Testing

Of course we'd have to test our neural network.

First we load up the testing data:

testImgs, err := readImageFile(os.Open("t10k-images.idx3-ubyte"))
if err != nil {
   log.Fatal(err)
}

testlabels, err := readLabelFile(os.Open("t10k-labels.idx1-ubyte"))
  if err != nil {
     log.Fatal(err)
  }

testData := prepareX(testImgs)
testLbl := prepareY(testlabels)
shape := testData.Shape()
visualize(testData, 10, 10, "testData.png")

In the last line, we visualize the test data to ensure that we do indeed have the correct dataset:

Then we have the main testing loop. Do observe that it's extremely similar to the training loop - because it's the same neural network!

var correct, total float32
numExamples = shape[0]
batches = numExamples / bs
for b := 0; b < batches; b++ {
    start := b * bs
    end := start + bs
    if start >= numExamples {
   ...