keras-js/test/activations/activations.js

/* eslint-env browser, mocha */

describe('activations', function () {
  const assert = chai.assert
  const styles = testGlobals.styles
  const logTime = testGlobals.logTime
  const stringifyCondensed = testGlobals.stringifyCondensed
  const approxEquals = KerasJS.testUtils.approxEquals
  const activations = KerasJS.activations

  before(function () {
    console.log('\n%cactivations', styles.h1)
  })

  /*********************************************************
   * softmax
   *********************************************************/

  describe('softmax', function () {
    before(function () {
      console.log('\n%csoftmax', styles.h2)
    })

    it('[activations.softmax.0] should work for 1D tensor', function () {
      const key = 'activations.softmax.0'
      console.log(`\n%c[${key}] 1D`, styles.h3)
      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()
      activations.softmax(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('[activations.softmax.1] should work for 2D tensor', function () {
      const key = 'activations.softmax.1'
      console.log(`\n%c[${key}] 2D`, styles.h3)
      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()
      activations.softmax(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('[activations.softmax.2] should work for very large values', function () {
      const key = 'activations.softmax.2'
      console.log(`\n%c[${key}] 1D, large values`, styles.h3)
      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()
      activations.softmax(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))
    })
  })

  /*********************************************************
   * softplus
   *********************************************************/

  describe('softplus', function () {
    before(function () {
      console.log('\n%csoftplus', styles.h2)
    })

    it('[activations.softplus.0] should work for 1D tensor', function () {
      const key = 'activations.softplus.0'
      console.log(`\n%c[${key}] 1D`, styles.h3)
      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()
      activations.softplus(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('[activations.softplus.1] should work for 2D tensor', function () {
      const key = 'activations.softplus.1'
      console.log(`\n%c[${key}] 2D`, styles.h3)
      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()
      activations.softplus(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('[activations.softplus.2] should work for 3D tensor', function () {
      const key = 'activations.softplus.2'
      console.log(`\n%c[${key}] 3D`, styles.h3)
      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()
      activations.softplus(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))
    })
  })

  /*********************************************************
   * softsign
   *********************************************************/

  describe('softsign', function () {
    before(function () {
      console.log('\n%csoftsign', styles.h2)
    })

    it('[activations.softsign.0] should work for 1D tensor', function () {
      const key = 'activations.softsign.0'
      console.log(`\n%c[${key}] 1D`, styles.h3)
      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()
      activations.softsign(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('[activations.softsign.1] should work for 2D tensor', function () {
      const key = 'activations.softsign.1'
      console.log(`\n%c[${key}] 2D`, styles.h3)
      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()
      activations.softsign(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('[activations.softsign.2] should work for 3D tensor', function () {
      const key = 'activations.softsign.2'
      console.log(`\n%c[${key}] 3D`, styles.h3)
      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()
      activations.softsign(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))
    })
  })

  /*********************************************************
   * relu
   *********************************************************/

  describe('relu', function () {
    before(function () {
      console.log('\n%crelu', styles.h2)
    })

    it('[activations.relu.0] should work for 1D tensor', function () {
      const key = 'activations.relu.0'
      console.log(`\n%c[${key}] 1D`, styles.h3)
      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()
      activations.relu(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('[activations.relu.1] should work for 2D tensor', function () {
      const key = 'activations.relu.1'
      console.log(`\n%c[${key}] 2D`, styles.h3)
      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()
      activations.relu(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('[activations.relu.2] should work for 3D tensor', function () {
      const key = 'activations.relu.2'
      console.log(`\n%c[${key}] 3D`, styles.h3)
      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()
      activations.relu(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('[activations.relu.3] should work with maxValue', function () {
      const key = 'activations.relu.3'
      console.log(`\n%c[${key}] 3D, maxValue=0.5`, styles.h3)
      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()
      activations.relu(t, { maxValue: 0.5 })
      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('[activations.relu.4] should work with alpha (slope of negative portion)', function () {
      const key = 'activations.relu.4'
      console.log(`\n%c[${key}] 3D, alpha=0.3`, styles.h3)
      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()
      activations.relu(t, { alpha: 0.3 })
      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))
    })
  })

  /*********************************************************
   * tanh
   *********************************************************/

  describe('tanh', function () {
    before(function () {
      console.log('\n%ctanh', styles.h2)
    })

    it('[activations.tanh.0] should work for 1D tensor', function () {
      const key = 'activations.tanh.0'
      console.log(`\n%c[${key}] 1D`, styles.h3)
      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()
      activations.tanh(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('[activations.tanh.1] should work for 2D tensor', function () {
      const key = 'activations.tanh.1'
      console.log(`\n%c[${key}] 2D`, styles.h3)
      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()
      activations.tanh(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('[activations.tanh.2] should work for 3D tensor', function () {
      const key = 'activations.tanh.2'
      console.log(`\n%c[${key}] 3D`, styles.h3)
      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()
      activations.tanh(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))
    })
  })

  /*********************************************************
   * sigmoid
   *********************************************************/

  describe('sigmoid', function () {
    before(function () {
      console.log('\n%csigmoid', styles.h2)
    })

    it('[activations.sigmoid.0] should work for 1D tensor', function () {
      const key = 'activations.sigmoid.0'
      console.log(`\n%c[${key}] 1D`, styles.h3)
      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()
      activations.sigmoid(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('[activations.sigmoid.1] should work for 2D tensor', function () {
      const key = 'activations.sigmoid.1'
      console.log(`\n%c[${key}] 2D`, styles.h3)
      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()
      activations.sigmoid(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('[activations.sigmoid.2] should work for 3D tensor', function () {
      const key = 'activations.sigmoid.2'
      console.log(`\n%c[${key}] 3D`, styles.h3)
      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()
      activations.sigmoid(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))
    })
  })

  /*********************************************************
   * hardSigmoid
   *********************************************************/

  describe('hardSigmoid', function () {
    before(function () {
      console.log('\n%chardSigmoid', styles.h2)
    })

    it('[activations.hardSigmoid.0] should work for 1D tensor', function () {
      const key = 'activations.hardSigmoid.0'
      console.log(`\n%c[${key}] 1D`, styles.h3)
      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()
      activations.hardSigmoid(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('[activations.hardSigmoid.1] should work for 2D tensor', function () {
      const key = 'activations.hardSigmoid.1'
      console.log(`\n%c[${key}] 2D`, styles.h3)
      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()
      activations.hardSigmoid(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('[activations.hardSigmoid.2] should work for 3D tensor', function () {
      const key = 'activations.hardSigmoid.2'
      console.log(`\n%c[${key}] 3D`, styles.h3)
      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()
      activations.hardSigmoid(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))
    })
  })

  /*********************************************************
   * linear
   *********************************************************/

  describe('linear', function () {
    before(function () {
      console.log('\n%clinear', styles.h2)
    })

    it('[activations.linear.0] should work for 1D tensor', function () {
      const key = 'activations.linear.0'
      console.log(`\n%c[${key}] 1D`, styles.h3)
      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()
      activations.linear(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('[activations.linear.1] should work for 2D tensor', function () {
      const key = 'activations.linear.1'
      console.log(`\n%c[${key}] 2D`, styles.h3)
      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()
      activations.linear(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('[activations.linear.2] should work for 3D tensor', function () {
      const key = 'activations.linear.2'
      console.log(`\n%c[${key}] 3D`, styles.h3)
      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()
      activations.linear(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))
    })
  })
})