Repeat elements of input
.
meridian
.
backend
.
repeat
(
input
,
repeats
,
axis
=
None
,
name
=
None
)
See also tf.concat
, tf.stack
, tf.tile
.
Args
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.An int. The axis along which to repeat values. By default, (axis=None),
use the flattened input array, and return a flat output array.
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
)
>
