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# MLCBatchNormalizationLayer

A layer that normalizes a batch of inputs.

```
class MLCBatchNormalizationLayer
```

## Topics

### Creating Batch Normalization Layers

[`init(featureChannelCount:mean:variance:beta:gamma:varianceEpsilon:)`](/documentation/MLCompute/MLCBatchNormalizationLayer/init(featureChannelCount:mean:variance:beta:gamma:varianceEpsilon:))

Creates a batch normalization layer with the number of feature channels, tensors, and variance epsilon you specify.

[`init(featureChannelCount:mean:variance:beta:gamma:varianceEpsilon:momentum:)`](/documentation/MLCompute/MLCBatchNormalizationLayer/init(featureChannelCount:mean:variance:beta:gamma:varianceEpsilon:momentum:))

Creates a batch normalization layer with the number of feature channels, tensors, variance epsilon, and momentum you specify.

### Inspecting Batch Normalization Layers

[`featureChannelCount`](/documentation/MLCompute/MLCBatchNormalizationLayer/featureChannelCount)

The number of feature channels.

[`mean`](/documentation/MLCompute/MLCBatchNormalizationLayer/mean)

The mean tensor.

[`variance`](/documentation/MLCompute/MLCBatchNormalizationLayer/variance)

The variance tensor.

[`beta`](/documentation/MLCompute/MLCBatchNormalizationLayer/beta)

The beta tensor.

[`gamma`](/documentation/MLCompute/MLCBatchNormalizationLayer/gamma)

The gamma tensor.

[`varianceEpsilon`](/documentation/MLCompute/MLCBatchNormalizationLayer/varianceEpsilon)

The variance epsilon you use for numerical stability.

[`momentum`](/documentation/MLCompute/MLCBatchNormalizationLayer/momentum)

The value you use for the running mean and variance computation.

[`betaParameter`](/documentation/MLCompute/MLCBatchNormalizationLayer/betaParameter)

The beta tensor parameter you use for optimizer updates.

[`gammaParameter`](/documentation/MLCompute/MLCBatchNormalizationLayer/gammaParameter)

The gamma tensor parameter you use for optimizer updates.


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