diff options
Diffstat (limited to 'src/armnn/backends/test/ActivationTestImpl.hpp')
| -rw-r--r-- | src/armnn/backends/test/ActivationTestImpl.hpp | 27 |
1 files changed, 14 insertions, 13 deletions
diff --git a/src/armnn/backends/test/ActivationTestImpl.hpp b/src/armnn/backends/test/ActivationTestImpl.hpp index 255a00ef0b..e699b2289b 100644 --- a/src/armnn/backends/test/ActivationTestImpl.hpp +++ b/src/armnn/backends/test/ActivationTestImpl.hpp @@ -53,7 +53,7 @@ LayerTestResult<T, 4> BoundedReLuTestCommon(armnn::IWorkloadFactory& workloadFac std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); - // Setup bounded ReLu + // Setup bounded ReLu. armnn::ActivationQueueDescriptor descriptor; armnn::WorkloadInfo workloadInfo; AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get()); @@ -94,7 +94,7 @@ LayerTestResult<float, 4> BoundedReLuUpperAndLowerBoundTest(armnn::IWorkloadFact 0.999f, 1.2f, 0.89f, 6.1f, }; - // Calculated manually + // Calculated manually. std::vector<float> output = std::vector<float>{ -1.0f, 0.1f, 0.5f, 1.0f, 0.786f, 0.9875f, -1.0f, 0.384f, @@ -122,7 +122,7 @@ LayerTestResult<float, 4> BoundedReLuUpperBoundOnlyTest(armnn::IWorkloadFactory& 0.999f, 1.2f, 0.89f, 6.1f, }; - // Calculated manually + // Calculated manually. std::vector<float> output = std::vector<float>{ 0.0f, 0.1f, 0.5f, 6.0f, 0.786f, 5.9875f, 0.0f, 0.384f, @@ -147,7 +147,7 @@ LayerTestResult<uint8_t, 4> BoundedReLuUint8UpperBoundOnlyTest(armnn::IWorkloadF 251, 8, 92 }; - // Calculated manually + // Calculated manually. std::vector<uint8_t> output = std::vector<uint8_t>{ 0, 122, 0, 255, 0, 58 @@ -176,7 +176,7 @@ LayerTestResult<uint8_t, 4> BoundedReLuUint8UpperAndLowerBoundTest(armnn::IWorkl 251, 8, 92 }; - // Calculated manually + // Calculated manually. std::vector<uint8_t> output = std::vector<uint8_t>{ 51, 192, 32, 192, 32, 92 @@ -186,7 +186,7 @@ LayerTestResult<uint8_t, 4> BoundedReLuUint8UpperAndLowerBoundTest(armnn::IWorkl float inputScale = 0.0125f; return BoundedReLuTestCommon(workloadFactory, 1.0f, -1.0f, - inputScale, inputOffset, inputScale, inputOffset, // input/output scale & offset same + inputScale, inputOffset, inputScale, inputOffset, // Input/output scale & offset same. input, output, inputWidth, inputHeight, inputChannels, inputBatchSize); } @@ -229,13 +229,14 @@ boost::multi_array<float, 4> BoundedReLuRandomInputTest(armnn::IWorkloadFactory& boost::multi_array<float, 4> output(GetTensorShapeAsArray<4>(outputTensorInfo)); - // min/max random values passed to MakeRandomTensor are purposely outside of the ReLu range [lowerBound, upperBound] + // Min/max random values passed to MakeRandomTensor are purposely outside of the ReLu + // range [lowerBound, upperBound]. auto input = MakeRandomTensor<float, 4>(inputTensorInfo, 4605828, lowerBound - 5.0f, upperBound * 2.0f); std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); - // Setup bounded ReLu + // Set up bounded ReLu. armnn::ActivationQueueDescriptor descriptor; armnn::WorkloadInfo workloadInfo; AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get()); @@ -308,7 +309,7 @@ LayerTestResult<T,4> ConstantLinearActivationTestCommon(armnn::IWorkloadFactory& std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); - // Do linear activation that should leave tensor unchanged + // Do linear activation that should leave the tensor unchanged. armnn::ActivationQueueDescriptor data; armnn::WorkloadInfo info; AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); @@ -329,7 +330,7 @@ LayerTestResult<T,4> ConstantLinearActivationTestCommon(armnn::IWorkloadFactory& CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get()); - // Ensure output equals input + // Ensure output equals input. ret.outputExpected = input; return ret; @@ -386,7 +387,7 @@ LayerTestResult<T, 4> SimpleActivationTest(armnn::IWorkloadFactory& workloadFact std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); - // Setup bounded ReLu + // Setup bounded ReLu. armnn::ActivationQueueDescriptor descriptor; armnn::WorkloadInfo workloadInfo; AddInputToWorkload(descriptor, workloadInfo, inputTensorInfo, inputHandle.get()); @@ -407,7 +408,7 @@ LayerTestResult<T, 4> SimpleActivationTest(armnn::IWorkloadFactory& workloadFact CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get()); - // Calculated manually + // Calculated manually. result.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, outputExpectedData)); return result; @@ -423,7 +424,7 @@ LayerTestResult<T, 4> SimpleSigmoidTestCommon(armnn::IWorkloadFactory& workloadF 1.0f, 2.0f, 3.0f, 4.0f }; - // Calculate output values for input + // Calculate output values for input. auto f = [](float value) { return 1.0f / (1.0f + std::exp(-value)); |