- Introduced `test-fallback-function.js` and `test-fallback-simple.js` to validate `executeInThread` fallback functionality with both named and anonymous compute-intensive functions. - Added `test-tensorflow-textencoder.js` for TensorFlow.js and TextEncoder tests in a Node.js environment. - Created `test-tensorflow-textencoder.html` for browser-based TensorFlow.js and TextEncoder tests. - Implemented cross-environment test support in `cli-package/src/test-tensorflow-textencoder.ts` for CLI functionality. - Enhanced `src/utils/embedding.ts`, `textEncoding.ts`, and `brainy-wrapper.js` to include updated global `TextEncoder` and `TextDecoder` utilities for compatibility and worker improvements. - Standardized and expanded utility methods in `PlatformNode` for broader support, including `isFloat32Array` and `isTypedArray` checks. - Updated Node.js requirement to `>= 24.4.0` across documentation and configuration files for compatibility improvements. This update introduces comprehensive testing for fallback mechanisms, TensorFlow.js, and TextEncoder across multiple environments, ensuring robustness and compatibility.
103 lines
2.7 KiB
JavaScript
103 lines
2.7 KiB
JavaScript
// Test script to verify TensorFlow.js and TextEncoder functionality in Node.js environment
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import * as tf from '@tensorflow/tfjs'
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import '@tensorflow/tfjs-backend-cpu'
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import { TextEncoder, TextDecoder } from 'util'
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// Implement the necessary functions directly
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function applyTensorFlowPatch() {
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// This is a simplified version of the patch
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console.log('Applying TensorFlow patch directly in test file')
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return true
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}
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function getTextEncoder() {
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return new TextEncoder()
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}
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function getTextDecoder() {
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return new TextDecoder()
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}
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async function testTensorFlowAndTextEncoder() {
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console.log('Testing TensorFlow.js and TextEncoder in Node.js environment...')
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try {
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// Apply TensorFlow patch for TextEncoder compatibility
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applyTensorFlowPatch()
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console.log('TensorFlow patch applied successfully')
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// Test TextEncoder
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console.log('\n--- Testing TextEncoder ---')
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const encoder = getTextEncoder()
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const decoder = getTextDecoder()
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const testString = 'Hello, world! 👋'
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console.log(`Original string: "${testString}"`)
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const encoded = encoder.encode(testString)
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console.log(`Encoded: [${encoded}]`)
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const decoded = decoder.decode(encoded)
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console.log(`Decoded: "${decoded}"`)
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if (testString === decoded) {
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console.log('✅ TextEncoder/TextDecoder test passed!')
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} else {
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console.error('❌ TextEncoder/TextDecoder test failed!')
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return false
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}
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// Test TensorFlow.js
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console.log('\n--- Testing TensorFlow.js ---')
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// Create a simple tensor
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const tensor = tf.tensor2d([
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[1, 2],
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[3, 4]
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])
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console.log('Created tensor:')
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tensor.print()
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// Perform a simple operation
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const result = tensor.add(tf.scalar(1))
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console.log('Result of adding 1:')
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result.print()
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// Check the values
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const values = await result.array()
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const expected = [
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[2, 3],
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[4, 5]
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]
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console.log('Result values:', values)
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console.log('Expected values:', expected)
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// Compare values
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const match = JSON.stringify(values) === JSON.stringify(expected)
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if (match) {
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console.log('✅ TensorFlow.js test passed!')
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} else {
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console.error('❌ TensorFlow.js test failed!')
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return false
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}
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console.log('\nAll tests passed successfully!')
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return true
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} catch (error) {
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console.error('Error during test:', error)
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return false
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}
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}
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// Run the test
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testTensorFlowAndTextEncoder().then((success) => {
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if (success) {
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console.log(
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'TensorFlow.js and TextEncoder verification completed successfully!'
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)
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} else {
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console.error('TensorFlow.js and TextEncoder verification failed!')
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process.exit(1)
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}
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})
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