implement BatchNormalization in all modes, with tests

test/normalization/BatchNormalization.js

@@ -0,0 +1,46 @@
+/* eslint-env browser, mocha */
+
+describe('normalization layer: BatchNormalization', 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
+
+  const testParams = [
+    { attrs: { epsilon: 1e-5, mode: 0, axis: -1 } },
+    { attrs: { epsilon: 1e-2, mode: 0, axis: -1 } },
+    { attrs: { epsilon: 1e-5, mode: 0, axis: 1 } },
+    { attrs: { epsilon: 1e-5, mode: 0, axis: 2 } },
+    { attrs: { epsilon: 1e-5, mode: 0, axis: 3 } },
+    { attrs: { epsilon: 1e-5, mode: 1, axis: -1 } },
+    { attrs: { epsilon: 1e-5, mode: 2, axis: -1 } }
+  ]
+
+  before(function () {
+    console.log('\n%cnormalization layer: BatchNormalization', styles.h1)
+  })
+
+  testParams.forEach(({ attrs }, i) => {
+    const key = `normalization.BatchNormalization.${i}`
+    const title = `[${key}] test: epsilon='${attrs.epsilon}', mode=${attrs.mode}, axis=${attrs.axis}`
+
+    it(title, function () {
+      console.log(`\n%c${title}`, styles.h3)
+      let testLayer = new layers.BatchNormalization(attrs)
+      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))
+    })
+  })
+})