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  "framework" : "Accelerate",
  "identifier" : "/documentation/Accelerate/BNNS/FullyConnectedLayer/sparsify(batchSize:inputLayout:inputDenseShape:inputValues:output:sparseParameters:workspace:filterParameters:)",
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# sparsify(batchSize:inputLayout:inputDenseShape:inputValues:output:sparseParameters:workspace:filterParameters:)

Converts a sparse tensor from a standardized sparse layout to a device-specific sparse layout that Fully Connected uses.

```
static func sparsify(batchSize: Int = 1, inputLayout layout: BNNS.SparseLayout, inputDenseShape: BNNSNDArrayDescriptor, inputValues: BNNSNDArrayDescriptor, output: inout BNNSNDArrayDescriptor, sparseParameters: BNNS.SparseParameters? = nil, workspace: UnsafeMutableRawBufferPointer? = nil, filterParameters: BNNSFilterParameters? = nil) throws
```

## Parameters

`batchSize`

The number of input-output pairs to process.

`layout`

The layout and nonzero indices of the sparse input.

`inputDenseShape`

The dense shape of the sparse 2D input.

`inputValues`

A 1D array descriptor that contains the nonzero input values.

`output`

The destination array descriptor that contains the output-device-optimized BNNS Sparse Fully Connected weights.

`sparseParameters`

An optional data structure that provides a hint to the sparsity function.

`workspace`

An optional pointer to a memory region that the function uses as scratch space.

`filterParameters`

The runtime filter parameters.

---

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