Upsample - 9 vs 10¶
- Upsample9 → Upsample10 +0 -0
Upsample9 → Upsample10
RENAMED
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@@ -1 +1 @@
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1
1
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Upsample the input tensor.
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2
2
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Each dimension value of the output tensor is:
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3
3
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output_dimension = floor(input_dimension * scale).
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4
4
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**Attributes**
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5
5
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* **mode**:
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6
6
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Two interpolation modes: nearest (default), and linear (including
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7
7
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bilinear, trilinear, etc)
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8
8
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**Inputs**
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9
9
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* **X** (heterogeneous) - **T**:
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10
10
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N-D tensor
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11
11
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* **scales** (heterogeneous) - **tensor(float)**:
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12
12
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The scale array along each dimension. It takes value greater than or
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13
13
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equal to 1. The number of elements of 'scales' should be the same as
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14
14
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the rank of input 'X'.
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15
15
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**Outputs**
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16
16
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* **Y** (heterogeneous) - **T**:
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17
17
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N-D tensor after resizing
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18
18
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**Type Constraints**
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19
19
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* **T** in (
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20
20
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tensor(bool),
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21
21
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tensor(complex128),
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22
22
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tensor(complex64),
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23
23
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tensor(double),
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24
24
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tensor(float),
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25
25
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tensor(float16),
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26
26
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tensor(int16),
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27
27
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tensor(int32),
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28
28
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tensor(int64),
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29
29
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tensor(int8),
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30
30
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tensor(string),
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31
31
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tensor(uint16),
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32
32
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tensor(uint32),
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33
33
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tensor(uint64),
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34
34
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tensor(uint8)
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35
35
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):
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36
36
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Constrain input 'X' and output 'Y' to all tensor types.
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