PReLUBackward¶
General¶
PReLUBackward operation computes gradient for PReLU.
Operation attributes¶
Attribute Name |
Description |
Value Type |
Supported Values |
Required or Optional |
---|---|---|---|---|
Denotes the data format of the input and output data. |
string |
|
Optional |
Broadcasting Rules¶
Only slope tensor supports broadcasting semantics. Slope tensor is uni-directionally broadcasted to \(\src\) if one of the following rules is met:
PyTorch case: slope is 1D tensor and broadcast per channel, length of slope is equal to the length of \(\src\) in channel dimension.
PyTorch case: slope is 1D tensor and broadcast per tensor, length of slope is equal to 1.
Tensorflow case: slope is nD tensor and its dimensions must be equal to the \(\src\) dimensions starting from the second element: \(slope\_shape = input\_forward\_shape[1:]\)
Execution arguments¶
The inputs and outputs must be provided according to below index order when constructing an operation.
Inputs¶
Index |
Argument Name |
Required or Optional |
---|---|---|
0 |
|
Required |
1 |
|
Required |
2 |
|
Required |
Outputs¶
Index |
Argument Name |
Required or Optional |
---|---|---|
0 |
|
Required |
1 |
|
Required |
Supported data types¶
PReLUBackward operation supports the following data type combinations.
Src |
Slope |
Diff_dst |
Diff_src |
Diff_slope |
---|---|---|---|---|
f32 |
f32 |
f32 |
f32 |
f32 |
bf16 |
bf16 |
bf16 |
bf16 |
bf16 |
f16 |
f16 |
f16 |
f16 |
f16 |