---
title: "transposed(permutation:)"
framework: coreml
role: symbol
role_heading: Instance Method
path: "coreml/mlshapedarrayslice/transposed(permutation:)"
---

# transposed(permutation:)

Returns a new transposed shaped array using a custom permutation.

## Declaration

```swift
func transposed(permutation axes: [Int]) -> MLShapedArraySlice<Scalar>
```

## Discussion

Discussion Use this method to convert, for example, the image data layout from [C, H, W] to [C, W, H], where C is channel, W is width, and H is height. // The source tensor has 3 channels, 128 x 64 image in [C, H, W] layout. let imageCHW = MLShapedArray<Int32>(scalars: pixelValues,                                     shape: [3, 64, 128]) // Slice for the first two channels. let imageSliceCHW = imageCHW[0..<2]

// Transpose. let imageSliceCWH = imageSliceCHW.transposed(permutation: [0, 2, 1]) imageSliceCHW.shape // [2, 64, 128] imageSliceCWH.shape // [2, 128, 64] The shape (shape_out) is transposed from the input shape (shape_in) as follows. shape_out[i]   == permutation.map { shape_in[$0] } The scalar value of the output shaped array (array_out) is related to the input shaped array (array_in) as follows. array_out(scalarAt: permutation.map { indices[$0] })   == array_in[scalarAt: indices]]

## See Also

### Shaping the array slice

- [changingLayout(to:)](coreml/mlshapedarrayslice/changinglayout(to:).md)
- [expandingShape(at:)](coreml/mlshapedarrayslice/expandingshape(at:).md)
- [reshaped(to:)](coreml/mlshapedarrayslice/reshaped(to:).md)
- [squeezingShape()](coreml/mlshapedarrayslice/squeezingshape().md)
- [transposed()](coreml/mlshapedarrayslice/transposed().md)