I get this error message “Can’t compile the student’s code. Error when checking input: expected dense_Dense1_input to have 2 dimensions, but got array with shape (None, 28, 28, 1)” when submitting assignment. This is my complete code:
import {FMnistData} from ‘./fashion-data.js’;
var canvas, ctx, saveButton, clearButton;
var pos = {x:0, y:0};
var rawImage;
var model;
function getModel() {
model = tf.sequential();
model.add(tf.layers.conv2d({inputShape: [28, 28, 1], kernelSize: 3, filters: 8, activation: ‘relu’}));
model.add(tf.layers.maxPooling2d({poolSize: [2, 2]}));
model.add(tf.layers.conv2d({filters: 16, kernelSize: 3, activation: ‘relu’}));
model.add(tf.layers.maxPooling2d({poolSize: [2, 2]}));
model.add(tf.layers.flatten());
model.add(tf.layers.dense({units: 128, activation: ‘relu’}));
model.add(tf.layers.dense({units: 10, activation: ‘softmax’}));
model.compile({optimizer:tf.train.adam(), loss:'categoricalCrossentropy', metrics: ['accuracy']});// YOUR CODE HERE);
return model;
}
async function train(model, data) {
const metrics = // YOUR CODE HERE
[‘loss’,‘val_loss’,‘acc’,‘val_acc’];
const container = // YOUR CODE HERE
{name: 'Model Training', styles: {height: '640px'}};
const fitCallbacks = // YOUR CODE HERE
tfvis.show.fitCallbacks(container, metrics);
const BATCH_SIZE = 512;
const TRAIN_DATA_SIZE = 6000;
const TEST_DATA_SIZE = 1000;
const [trainXs, trainYs] = // YOUR CODE HERE
tf.tidy(() => {
const d = data.nextTrainBatch(TRAIN_DATA_SIZE);
return [
d.xs.reshape([TRAIN_DATA_SIZE, 28, 28, 1]),
d.labels
];
});
const [testXs, testYs] = // YOUR CODE HERE
tf.tidy(() => {
const d = data.nextTestBatch(TEST_DATA_SIZE);
return [
d.xs.reshape([TEST_DATA_SIZE, 28, 28, 1]),
d.labels
];
});
return model.fit(trainXs, trainYs, {
batchSize: BATCH_SIZE,
validationData: [testXs, testYs],
epochs: 10,
shuffle: true,
callbacks: fitCallbacks
});
}
function setPosition(e){
pos.x = e.clientX-100;
pos.y = e.clientY-100;
}
function draw(e) {
if(e.buttons!=1) return;
ctx.beginPath();
ctx.lineWidth = 24;
ctx.lineCap = ‘round’;
ctx.strokeStyle = ‘white’;
ctx.moveTo(pos.x, pos.y);
setPosition(e);
ctx.lineTo(pos.x, pos.y);
ctx.stroke();
rawImage.src = canvas.toDataURL(‘image/png’);
}
function erase() {
ctx.fillStyle = “black”;
ctx.fillRect(0,0,280,280);
}
function save() {
var raw = tf.browser.fromPixels(rawImage,1);
var resized = tf.image.resizeBilinear(raw, [28,28]);
var tensor = resized.expandDims(0);
var prediction = model.predict(tensor);
var pIndex = tf.argMax(prediction, 1).dataSync();
var classNames = ["T-shirt/top", "Trouser", "Pullover",
"Dress", "Coat", "Sandal", "Shirt",
"Sneaker", "Bag", "Ankle boot"];
alert(classNames[pIndex]);
}
function init() {
canvas = document.getElementById(‘canvas’);
rawImage = document.getElementById(‘canvasimg’);
ctx = canvas.getContext(“2d”);
ctx.fillStyle = “black”;
ctx.fillRect(0,0,280,280);
canvas.addEventListener(“mousemove”, draw);
canvas.addEventListener(“mousedown”, setPosition);
canvas.addEventListener(“mouseenter”, setPosition);
saveButton = document.getElementById(‘sb’);
saveButton.addEventListener(“click”, save);
clearButton = document.getElementById(‘cb’);
clearButton.addEventListener(“click”, erase);
}
async function run() {
const data = new FMnistData();
await data.load();
const model = getModel();
tfvis.show.modelSummary({name: ‘Model Architecture’}, model);
await train(model, data);
await model.save(‘downloads://my_model’);
init();
alert(“Training is done, try classifying your drawings!”);
}
document.addEventListener(‘DOMContentLoaded’, run);
Which code is causing the error?