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