Intel® oneAPI Deep Neural Network Developer Guide and Reference
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BatchNormInference
General
The formula is the same as Batch Normalization primitive like below.

where
are required scale and shift for a channel,
are mean and variance for a channel, and
is a constant to improve numerical stability.
Operation attributes
Attribute Name |
Description |
Value Type |
Supported Values |
Required or Optional |
---|---|---|---|---|
A number to be added to the variance to avoid division by zero. |
f32 |
A positive float value |
Required |
|
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 |
gamma |
Required |
2 |
beta |
Required |
3 |
mean |
Required |
4 |
variance ( |
Required |
Outputs
Index |
Argument Name |
Required or Optional |
---|---|---|
0 |
dst |
Required |
Supported data types
BatchNormInference operation supports the following data type combinations.
Src / Dst |
Gamma / Beta / Mean / Variance |
---|---|
f32 |
f32 |
bf16 |
f32, bf16 |
f16 |
f32 |