# Source code for mars.tensor.base.tile

```
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright 1999-2021 Alibaba Group Holding Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
[docs]def tile(A, reps):
"""
Construct a tensor by repeating A the number of times given by reps.
If `reps` has length ``d``, the result will have dimension of
``max(d, A.ndim)``.
If ``A.ndim < d``, `A` is promoted to be d-dimensional by prepending new
axes. So a shape (3,) array is promoted to (1, 3) for 2-D replication,
or shape (1, 1, 3) for 3-D replication. If this is not the desired
behavior, promote `A` to d-dimensions manually before calling this
function.
If ``A.ndim > d``, `reps` is promoted to `A`.ndim by pre-pending 1's to it.
Thus for an `A` of shape (2, 3, 4, 5), a `reps` of (2, 2) is treated as
(1, 1, 2, 2).
Note : Although tile may be used for broadcasting, it is strongly
recommended to use Mars' broadcasting operations and functions.
Parameters
----------
A : array_like
The input tensor.
reps : array_like
The number of repetitions of `A` along each axis.
Returns
-------
c : Tensor
The tiled output tensor.
See Also
--------
repeat : Repeat elements of a tensor.
broadcast_to : Broadcast a tensor to a new shape
Examples
--------
>>> import mars.tensor as mt
>>> a = mt.array([0, 1, 2])
>>> mt.tile(a, 2).execute()
array([0, 1, 2, 0, 1, 2])
>>> mt.tile(a, (2, 2)).execute()
array([[0, 1, 2, 0, 1, 2],
[0, 1, 2, 0, 1, 2]])
>>> mt.tile(a, (2, 1, 2)).execute()
array([[[0, 1, 2, 0, 1, 2]],
[[0, 1, 2, 0, 1, 2]]])
>>> b = mt.array([[1, 2], [3, 4]])
>>> mt.tile(b, 2).execute()
array([[1, 2, 1, 2],
[3, 4, 3, 4]])
>>> mt.tile(b, (2, 1)).execute()
array([[1, 2],
[3, 4],
[1, 2],
[3, 4]])
>>> c = mt.array([1,2,3,4])
>>> mt.tile(c,(4,1)).execute()
array([[1, 2, 3, 4],
[1, 2, 3, 4],
[1, 2, 3, 4],
[1, 2, 3, 4]])
"""
from ..merge import concatenate
try:
tup = tuple(reps)
except TypeError:
tup = (reps,)
d = len(tup)
if A.ndim < d:
A = A[tuple(np.newaxis for _ in range(d - A.ndim))]
elif A.ndim > d:
tup = (1,) * (A.ndim - d) + tup
a = A
for axis, rep in enumerate(tup):
if rep == 0:
slc = (slice(None),) * axis + (slice(0),)
a = a[slc]
elif rep < 0:
raise ValueError("negative dimensions are not allowed")
elif rep > 1:
a = concatenate([a] * rep, axis=axis)
return a
```