Intel® oneAPI Deep Neural Network Developer Guide and Reference
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BatchNormForwardTraining
General
BatchNormForwardTraining operation performs batch normalization at training mode.
Mean and variance are computed at runtime, the following formulas are used:
,
.
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 f32 value |
Required |
|
A number to be used to calculate running mean and running variance. |
f32 |
A positive f32 value |
Optional |
|
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 |
mean |
Required |
2 |
variance ( |
Required |
3 |
gamma |
Optional |
4 |
beta |
Optional |
Outputs
Index |
Argument Name |
Required or Optional |
---|---|---|
0 |
dst |
Required |
1 |
running_mean |
Required |
2 |
running_variance |
Required |
3 |
batch_mean |
Required |
4 |
batch_variance |
Required |
Supported data types
BatchNormInference operation supports the following data type combinations.
Src / Dst |
Gamma / Beta / Mean / Variance / Batch_mean / Batch_variance / Running_mean / Running_variance |
---|---|
f32 |
f32 |
bf16 |
f32, bf16 |
f16 |
f32 |