# argument(name:dataType:shape:intent:) Registers and returns an input or in-out tensor argument to the graph. ``` func argument(name: String? = nil, dataType: T.Type, shape: [Int], intent: BNNSGraph.Builder.Intent = .input) -> BNNSGraph.Builder.Tensor where T : BNNSScalar ``` ## Parameters `name` The name of the argument. `dataType` The argument’s data type. `shape` An array of integers or closed ranges that define the sizes of each dimension of the argument. Pass a negative value to specify a flexible dimension. `intent` A constant that specifies whether the argument is input, output, or in-out. ## Discussion The following code shows how to specify inputs with flexible shapes. The code calls `setBatchSize` before executing the context to specify that the two inputs and the output tensors are 8-element vectors: ``` let context = try? BNNSGraph.makeContext ({ builder in let x = builder.argument(name: "x", dataType: Float.self, shape: [-1]) let y = builder.argument(name: "y", dataType: Float.self, shape: [-1]) let z = x + y return [z] }) var args = context.argumentNames().map { name in return context.tensor(argument: name, fillKnownDynamicShapes: false)! } defer { args.forEach { $0.deallocate() } } let n = 8 context.setBatchSize(n) args[context.argumentPosition(argument: "x")] .allocate(initializingFrom: [1, 2, 3, 4, 5, 6, 7, 8] as [Float]) args[context.argumentPosition(argument: "y")] .allocate(initializingFrom: [10, 20, 30, 40, 50, 60, 70, 80] as [Float]) // Output argument args[0].allocate(as: Float.self, count: n) try context.executeFunction(arguments: &args) ``` On return, the output tensor contains the values `[11, 22, 33, 44, 55, 66, 77, 88]`. ``` --- Copyright © 2026 Apple Inc. All rights reserved. | [Terms of Use](https://www.apple.com/legal/internet-services/terms/site.html) | [Privacy Policy](https://www.apple.com/privacy/privacy-policy)