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