/TensorFlow 2.4

# tf.repeat

Repeat elements of `input`.

Args
`input` An `N`-dimensional Tensor.
`repeats` An 1-D `int` Tensor. The number of repetitions for each element. repeats is broadcasted to fit the shape of the given axis. `len(repeats)` must equal `input.shape[axis]` if axis is not None.
`axis` An int. The axis along which to repeat values. By default (axis=None), use the flattened input array, and return a flat output array.
`name` A name for the operation.
Returns
A Tensor which has the same shape as `input`, except along the given axis. If axis is None then the output array is flattened to match the flattened input array.

#### Example usage:

```repeat(['a', 'b', 'c'], repeats=[3, 0, 2], axis=0)
<tf.Tensor: shape=(5,), dtype=string,
numpy=array([b'a', b'a', b'a', b'c', b'c'], dtype=object)>
```
```repeat([[1, 2], [3, 4]], repeats=[2, 3], axis=0)
<tf.Tensor: shape=(5, 2), dtype=int32, numpy=
array([[1, 2],
[1, 2],
[3, 4],
[3, 4],
[3, 4]], dtype=int32)>
```
```repeat([[1, 2], [3, 4]], repeats=[2, 3], axis=1)
<tf.Tensor: shape=(2, 5), dtype=int32, numpy=
array([[1, 1, 2, 2, 2],
[3, 3, 4, 4, 4]], dtype=int32)>
```
```repeat(3, repeats=4)
<tf.Tensor: shape=(4,), dtype=int32, numpy=array([3, 3, 3, 3], dtype=int32)>
```
```repeat([[1,2], [3,4]], repeats=2)
<tf.Tensor: shape=(8,), dtype=int32,
numpy=array([1, 1, 2, 2, 3, 3, 4, 4], dtype=int32)>
```