---
title: "init(featureChannelCount:mean:variance:beta:gamma:varianceEpsilon:momentum:)"
framework: ML Compute
role: symbol
role_heading: Initializer
platforms: [iOS 14.0+, iPadOS 14.0+, Mac Catalyst 14.0+, macOS 11.0+, tvOS 14.0+]
path: "mlcompute/mlcbatchnormalizationlayer/init(featurechannelcount:mean:variance:beta:gamma:varianceepsilon:momentum:)"
---

# 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.

## Declaration

```swift
convenience init?(featureChannelCount: Int, mean: MLCTensor, variance: MLCTensor, beta: MLCTensor?, gamma: MLCTensor?, varianceEpsilon: Float, momentum: Float)
```

## Parameters

- `featureChannelCount`: The number of feature channels.
- `mean`: The mean tensor.
- `variance`: The variance tensor.
- `beta`: The beta tensor.
- `gamma`: The gamma tensor.
- `varianceEpsilon`: The variance epsilon you use for numerical stability.
- `momentum`: The momentum value for the running mean and variance computation.

## See Also

### Creating Batch Normalization Layers

- [init(featureChannelCount:mean:variance:beta:gamma:varianceEpsilon:)](mlcompute/mlcbatchnormalizationlayer/init(featurechannelcount:mean:variance:beta:gamma:varianceepsilon:).md)