Function loadImages

quantization/data_mnist.js:89–126

(baseURL, destDir, filename)

}

async function loadImages(baseURL, destDir, filename) {
  const buffer =
      await fetchOnceAndSaveToDiskWithBuffer(baseURL, destDir, filename);

  const headerBytes = IMAGE_HEADER_BYTES;
  const recordBytes = IMAGE_HEIGHT * IMAGE_WIDTH;

  const headerValues = loadHeaderValues(buffer, headerBytes);
  tf.util.assert(
      headerValues[0] === IMAGE_HEADER_MAGIC_NUM,
      () => `Image file header doesn't match expected magic num.`);
  tf.util.assert(
      headerValues[2] === IMAGE_HEIGHT,
      () => `Value in file header (${headerValues[2]}) doesn't ` +
      `match the expected image height ${IMAGE_HEIGHT}`);
  tf.util.assert(
      headerValues[3] === IMAGE_WIDTH,
      () => `Value in file header (${headerValues[3]}) doesn't ` +
      `match the expected image height ${IMAGE_WIDTH}`);

  const images = [];
  let index = headerBytes;
  while (index < buffer.byteLength) {
    const array = new Float32Array(recordBytes);
    for (let i = 0; i < recordBytes; i++) {
      // Normalize the pixel values into the 0-1 interval, from
      // the original 0-255 interval.
      array[i] = buffer.readUInt8(index++) / 255;
    }
    images.push(array);
  }

  tf.util.assert(
      images.length === headerValues[1],
      () => `Actual images length (${images.length} doesn't match ` +
      `value in header (${headerValues[1]})`);
  return images;
}

async function loadLabels(baseURL, destDir, filename) {
  const buffer =