# PReLUBackward¶

## General¶

PReLUBackward operation computes gradient for PReLU.

## Operation attributes¶

Attribute Name

Descr

data_format

Denotes the data format of the input and output data.

string

NCX , NXC (default)

Optional

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 below index order when constructing an operation.

### Inputs¶

Index

Argu

0

src

Required

1

slope

Required

2

diff_dst

Required

### Outputs¶

Index

Argu

0

diff_src

Required

1

diff_slope

Required

## Supported data types¶

PReLUBackward operation supports the following data type combinations.

Src

Slope

Diff_dst

f32

f32

f32

f32

f32

bf16

bf16

bf16

bf16

bf16

f16

f16

f16

f16

f16