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https://github.com/saymrwulf/onnxruntime.git
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* initial commit for Node.js binding * add c++ code * add inference session impl * e2e working * add settings.json * add test data * adjust binding declaration * refine tensor constructor declaration * update tests * enable onnx tests * simply refine readme * refine cpp impl * refine tests * formatting * add linting * move bin folder * fix linux build * manually update test filter list * update C++ API headers: fix crash in release build * make (manually) prebuild work * add test into prepack script * specify prebuild runtime type (N-API) * build.ts: update rebuild and include regex * fix lazy load on electron.js * update dev version, git link and binary host * support session options and run options * bump dev version * update README * add 1 example * move folder * adjust path * update document for examples * rename example 01 * add example 02 * add session option: log severity level * add example 04 * resolve comments * fix typo * remove double guard in header files * add copyright banner * move BUILD outside from README * consume test filter list from onnxruntime
101 lines
4.4 KiB
TypeScript
101 lines
4.4 KiB
TypeScript
// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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import * as assert from 'assert';
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// tensor with type information
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import {Tensor} from '../../../lib/tensor';
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import {createTestData, NUMERIC_TYPE_MAP} from '../../test-utils';
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// tensor with no type information, used for testing type check
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const TensorAny = Tensor as any;
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function testAllTensortypes(
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title: string, length: number,
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funcNumerictypes: (passtypeParam: boolean, type: Tensor.Type, data: Tensor.DataType) => void,
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funcStringtype?: (passtypeParam: boolean, data: string[]) => void): void {
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NUMERIC_TYPE_MAP.forEach((ctor, type) => {
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it(`${title} - (${type}, ${ctor.name})`, () => {
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funcNumerictypes(true, type, createTestData(type, length));
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});
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if (type !== 'bool') {
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it(`${title} - (${ctor.name})`, () => {
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funcNumerictypes(false, type, createTestData(type, length));
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});
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}
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});
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if (!funcStringtype) {
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it(`${title} - (string, ${Array.name})`, () => {
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funcNumerictypes(true, 'string', createTestData('string', length));
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});
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it(`${title} - (${Array.name})`, () => {
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funcNumerictypes(false, 'string', createTestData('string', length));
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});
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} else {
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it(`${title} - (string, string[])`, () => {
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funcStringtype(true, createTestData('string', length) as string[]);
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});
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it(`${title} - (string[])`, () => {
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funcStringtype(false, createTestData('string', length) as string[]);
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});
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}
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}
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describe('UnitTests - tensor', () => {
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testAllTensortypes('check data and type', 100, (passtypeParam, type, data) => { // numeric and string tensors
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const tensor0 = passtypeParam ? new Tensor(type, data) : new Tensor(data);
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assert.strictEqual(tensor0.data, data, 'tensor.data and data should be the same object.');
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assert.strictEqual(tensor0.type, type, 'tensor.type and type should be equal.');
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});
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testAllTensortypes('check dims (omitted)', 200, (passtypeParam, type, data) => { // numeric and string tensors
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const tensor0 = passtypeParam ? new Tensor(type, data) : new Tensor(data);
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assert.deepStrictEqual(
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tensor0.dims, [200],
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'tensor.dims should be a number array with exactly 1 item, with value of the array length.');
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});
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testAllTensortypes('check dims (specified)', 60, (passtypeParam, type, data) => { // numeric and string tensors
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const tensor0 = passtypeParam ? new Tensor(type, data, [3, 4, 5]) : new Tensor(data, [3, 4, 5]);
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assert.deepStrictEqual(tensor0.dims, [3, 4, 5], 'tensor.dims should be a number array with the given 3 items.');
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});
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testAllTensortypes(
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'BAD CALL - invalid dims type', 100, (passtypeParam, type, data) => { // numeric and string tensors
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assert.throws(() => {
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const badDims = {};
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passtypeParam ? new TensorAny(type, data, badDims) : new TensorAny(data, badDims);
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}, {name: 'TypeError', message: /must be a number array/});
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});
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testAllTensortypes(
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'BAD CALL - invalid dims element type', 100, (passtypeParam, type, data) => { // numeric and string tensors
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assert.throws(() => {
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const badDims = [1, 2, ''];
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passtypeParam ? new TensorAny(type, data, badDims) : new TensorAny(data, badDims);
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}, {name: 'TypeError', message: /must be an integer/});
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});
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testAllTensortypes(
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'BAD CALL - invalid dims number type (negative)', 100,
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(passtypeParam, type, data) => { // numeric and string tensors
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assert.throws(() => {
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const badDims = [1, 2, -1];
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passtypeParam ? new TensorAny(type, data, badDims) : new TensorAny(data, badDims);
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}, {name: 'RangeError', message: /must be a non-negative integer/});
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});
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testAllTensortypes(
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'BAD CALL - invalid dims number type (non-integer)', 100,
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(passtypeParam, type, data) => { // numeric and string tensors
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assert.throws(() => {
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const badDims = [1, 2, 1.5];
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passtypeParam ? new TensorAny(type, data, badDims) : new TensorAny(data, badDims);
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}, {name: 'TypeError', message: /must be an integer/});
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});
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testAllTensortypes(
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'BAD CALL - length and dims does not match', 100, (passtypeParam, type, data) => { // numeric and string tensors
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assert.throws(() => {
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const badDims = [10, 8];
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passtypeParam ? new TensorAny(type, data, badDims) : new TensorAny(data, badDims);
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}, {name: 'Error', message: /does not match data length/});
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});
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});
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