Method load

mnist/data.js:41–96

()

  constructor() {}

  async load() {
    // Make a request for the MNIST sprited image.
    const img = new Image();
    const canvas = document.createElement('canvas');
    const ctx = canvas.getContext('2d');
    const imgRequest = new Promise((resolve, reject) => {
      img.crossOrigin = '';
      img.onload = () => {
        img.width = img.naturalWidth;
        img.height = img.naturalHeight;

        const datasetBytesBuffer =
            new ArrayBuffer(NUM_DATASET_ELEMENTS * IMAGE_SIZE * 4);

        const chunkSize = 5000;
        canvas.width = img.width;
        canvas.height = chunkSize;

        for (let i = 0; i < NUM_DATASET_ELEMENTS / chunkSize; i++) {
          const datasetBytesView = new Float32Array(
              datasetBytesBuffer, i * IMAGE_SIZE * chunkSize * 4,
              IMAGE_SIZE * chunkSize);
          ctx.drawImage(
              img, 0, i * chunkSize, img.width, chunkSize, 0, 0, img.width,
              chunkSize);

          const imageData = ctx.getImageData(0, 0, canvas.width, canvas.height);

          for (let j = 0; j < imageData.data.length / 4; j++) {
            // All channels hold an equal value since the image is grayscale, so
            // just read the red channel.
            datasetBytesView[j] = imageData.data[j * 4] / 255;
          }
        }
        this.datasetImages = new Float32Array(datasetBytesBuffer);

        resolve();
      };
      img.src = MNIST_IMAGES_SPRITE_PATH;
    });

    const labelsRequest = fetch(MNIST_LABELS_PATH);
    const [imgResponse, labelsResponse] =
        await Promise.all([imgRequest, labelsRequest]);

    this.datasetLabels = new Uint8Array(await labelsResponse.arrayBuffer());

    // Slice the the images and labels into train and test sets.
    this.trainImages =
        this.datasetImages.slice(0, IMAGE_SIZE * NUM_TRAIN_ELEMENTS);
    this.testImages = this.datasetImages.slice(IMAGE_SIZE * NUM_TRAIN_ELEMENTS);
    this.trainLabels =
        this.datasetLabels.slice(0, NUM_CLASSES * NUM_TRAIN_ELEMENTS);
    this.testLabels =
        this.datasetLabels.slice(NUM_CLASSES * NUM_TRAIN_ELEMENTS);
  }

  /**