---
title: "BNNSFilterCreateLayerDropout(_:_:)"
framework: accelerate
role: symbol
role_heading: Function
path: "accelerate/bnnsfiltercreatelayerdropout(_:_:)"
---

# BNNSFilterCreateLayerDropout(_:_:)

Returns a new dropout layer.

## Declaration

```swift
func BNNSFilterCreateLayerDropout(_ layer_params: UnsafePointer<BNNSLayerParametersDropout>, _ filter_params: UnsafePointer<BNNSFilterParameters>?) -> BNNSFilter?
```

## Parameters

- `layer_params`: Layer parameters.
- `filter_params`: Filter runtime parameters.

## Discussion

Discussion Use a dropout layer to randomly set the elements—or entire dimensions—of a tensor to 0. The layer scales the unchanged elements by 1 / (1 - rate ). The following code randomly drops half the elements from a 4 x 4 matrix: let input: [Float] = [1, 1, 1, 1,                       1, 1, 1, 1,                       1, 1, 1, 1,                       1, 1, 1, 1]

var output = [Float](repeating: 0,                      count: input.count)

let descriptor = BNNSNDArrayDescriptor(flags: BNNSNDArrayFlags(0),                                        layout: BNNSDataLayoutRowMajorMatrix,                                        size: (4, 4, 0, 0, 0, 0, 0, 0),                                        stride: (0, 0, 0, 0, 0, 0, 0, 0),                                        data: nil,                                        data_type: .float,                                        table_data: nil,                                        table_data_type: .float,                                        data_scale: 0,                                        data_bias: 0)

let control: UInt8 = 0b0000 let rate: Float = 0.5

var dropoutParams = BNNSLayerParametersDropout(i_desc: descriptor,                                                o_desc: descriptor,                                                rate: rate,                                                seed: 0,                                                control: control)

let dropoutFilter = BNNSFilterCreateLayerDropout(&dropoutParams, nil)

BNNSFilterApply(dropoutFilter, input, &output) On return, output contains the following values: [ 2.0, 2.0, 0.0, 0.0,    2.0, 2.0, 0.0, 2.0,    2.0, 0.0, 0.0, 2.0,    0.0, 0.0, 0.0, 2.0 ] Use the control parameter to dropout entire dimensions. For example, setting control to 0b0010 and rate to 0.75 drops three quarters of the columns, and scales the remaining values by 4: [ 0.0, 4.0, 0.0, 0.0,    0.0, 4.0, 0.0, 0.0,    0.0, 4.0, 0.0, 0.0,    0.0, 4.0, 0.0, 0.0 ]

## See Also

### Dropout layers

- [BNNS.DropoutLayer](accelerate/bnns/dropoutlayer.md)
- [BNNSLayerParametersDropout](accelerate/bnnslayerparametersdropout.md)