tf.tile

Constructs a tensor by tiling a given tensor.

View aliases

Compat aliases for migration

tf.compat.v1.manip.tile, tf.compat.v1.tile

tf.tile(
    input: Annotated[Any, TV_Tile_T],
    multiples: Annotated[Any, TV_Tile_Tmultiples],
    name=None
) -> Annotated[Any, TV_Tile_T]

Used in the notebooks

Used in the guide	Used in the tutorials
Better performance with the tf.data API Ragged tensors Understanding masking & padding	Time series forecasting Calculate gradients Quantum data Parametrized Quantum Circuits for Reinforcement Learning A Tutorial on Multi-Armed Bandits with Per-Arm Features

This operation creates a new tensor by replicating input multiples times. The output tensor's i'th dimension has input.dims(i) * multiples[i] elements, and the values of input are replicated multiples[i] times along the 'i'th dimension. For example, tiling [a b c d] by [2] produces [a b c d a b c d].

a = tf.constant([[1,2,3],[4,5,6]], tf.int32)
b = tf.constant([1,2], tf.int32)
tf.tile(a, b)
<tf.Tensor: shape=(2, 6), dtype=int32, numpy=
array([[1, 2, 3, 1, 2, 3],
       [4, 5, 6, 4, 5, 6]], dtype=int32)>
c = tf.constant([2,1], tf.int32)
tf.tile(a, c)
<tf.Tensor: shape=(4, 3), dtype=int32, numpy=
array([[1, 2, 3],
       [4, 5, 6],
       [1, 2, 3],
       [4, 5, 6]], dtype=int32)>
d = tf.constant([2,2], tf.int32)
tf.tile(a, d)
<tf.Tensor: shape=(4, 6), dtype=int32, numpy=
array([[1, 2, 3, 1, 2, 3],
       [4, 5, 6, 4, 5, 6],
       [1, 2, 3, 1, 2, 3],
       [4, 5, 6, 4, 5, 6]], dtype=int32)>

Args
`input`	A `Tensor`. Can be of any rank.
`multiples`	A `Tensor`. Must be one of the following types: `int32`, `int64`. 1-D. Length must be the same as the number of dimensions in `input`
`name`	A name for the operation (optional).

Returns
A `Tensor`. Has the same type as `input`.

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Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/tile