tf.repeat

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Repeat elements of input.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.repeat

tf.repeat(
    input, repeats, axis=None, name=None
)

See also tf.concat, tf.stack, tf.tile.

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)>