BatchNormTrainingBackward

General

BatchNormTrainingBackward operation calculated the gradients of input tensors.

Operation attributes

Attribute Name	Description	Value Type	Supported Values	Required or Optional
epsilon	A number to be added to the variance to avoid division by zero.	f32	A positive float value	Required
data_format	Controls how to interpret the shape of src and dst .	string	NCX , NXC (default)	Optional

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	src	Required
1	diff_dst	Required
2	mean	Required
3	variance ( \(\sigma^2\) )	Required
4	gamma	Optional

Outputs

Index	Argument Name	Required or Optional
0	diff_src	Required
1	diff_gamma	Optional
2	diff_beta	Optional

Note

diff_gamma and diff_beta should be either both provided or neither provided. If neither provided, the input gamma will be ignored.

Supported data types

BatchNormTrainingBackward operation supports the following data type combinations.

Src / Diff_dst / Diff_src	Mean / Variance / Gamma / Diff_gamma / Diff_beta
f32	f32
bf16	f32, bf16
f16	f32

Implementation Notes

BatchNormTrainingBackward supports in-place operations, meaning that diff_dst can be used as both input and output (diff_src). In case of in-place operation, the original diff_dst data will be overwritten. Use in-place operations whenever possible for performance.