Abs#
Abs - 13#
Version
name: Abs (GitHub)
domain: main
since_version: 13
function: False
support_level: SupportType.COMMON
shape inference: True
This version of the operator has been available since version 13.
Summary
Absolute takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the absolute is, y = abs(x), is applied to the tensor elementwise.
Inputs
X (heterogeneous) - T: Input tensor
Outputs
Y (heterogeneous) - T: Output tensor
Type Constraints
T in ( tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) ): Constrain input and output types to all numeric tensors.
Examples
Differences
0 | 0 | Absolute takes one input data (Tensor | Absolute takes one input data (Tensor |
1 | 1 | (Tensor | (Tensor |
2 | 2 | the tensor elementwise. | the tensor elementwise. |
3 | 3 |
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4 | 4 | **Inputs** | **Inputs** |
5 | 5 |
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6 | 6 | * **X** (heterogeneous) - **T**: | * **X** (heterogeneous) - **T**: |
7 | 7 | Input tensor | Input tensor |
8 | 8 |
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9 | 9 | **Outputs** | **Outputs** |
10 | 10 |
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11 | 11 | * **Y** (heterogeneous) - **T**: | * **Y** (heterogeneous) - **T**: |
12 | 12 | Output tensor | Output tensor |
13 | 13 |
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14 | 14 | **Type Constraints** | **Type Constraints** |
15 | 15 |
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16 | 16 | * **T** in ( | * **T** in ( |
17 | tensor(bfloat16), | ||
17 | 18 | tensor(double), | tensor(double), |
18 | 19 | tensor(float), | tensor(float), |
19 | 20 | tensor(float16), | tensor(float16), |
20 | 21 | tensor(int16), | tensor(int16), |
21 | 22 | tensor(int32), | tensor(int32), |
22 | 23 | tensor(int64), | tensor(int64), |
23 | 24 | tensor(int8), | tensor(int8), |
24 | 25 | tensor(uint16), | tensor(uint16), |
25 | 26 | tensor(uint32), | tensor(uint32), |
26 | 27 | tensor(uint64), | tensor(uint64), |
27 | 28 | tensor(uint8) | tensor(uint8) |
28 | 29 | ): | ): |
29 | 30 | Constrain input and output types to all numeric tensors. | Constrain input and output types to all numeric tensors. |
Abs - 6#
Version
name: Abs (GitHub)
domain: main
since_version: 6
function: False
support_level: SupportType.COMMON
shape inference: True
This version of the operator has been available since version 6.
Summary
Absolute takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the absolute is, y = abs(x), is applied to the tensor elementwise.
Inputs
X (heterogeneous) - T: Input tensor
Outputs
Y (heterogeneous) - T: Output tensor
Type Constraints
T in ( tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) ): Constrain input and output types to all numeric tensors.
Differences
0 | 0 | Absolute takes one input data (Tensor | Absolute takes one input data (Tensor |
1 | 1 | (Tensor | (Tensor |
2 | 2 | the tensor elementwise. | the tensor elementwise. |
3 | 3 |
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4 | **Attributes** | ||
5 |
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6 | * **consumed_inputs**: | ||
7 | legacy optimization attribute. | ||
8 |
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9 | 4 | **Inputs** | **Inputs** |
10 | 5 |
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11 | 6 | * **X** (heterogeneous) - **T**: | * **X** (heterogeneous) - **T**: |
12 | 7 | Input tensor | Input tensor |
13 | 8 |
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14 | 9 | **Outputs** | **Outputs** |
15 | 10 |
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16 | 11 | * **Y** (heterogeneous) - **T**: | * **Y** (heterogeneous) - **T**: |
17 | 12 | Output tensor | Output tensor |
18 | 13 |
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19 | 14 | **Type Constraints** | **Type Constraints** |
20 | 15 |
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21 | 16 | * **T** in ( | * **T** in ( |
22 | 17 | tensor(double), | tensor(double), |
23 | 18 | tensor(float), | tensor(float), |
24 | 19 | tensor(float16) |
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20 | tensor(int16), | ||
21 | tensor(int32), | ||
22 | tensor(int64), | ||
23 | tensor(int8), | ||
24 | tensor(uint16), | ||
25 | tensor(uint32), | ||
26 | tensor(uint64), | ||
27 | tensor(uint8) | ||
25 | 28 | ): | ): |
26 | 29 | Constrain input and output types to float tensors. |
|
Abs - 1#
Version
name: Abs (GitHub)
domain: main
since_version: 1
function: False
support_level: SupportType.COMMON
shape inference: False
This version of the operator has been available since version 1.
Summary
Absolute takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the absolute is, y = abs(x), is applied to the tensor elementwise.
Attributes
consumed_inputs: legacy optimization attribute.
Inputs
X (heterogeneous) - T: Input tensor
Outputs
Y (heterogeneous) - T: Output tensor
Type Constraints
T in ( tensor(double), tensor(float), tensor(float16) ): Constrain input and output types to float tensors.