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# init(_:dataLayout:stride:)

Returns a new shape with the specified size, data layout, and stride.

```
init(_ size: [Int], dataLayout: BNNS.DataLayout? = nil, stride: [Int]? = nil)
```

## Parameters

`size`

An array that specifies the number of values in each dimension.

`dataLayout`

The number of dimensions of the array, and how it stores the data.

`stride`

An array specifying the increment, in values, between a value and the next in each dimension.

## Discussion

Pass `nil` to `dataLayout` to have `init(size:dataLayout:stride:)` return a shape with the default layout for the rank that’s equal to the count of `size`. The default layouts for each dimensionality are:

- 1D: [`BNNS.DataLayout.vector`](/documentation/Accelerate/BNNS/DataLayout/vector)
- 2D: [`BNNS.DataLayout.matrixFirstMajor`](/documentation/Accelerate/BNNS/DataLayout/matrixFirstMajor)
- 3D: [`BNNS.DataLayout.tensor3DFirstMajor`](/documentation/Accelerate/BNNS/DataLayout/tensor3DFirstMajor)
- 4D: [`BNNS.DataLayout.tensor4DFirstMajor`](/documentation/Accelerate/BNNS/DataLayout/tensor4DFirstMajor)
- 5D: [`BNNS.DataLayout.tensor5DFirstMajor`](/documentation/Accelerate/BNNS/DataLayout/tensor5DFirstMajor)
- 6D: [`BNNS.DataLayout.tensor6DFirstMajor`](/documentation/Accelerate/BNNS/DataLayout/tensor6DFirstMajor)
- 7D: [`BNNS.DataLayout.tensor7DFirstMajor`](/documentation/Accelerate/BNNS/DataLayout/tensor7DFirstMajor)
- 8D: [`BNNS.DataLayout.tensor8DFirstMajor`](/documentation/Accelerate/BNNS/DataLayout/tensor8DFirstMajor)

This initializer interprets a stride value of `0` to mean that values are contiguous for that axis.

---

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