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tf.repeat

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Repeat elements of input

Aliases:

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

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.

Examples:

>>> repeat(['a', 'b', 'c'], repeats=[3, 0, 2], axis=0)
['a', 'a', 'a', 'c', 'c']
>>> repeat([[1, 2], [3, 4]], repeats=[2, 3], axis=0)
[[1, 2], [1, 2], [3, 4], [3, 4], [3, 4]]
>>> repeat([[1, 2], [3, 4]], repeats=[2, 3], axis=1)
[[1, 1, 2, 2, 2], [3, 3, 4, 4, 4]]
>>> repeat(3, repeats=4)
[3, 3, 3, 3]
>>> repeat([[1,2], [3,4]], repeats=2)
[1, 1, 2, 2, 3, 3, 4, 4]