function div_(a, b) {
    let $a = (0, _tensorUtilEnv.convertToTensor)(a, "a", "div");
    let $b = (0, _tensorUtilEnv.convertToTensor)(b, "b", "div");
    [$a, $b] = (0, _tensorUtil.makeTypesMatch)($a, $b);
    if ($a.dtype === "int32" && $b.dtype === "int32") return (0, _floorDiv.floorDiv)($a, $b);
    const inputs = {
        a: $a,
        b: $b
    };
    const attrs = {};
    // tslint:disable-next-line: no-unnecessary-type-assertion
    return (0, _engine.ENGINE).runKernel((0, _kernelNames.RealDiv), inputs, attrs);
}
Divides two `tf.Tensor`s element-wise, A / B. Supports broadcasting.

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

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

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

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

@param a The first tensor as the numerator.
@param b The second tensor as the denominator. Must have the same dtype as
`a`.

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