Neg#
Neg - 13#
Version
name: Neg (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
Neg takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where each element flipped sign, y = -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) ): Constrain input and output types to signed numeric tensors.
Examples
Differences
0 | 0 | Neg takes one input data (Tensor | Neg takes one input data (Tensor |
1 | 1 | (Tensor | (Tensor |
2 | 2 | the tensor elementwise. | the tensor elementwise. |
3 | 3 | | |
4 | 4 | **Inputs** | **Inputs** |
5 | 5 | | |
6 | 6 | * **X** (heterogeneous) - **T**: | * **X** (heterogeneous) - **T**: |
7 | 7 | Input tensor | Input tensor |
8 | 8 | | |
9 | 9 | **Outputs** | **Outputs** |
10 | 10 | | |
11 | 11 | * **Y** (heterogeneous) - **T**: | * **Y** (heterogeneous) - **T**: |
12 | 12 | Output tensor | Output tensor |
13 | 13 | | |
14 | 14 | **Type Constraints** | **Type Constraints** |
15 | 15 | | |
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 | ): | ): |
25 | 26 | Constrain input and output types to signed numeric tensors. | Constrain input and output types to signed numeric tensors. |
Neg - 6#
Version
name: Neg (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
Neg takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where each element flipped sign, y = -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) ): Constrain input and output types to signed numeric tensors.
Differences
0 | 0 | Neg takes one input data (Tensor | Neg takes one input data (Tensor |
1 | 1 | (Tensor | (Tensor |
2 | 2 | the tensor elementwise. | the tensor elementwise. |
3 | 3 | | |
4 | **Attributes** | ||
5 | | ||
6 | * **consumed_inputs**: | ||
7 | legacy optimization attribute. | ||
8 | | ||
9 | 4 | **Inputs** | **Inputs** |
10 | 5 | | |
11 | 6 | * **X** (heterogeneous) - **T**: | * **X** (heterogeneous) - **T**: |
12 | 7 | Input tensor | Input tensor |
13 | 8 | | |
14 | 9 | **Outputs** | **Outputs** |
15 | 10 | | |
16 | 11 | * **Y** (heterogeneous) - **T**: | * **Y** (heterogeneous) - **T**: |
17 | 12 | Output tensor | Output tensor |
18 | 13 | | |
19 | 14 | **Type Constraints** | **Type Constraints** |
20 | 15 | | |
21 | 16 | * **T** in ( | * **T** in ( |
22 | 17 | tensor(double), | tensor(double), |
23 | 18 | tensor(float), | tensor(float), |
24 | 19 | tensor(float16) | |
20 | tensor(int16), | ||
21 | tensor(int32), | ||
22 | tensor(int64), | ||
23 | tensor(int8) | ||
25 | 24 | ): | ): |
26 | 25 | Constrain input and output types to float tensors. | |
Neg - 1#
Version
name: Neg (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
Neg takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where each element flipped sign, y = -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.