k = 4;
resource = ResourceObject["MNIST"];
trainingData = ResourceData[resource, "TrainingData"];
trainingSubset = Select[trainingData, Last[#] <= k &];
testData = ResourceData[resource, "TestData"];
testSubset = Select[testData, Last[#] <= k &];
RandomSample[trainingSubset, 8]
trainingImages = Keys[trainingSubset];
meanImage = Image[Mean@Map[ImageData, trainingImages]]

net = NetGraph[{FlattenLayer[], 50, Ramp, 784, Tanh, ReshapeLayer[{1, 28, 28}],
MeanSquaredLossLayer[]}, {1 -> 2 -> 3 -> 4 -> 5 -> 6 -> NetPort["Output"],
6 -> NetPort[7, "Input"], NetPort["Input"] -> NetPort[7, "Target"]},
"Input" -> NetEncoder[{"Image", {28, 28}, "Grayscale", "MeanImage" -> meanImage}],
"Output" -> NetDecoder[{"Image", "Grayscale"}]]

trained = NetTrain[net, <|"Input" -> trainingImages|>, "Loss"];

cm = ClassifierMeasurements[trained, testData]

ClassifierMeasurements: This neural network cannot be converted to a ClassifierFunction.