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49 lines
2.1 KiB
JavaScript
49 lines
2.1 KiB
JavaScript
/* eslint-env browser, mocha */
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describe('convolutional layer: ZeroPadding1D', function () {
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const assert = chai.assert
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const styles = testGlobals.styles
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const logTime = testGlobals.logTime
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const stringifyCondensed = testGlobals.stringifyCondensed
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const approxEquals = KerasJS.testUtils.approxEquals
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const layers = KerasJS.layers
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before(function () {
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console.log('\n%cconvolutional layer: ZeroPadding1D', styles.h1)
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})
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it(`[convolutional.ZeroPadding1D.0] padding 1 on 3x5 input`, function () {
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const key = `convolutional.ZeroPadding1D.0`
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console.log(`\n%c[${key}] padding 1 on 3x5 input`, styles.h3)
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let testLayer = new layers.ZeroPadding1D({ padding: 1 })
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let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
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console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
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const startTime = performance.now()
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t = testLayer.call(t)
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const endTime = performance.now()
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console.log('%cout', styles.h4, stringifyCondensed(t.tensor))
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logTime(startTime, endTime)
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const dataExpected = new Float32Array(TEST_DATA[key].expected.data)
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const shapeExpected = TEST_DATA[key].expected.shape
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assert.deepEqual(t.tensor.shape, shapeExpected)
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assert.isTrue(approxEquals(t.tensor, dataExpected))
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})
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it(`[convolutional.ZeroPadding1D.1] padding 3 on 4x4 input`, function () {
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const key = `convolutional.ZeroPadding1D.1`
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console.log(`\n%c[${key}] padding 3 on 4x4 input`, styles.h3)
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let testLayer = new layers.ZeroPadding1D({ padding: 3 })
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let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
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console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
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const startTime = performance.now()
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t = testLayer.call(t)
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const endTime = performance.now()
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console.log('%cout', styles.h4, stringifyCondensed(t.tensor))
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logTime(startTime, endTime)
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const dataExpected = new Float32Array(TEST_DATA[key].expected.data)
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const shapeExpected = TEST_DATA[key].expected.shape
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assert.deepEqual(t.tensor.shape, shapeExpected)
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assert.isTrue(approxEquals(t.tensor, dataExpected))
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})
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})
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