function squaredDifference_(a, b) {
    let $a = (0, _tensorUtilEnv.convertToTensor)(a, "a", "squaredDifference");
    let $b = (0, _tensorUtilEnv.convertToTensor)(b, "b", "squaredDifference");
    [$a, $b] = (0, _tensorUtil.makeTypesMatch)($a, $b);
    (0, _broadcastUtil.assertAndGetBroadcastShape)($a.shape, $b.shape);
    const inputs = {
        a: $a,
        b: $b
    };
    const attrs = {};
    return (0, _engine.ENGINE).runKernel((0, _kernelNames.SquaredDifference), inputs, attrs);
}
Returns (a - b) * (a - b) element-wise.
Supports broadcasting.

```js
const a = tf.tensor1d([1, 4, 3, 16]);
const b = tf.tensor1d([1, 2, 9, 4]);

a.squaredDifference(b).print();  // or tf.squaredDifference(a, b)
```

```js
// Broadcast squared difference  a with b.
const a = tf.tensor1d([2, 4, 6, 8]);
const b = tf.scalar(5);

a.squaredDifference(b).print();  // or tf.squaredDifference(a, b)
```

@param a The first tensor.
@param b The second tensor. Must have the same type as `a`.

@doc {heading: 'Operations', subheading: 'Arithmetic'}