100]
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//
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// create a [1x2] string tensor
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//
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const tensor05 = new Tensor('string', ['a', 'b'], [1, 2]);
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const tensor05_B = new Tensor(['a', 'b'], [1, 2]); // type 'string' can be omitted
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//
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// !!! BAD USAGES !!!
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// followings are bad usages that may cause an error to be thrown. try not to make these mistakes.
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//
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// create from mismatched TypedArray
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try {
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const tensor = new Tensor('float64', new Float32Array(100)); // 'float64' must use with Float64Array as data.
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} catch{ }
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// bad dimension (negative value)
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try {
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const tensor = new Tensor(new Float32Array(100), [1, 2, -1]); // negative dims is not allowed.
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} catch{ }
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// size mismatch (scalar size should be 1)
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try {
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const tensor = new Tensor(new Float32Array(0), []);
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} catch{ }
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// size mismatch (5 * 6 != 40)
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try {
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const tensor = new Tensor(new Float32Array(40), [5, 6]);
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} catch{ }
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