Intel® oneAPI Deep Neural Network Developer Guide and Reference
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  |