What are integration testing setup for Core ML in Swift?

Integration testing for Core ML in Swift involves setting up a test environment where you can validate the interaction between the Core ML model and your app’s components. This often includes loading a model, making predictions, and verifying the output against expected results.

Steps to Set Up Integration Testing for Core ML

Import the Core ML Model: Ensure the model is included in your project.
Create Test Cases: Use XCTest framework to write test cases for the model's functionality.
Load the Model: In your test, load the Core ML model.
Make Predictions: Pass sample data to the model and retrieve predictions.
Assert Results: Verify that the predictions match the expected outputs.

Example of Core ML Integration Testing


        import XCTest
        import CoreML

        class CoreMLModelTests: XCTestCase {
            var model: YourModelName!

            override func setUp() {
                super.setUp()
                // Load your Core ML model
                model = try? YourModelName(configuration: MLModelConfiguration())
            }
            
            func testModelPrediction() {
                // Prepare sample input data
                let input = YourModelNameInput(sampleData: ...)
                
                // Make prediction
                let prediction = try? model.prediction(input: input)
                
                // Verify the output
                XCTAssertNotNil(prediction)
                XCTAssertEqual(prediction?.outputValue, expectedOutput)
            }
        }

Core ML Swift Integration Testing XCTest Machine Learning iOS Development

What are integration testing setup for Core ML in Swift?

Steps to Set Up Integration Testing for Core ML

Example of Core ML Integration Testing

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What are integration testing setup for Core ML in Swift?

Steps to Set Up Integration Testing for Core ML

Example of Core ML Integration Testing

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