function pow_(base, exp) {
    let $base = (0, _tensorUtilEnv.convertToTensor)(base, "base", "pow");
    let $exp = (0, _tensorUtilEnv.convertToTensor)(exp, "exp", "pow");
    [$base, $exp] = (0, _tensorUtil.makeTypesMatch)($base, $exp);
    const inputs = {
        a: $base,
        b: $exp
    };
    return (0, _engine.ENGINE).runKernel((0, _kernelNames.Pow), inputs);
}
Computes the power of one `tf.Tensor` to another. Supports broadcasting.

Given a `tf.Tensor` x and a `tf.Tensor` y, this operation computes x^y for
corresponding elements in x and y. The result's dtype will be the upcasted
type of the `base` and `exp` dtypes.

```js
const a = tf.tensor([[2, 3], [4, 5]])
const b = tf.tensor([[1, 2], [3, 0]]).toInt();

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

```js
const a = tf.tensor([[1, 2], [3, 4]])
const b = tf.tensor(2).toInt();

a.pow(b).print();  // or tf.pow(a, b)
```
We also expose `powStrict` which has the same signature as this op and
asserts that `base` and `exp` are the same shape (does not broadcast).

@param base The base `tf.Tensor` to pow element-wise.
@param exp The exponent `tf.Tensor` to pow element-wise.

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