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Update C1_W4_Assignment.js #60

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35 changes: 17 additions & 18 deletions C1_Browser-based-TF-JS/W4/assignment/C1_W4_Assignment.js
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Original file line number Diff line number Diff line change
Expand Up @@ -25,20 +25,24 @@ async function train() {
// using ReLu activation functions where applicable.
model = tf.sequential({
layers: [

// YOUR CODE HERE

tf.layers.flatten({inputShape: mobilenet.outputs[0].shape.slice(1)}),
tf.layers.dense({units: 100, activation: 'relu'}),
tf.layers.dense({units: 50, activation: 'relu'}),
tf.layers.dense({units: 5, activation: 'softmax'})
]
});


// Set the optimizer to be tf.train.adam() with a learning rate of 0.0001.
const optimizer = // YOUR CODE HERE
const optimizer = tf.train.adam(0.0001);


// Compile the model using the categoricalCrossentropy loss, and
// the optimizer you defined above.
model.compile(// YOUR CODE HERE);
model.compile({
optimizer: optimizer,
loss: 'categoricalCrossentropy'
});

let loss = 0;
model.fit(dataset.xs, dataset.ys, {
Expand Down Expand Up @@ -71,12 +75,10 @@ function handleButton(elem){
spockSamples++;
document.getElementById("spocksamples").innerText = "Spock samples:" + spockSamples;
break;

// Add a case for lizard samples.
// HINT: Look at the previous cases.

// YOUR CODE HERE

case "4":
lizardSamples++;
document.getElementById("lizardsamples").innerText = "Lizard samples:" + lizardSamples;
break;

}
label = parseInt(elem.id);
Expand Down Expand Up @@ -108,12 +110,9 @@ async function predict() {
case 3:
predictionText = "I see Spock";
break;

// Add a case for lizard samples.
// HINT: Look at the previous cases.

// YOUR CODE HERE

case 4:
predictionText = "I see Lizard";
break;

}
document.getElementById("prediction").innerText = predictionText;
Expand Down Expand Up @@ -154,4 +153,4 @@ async function init(){
}


init();
init();