Intel® oneAPI Deep Neural Network Developer Guide and Reference
A newer version of this document is available. Customers should click here to go to the newest version.
ReduceMean
General
ReduceMean operation performs the reduction with finding the arithmetic mean on a given src data along dimensions specified by axes.
Take channel axis = 0 and keep_dims = True as an example:
 
   Operation attributes
Attribute Name  |  
        Description  |  
        Value Type  |  
        Supported Values  |  
        Required or Optional  |  
       
|---|---|---|---|---|
Specify indices of src tensor, along which the reduction is performed. If axes is a list, reduce over all of them. If axes is empty, corresponds to the identity operation. If axes contains all dimensions of src tensor, a single reduction value is calculated for the entire src tensor. Exactly one of attribute axes and the second input tensor axes should be available.  |  
        s64  |  
        A s64 list values which is in the range of [-r, r-1] where r = rank(src). Empty list(default)  |  
        Optional  |  
       |
If set to true it holds axes that are used for reduction. For each such axes, dst dimension is equal to 1.  |  
        bool  |  
        true , false (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  |  
        axes  |  
        Optional  |  
       
Outputs
Index  |  
        Argument Name  |  
        Required or Optional  |  
       
|---|---|---|
0  |  
        dst  |  
        Required  |  
       
Supported data types
ReduceMean operation supports the following data type combinations.
Src  |  
        Dst  |  
        Axes  |  
       
|---|---|---|
f32  |  
        f32  |  
        s32  |  
       
bf16  |  
        bf16  |  
        s32  |  
       
f16  |  
        f16  |  
        s32  |