function tensor5d(values, shape, dtype) {
    (0, _util.assertNonNull)(values);
    if (shape != null && shape.length !== 5) throw new Error("tensor5d() requires shape to have five numbers");
    const inferredShape = (0, _tensorUtilEnv.inferShape)(values, dtype);
    if (inferredShape.length !== 5 && inferredShape.length !== 1) throw new Error("tensor5d() requires values to be number[][][][][] or flat/TypedArray");
    if (inferredShape.length === 1 && shape == null) throw new Error("tensor5d() requires shape to be provided when `values` are a flat array");
    return (0, _tensorOpsUtil.makeTensor)(values, shape, inferredShape, dtype);
}
Creates rank-5 `tf.Tensor` with the provided values, shape and dtype.

The same functionality can be achieved with `tf.tensor`, but in general
we recommend using `tf.tensor5d` as it makes the code more readable.

 ```js
// Pass a nested array.
tf.tensor5d([[[[[1],[2]],[[3],[4]]],[[[5],[6]],[[7],[8]]]]]).print();
```
```js
// Pass a flat array and specify a shape.
tf.tensor5d([1, 2, 3, 4, 5, 6, 7, 8], [1, 2, 2, 2, 1]).print();
```

@param values The values of the tensor. Can be nested array of numbers,
    or a flat array, or a `TypedArray`.
@param shape The shape of the tensor. Optional. If not provided,
  it is inferred from `values`.
@param dtype The data type.

@doc {heading: 'Tensors', subheading: 'Creation'}