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JavaScript

/* eslint-env browser, mocha */
describe('core layer: Highway', function () {
const assert = chai.assert
const styles = testGlobals.styles
const logTime = testGlobals.logTime
const stringifyCondensed = testGlobals.stringifyCondensed
const approxEquals = KerasJS.testUtils.approxEquals
const layers = KerasJS.layers
before(function () {
console.log('\n%ccore layer: Highway', styles.h1)
})
it('[core.Highway.0] should produce expected values, transformBias=-2, activation=linear bias=true', function () {
const key = 'core.Highway.0'
console.log(`\n%c[${key}] transformBias=-2, activation=linear bias=true`, styles.h3)
let testLayer = new layers.Highway({ transformBias: -2, activation: 'linear', bias: true })
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
t = testLayer.call(t)
const endTime = performance.now()
console.log('%cout', styles.h4, stringifyCondensed(t.tensor))
logTime(startTime, endTime)
const dataExpected = new Float32Array(TEST_DATA[key].expected.data)
const shapeExpected = TEST_DATA[key].expected.shape
assert.deepEqual(t.tensor.shape, shapeExpected)
assert.isTrue(approxEquals(t.tensor, dataExpected))
})
it('[core.Highway.1] should produce expected values, transformBias=-5, activation=tanh bias=true', function () {
const key = 'core.Highway.1'
console.log(`\n%c[${key}] transformBias=-5, activation=tanh bias=true`, styles.h3)
let testLayer = new layers.Highway({ transformBias: -5, activation: 'tanh', bias: true })
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
t = testLayer.call(t)
const endTime = performance.now()
console.log('%cout', styles.h4, stringifyCondensed(t.tensor))
logTime(startTime, endTime)
const dataExpected = new Float32Array(TEST_DATA[key].expected.data)
const shapeExpected = TEST_DATA[key].expected.shape
assert.deepEqual(t.tensor.shape, shapeExpected)
assert.isTrue(approxEquals(t.tensor, dataExpected))
})
it('[core.Highway.2] should produce expected values, transformBias=1, activation=hardSigmoid bias=false', function () {
const key = 'core.Highway.2'
console.log(`\n%c[${key}] transformBias=1, activation=hardSigmoid bias=false`, styles.h3)
let testLayer = new layers.Highway({ transformBias: 1, activation: 'hardSigmoid', bias: false })
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
t = testLayer.call(t)
const endTime = performance.now()
console.log('%cout', styles.h4, stringifyCondensed(t.tensor))
logTime(startTime, endTime)
const dataExpected = new Float32Array(TEST_DATA[key].expected.data)
const shapeExpected = TEST_DATA[key].expected.shape
assert.deepEqual(t.tensor.shape, shapeExpected)
assert.isTrue(approxEquals(t.tensor, dataExpected))
})
})