---
title: "BNNSFilterCreateLayerFullyConnected(_:_:)"
framework: accelerate
role: symbol
role_heading: Function
path: "accelerate/bnnsfiltercreatelayerfullyconnected(_:_:)"
---

# BNNSFilterCreateLayerFullyConnected(_:_:)

Returns a new fully connected layer.

## Declaration

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

## Parameters

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

## Discussion

Discussion Use a fully connected layer to construct each output feature from a linear combination of all input features. Fully connected layers compute the matrix-vector product of a weights matrix and the input vector. Applying a Fully Connected Filter With a 2D Weights Matrix In the case where your input data is a vector and your weights data is a matrix, provide the weights as an m x n row-major matrix where m is the number of fully connected results, and n is the number of items in the input. For example, the following code defines a column matrix input that contains four values, a 3 x 4 weights matrix, and a three-element vector that receives the result: let input: [Float] = [1,                       2,                       3,                       4]

let weightsData: [Float] = [10, 20, 30, 40,                             100, 200, 300, 400,                             1000, 2000, 3000, 4000]

let n = 3

var output = [Float](repeating: .nan,                      count: n) Use the following code to create and apply the fully connected layer: let flags = BNNSNDArrayFlags(0)

weightsData.withUnsafeBufferPointer { weightsPtr in     let inDescription = BNNSNDArrayDescriptor(flags: flags,                                               layout: BNNSDataLayoutVector,                                               size: (4, 0, 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 outDescription = BNNSNDArrayDescriptor(flags: flags,                                                layout: BNNSDataLayoutVector,                                                size: (3, 0, 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 weightsDescription = BNNSNDArrayDescriptor(flags: flags,                                                    layout: BNNSDataLayoutRowMajorMatrix,                                                    size: (4, 3, 0, 0, 0, 0, 0, 0),                                                    stride: (0, 0, 0, 0, 0, 0, 0, 0),                                                    data: UnsafeMutableRawPointer(mutating: weightsPtr.baseAddress),                                                    data_type: .float,                                                    table_data: nil,                                                    table_data_type: .float,                                                    data_scale: 0,                                                    data_bias: 0)

var layerParameters = BNNSLayerParametersFullyConnected(i_desc: inDescription,                                                             w_desc: weightsDescription,                                                             o_desc: outDescription,                                                             bias: BNNSNDArrayDescriptor(),                                                             activation: .identity)          let filter = BNNSFilterCreateLayerFullyConnected(&layerParameters,                                                      nil)     defer {         BNNSFilterDestroy(filter)     }          BNNSFilterApply(filter,                     input,                     &output) } On return, output contains the following values: [300.0,      // 1 * 10 + 2 * 20 + 3 * 30 + 4 * 40  3000.0,     // 1 * 100 + 2 * 200 + 3 * 300 + 4 * 400  30000.0]    // 1 * 1000 + 2 * 2000 + 3 * 3000 + 4 * 4000

## See Also

### Fully connected layers

- [BNNSFullyConnectedLayerParameters](accelerate/bnnsfullyconnectedlayerparameters.md)
- [BNNSFilterCreateFullyConnectedLayer(_:_:_:_:)](accelerate/bnnsfiltercreatefullyconnectedlayer(_:_:_:_:).md)
- [BNNS.FullyConnectedLayer](accelerate/bnns/fullyconnectedlayer.md)
- [BNNSLayerParametersFullyConnected](accelerate/bnnslayerparametersfullyconnected.md)