The data is the same data as in the previous chapter: the MNIST dataset. It can be found in the repository for this chapter, and we'll be using a function we wrote in the previous chapter to acquire the data:

// Image holds the pixel intensities of an image.
// 255 is foreground (black), 0 is background (white).
type RawImage []byte

// Label is a digit label in 0 to 9
type Label uint8


const numLabels = 10
const pixelRange = 255

const (
  imageMagic = 0x00000803
  labelMagic = 0x00000801
  Width = 28
  Height = 28
)

func readLabelFile(r io.Reader, e error) (labels []Label, err error) {
  if e != nil {
    return nil, e
  }

  var magic, n int32
  if err = binary.Read(r, binary.BigEndian, &magic); err != nil {
    return nil, err
  }
  if magic != labelMagic {
    return nil, os.ErrInvalid
  }
  if err = binary.Read(r, binary.BigEndian, &n); err != nil {
    return nil, err
  }
  labels = make([]Label, n)
  for i := 0; i < int(n); i++ {
    var l Label
    if err := binary.Read(r, binary.BigEndian, &l); err != nil {
      return nil, err
    }
    labels[i] = l
  }
  return labels, nil
}

func readImageFile(r io.Reader, e error) (imgs []RawImage, err error) {
  if e != nil {
    return nil, e
  }

  var magic, n, nrow, ncol int32
  if err = binary.Read(r, binary.BigEndian, &magic); err != nil {
    return nil, err
  }
  if magic != imageMagic {
    return nil, err /*os.ErrInvalid*/
  }
  if err = binary.Read(r, binary.BigEndian, &n); err != nil {
    return nil, err
  }
  if err = binary.Read(r, binary.BigEndian, &nrow); err != nil {
    return nil, err
  }
  if err = binary.Read(r, binary.BigEndian, &ncol); err != nil {
    return nil, err
  }
  imgs = make([]RawImage, n)
  m := int(nrow * ncol)
  for i := 0; i < int(n); i++ {
    imgs[i] = make(RawImage, m)
    m_, err := io.ReadFull(r, imgs[i])
    if err != nil {
      return nil, err
    }
    if m_ != int(m) {
      return nil, os.ErrInvalid
    }
  }
 return imgs, nil