Tile - 6 vs 13#
Next section compares an older to a newer version of the same operator after both definition are converted into markdown text. Green means an addition to the newer version, red means a deletion. Anything else is unchanged.
- Tile6 → Tile13 +0 -1
Tile6 → Tile13
RENAMED
|
@@ -1 +1 @@
|
|
|
1
1
|
Constructs a tensor by tiling a given tensor.
|
|
2
2
|
This is the same as function tile in Numpy, but no broadcast.
|
|
3
3
|
For example A = [[1, 2], [3, 4]], B = [1, 2], tile(A, B) = [[1, 2, 1, 2], [3, 4, 3, 4]]
|
|
4
4
|
**Inputs**
|
|
5
5
|
* **input** (heterogeneous) - **T**:
|
|
6
6
|
Input tensor of any shape.
|
|
7
7
|
* **repeats** (heterogeneous) - **T1**:
|
|
8
8
|
1D int64 tensor of the same length as input's dimension number,
|
|
9
9
|
includes numbers of repeated copies along input's dimensions.
|
|
10
10
|
**Outputs**
|
|
11
11
|
* **output** (heterogeneous) - **T**:
|
|
12
12
|
Output tensor of the same dimensions and type as tensor input.
|
|
13
13
|
output_dim[i] = input_dim[i] * repeats[i]
|
|
14
14
|
**Type Constraints**
|
|
15
15
|
* **T** in (
|
|
16
|
-
tensor(bfloat16),
|
|
17
16
|
tensor(bool),
|
|
18
17
|
tensor(complex128),
|
|
19
18
|
tensor(complex64),
|
|
20
19
|
tensor(double),
|
|
21
20
|
tensor(float),
|
|
22
21
|
tensor(float16),
|
|
23
22
|
tensor(int16),
|
|
24
23
|
tensor(int32),
|
|
25
24
|
tensor(int64),
|
|
26
25
|
tensor(int8),
|
|
27
26
|
tensor(string),
|
|
28
27
|
tensor(uint16),
|
|
29
28
|
tensor(uint32),
|
|
30
29
|
tensor(uint64),
|
|
31
30
|
tensor(uint8)
|
|
32
31
|
):
|
|
33
32
|
Constrain input and output types to all tensor types.
|
|
34
33
|
* **T1** in (
|
|
35
34
|
tensor(int64)
|
|
36
35
|
):
|
|
37
36
|
Constrain repeat's type to int64 tensors.
|