---
title: "init(sequenceLengths:sortedSequences:featureChannelCount:batchSize:data:)"
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/mlctensor/init(sequencelengths:sortedsequences:featurechannelcount:batchsize:data:)"
---

# init(sequenceLengths:sortedSequences:featureChannelCount:batchSize:data:)

Creates a tensor with the sequence lengths, sorting indicator, number of feature channels, batch size, and data you specify.

## Declaration

```swift
convenience init?(sequenceLengths: [Int], sortedSequences: Bool, featureChannelCount: Int, batchSize: Int, data: MLCTensorData? = nil)
```

## Parameters

- `sequenceLengths`: An array that contains the variable lengths of sequences stored in the tensor.
- `sortedSequences`: A Boolean that indicates whether you provide the sequence lengths sorted in descending order.
- `featureChannelCount`: The number of feature channels.
- `batchSize`: The tensor batch size.
- `data`: The tensor data.

## See Also

### Creating Tensors by Specifying Sequence Lengths

- [init(sequenceLength:featureChannelCount:batchSize:)](mlcompute/mlctensor/init(sequencelength:featurechannelcount:batchsize:).md)
- [init(sequenceLength:featureChannelCount:batchSize:data:)](mlcompute/mlctensor/init(sequencelength:featurechannelcount:batchsize:data:).md)
- [init(sequenceLength:featureChannelCount:batchSize:randomInitializerType:)](mlcompute/mlctensor/init(sequencelength:featurechannelcount:batchsize:randominitializertype:).md)
- [init(sequenceLengths:sortedSequences:featureChannelCount:batchSize:randomInitializerType:)](mlcompute/mlctensor/init(sequencelengths:sortedsequences:featurechannelcount:batchsize:randominitializertype:).md)