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# tf.repeat

Repeat elements of `input`.

`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.

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)>`
```
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