PReLUBackward#
PReLUBackward operation computes gradient for PReLU.
Operation Attributes#
|
Description |
Value Type |
|
|
---|---|---|---|---|
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:
1: PyTorch case: slope is 1D tensor and broadcast per channel, length of slope is equal to the length of src in channel dimension.
2: PyTorch case: slope is 1D tensor and broadcast per tensor, length of slope is equal to 1.
3: 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 the 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 |