onnxruntime/nodejs/test/e2e/simple-e2e-tests.ts
Yulong Wang 5dfc91db51
Node.js binding for ONNX Runtime (#3613)
* 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
2020-05-05 11:45:12 -07:00

105 lines
4.3 KiB
TypeScript

// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
import assert from 'assert';
import * as path from 'path';
import {Tensor} from '../../lib';
import {InferenceSession} from '../../lib/inference-session';
import {assertDataEqual, TEST_DATA_ROOT} from '../test-utils';
const MODEL_TEST_TYPES_CASES:
Array<{model: string; type: Tensor.Type; input0: Tensor.DataType; expectedOutput0: Tensor.DataType}> = [
{
model: path.join(TEST_DATA_ROOT, 'test_types_BOOL.pb'),
type: 'bool',
input0: Uint8Array.from([1, 0, 0, 1, 0]),
expectedOutput0: Uint8Array.from([1, 0, 0, 1, 0])
},
{
model: path.join(TEST_DATA_ROOT, 'test_types_DOUBLE.pb'),
type: 'float64',
input0: Float64Array.from([1.0, 2.0, 3.0, 4.0, 5.0]),
expectedOutput0: Float64Array.from([1.0, 2.0, 3.0, 4.0, 5.0])
},
{
model: path.join(TEST_DATA_ROOT, 'test_types_FLOAT.pb'),
type: 'float32',
input0: Float32Array.from([1.0, 2.0, 3.0, 4.0, 5.0]),
expectedOutput0: Float32Array.from([1.0, 2.0, 3.0, 4.0, 5.0])
},
{
model: path.join(TEST_DATA_ROOT, 'test_types_INT8.pb'),
type: 'int8',
input0: Int8Array.from([1, -2, 3, 4, -5]),
expectedOutput0: Int8Array.from([1, -2, 3, 4, -5])
},
{
model: path.join(TEST_DATA_ROOT, 'test_types_INT16.pb'),
type: 'int16',
input0: Int16Array.from([1, -2, 3, 4, -5]),
expectedOutput0: Int16Array.from([1, -2, 3, 4, -5])
},
{
model: path.join(TEST_DATA_ROOT, 'test_types_INT32.pb'),
type: 'int32',
input0: Int32Array.from([1, -2, 3, 4, -5]),
expectedOutput0: Int32Array.from([1, -2, 3, 4, -5])
},
{
model: path.join(TEST_DATA_ROOT, 'test_types_INT64.pb'),
type: 'int64',
input0: BigInt64Array.from([BigInt(1), BigInt(-2), BigInt(3), BigInt(4), BigInt(-5)]),
expectedOutput0: BigInt64Array.from([BigInt(1), BigInt(-2), BigInt(3), BigInt(4), BigInt(-5)])
},
{
model: path.join(TEST_DATA_ROOT, 'test_types_STRING.pb'),
type: 'string',
input0: ['a', 'b', 'c', 'd', 'e'],
expectedOutput0: ['a', 'b', 'c', 'd', 'e']
},
{
model: path.join(TEST_DATA_ROOT, 'test_types_UINT8.pb'),
type: 'uint8',
input0: Uint8Array.from([1, 2, 3, 4, 5]),
expectedOutput0: Uint8Array.from([1, 2, 3, 4, 5])
},
{
model: path.join(TEST_DATA_ROOT, 'test_types_UINT16.pb'),
type: 'uint16',
input0: Uint16Array.from([1, 2, 3, 4, 5]),
expectedOutput0: Uint16Array.from([1, 2, 3, 4, 5])
},
{
model: path.join(TEST_DATA_ROOT, 'test_types_UINT32.pb'),
type: 'uint32',
input0: Uint32Array.from([1, 2, 3, 4, 5]),
expectedOutput0: Uint32Array.from([1, 2, 3, 4, 5])
},
{
model: path.join(TEST_DATA_ROOT, 'test_types_UINT64.pb'),
type: 'uint64',
input0: BigUint64Array.from([BigInt(1), BigInt(2), BigInt(3), BigInt(4), BigInt(5)]),
expectedOutput0: BigUint64Array.from([BigInt(1), BigInt(2), BigInt(3), BigInt(4), BigInt(5)])
},
];
describe('E2E Tests - simple E2E tests', () => {
MODEL_TEST_TYPES_CASES.forEach(testCase => {
it(`${testCase.model}`, async () => {
const session = await InferenceSession.create(testCase.model);
const output = await session.run({'input': new Tensor(testCase.type, testCase.input0, [1, 5])});
assert(Object.prototype.hasOwnProperty.call(output, 'output'), '\'output\' should be in the result object.');
assert(output.output instanceof Tensor, 'result[output] should be a Tensor object.');
assert.strictEqual(output.output.size, 5, `output size expected 5, got ${output.output.size}.`);
assert.strictEqual(
output.output.type, testCase.type, `tensor type expected ${testCase.type}, got ${output.output.type}.`);
assert.strictEqual(
Object.getPrototypeOf(output.output.data), Object.getPrototypeOf(testCase.expectedOutput0),
`tensor data expected ${Object.getPrototypeOf(testCase.expectedOutput0).constructor.name}, got ${
Object.getPrototypeOf(output.output.data).constructor.name}`);
assertDataEqual(testCase.type, output.output.data, testCase.expectedOutput0);
});
});
});