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Diffstat (limited to 'src/armnn/backends/test/ActivationFixture.hpp')
-rw-r--r-- | src/armnn/backends/test/ActivationFixture.hpp | 56 |
1 files changed, 0 insertions, 56 deletions
diff --git a/src/armnn/backends/test/ActivationFixture.hpp b/src/armnn/backends/test/ActivationFixture.hpp deleted file mode 100644 index d9d4ca7470..0000000000 --- a/src/armnn/backends/test/ActivationFixture.hpp +++ /dev/null @@ -1,56 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// -#pragma once - -#include "TensorCopyUtils.hpp" -#include "WorkloadTestUtils.hpp" - -struct ActivationFixture -{ - ActivationFixture() - { - auto boostArrayExtents = boost::extents - [boost::numeric_cast<boost::multi_array_types::extent_gen::index>(batchSize)] - [boost::numeric_cast<boost::multi_array_types::extent_gen::index>(channels)] - [boost::numeric_cast<boost::multi_array_types::extent_gen::index>(height)] - [boost::numeric_cast<boost::multi_array_types::extent_gen::index>(width)]; - output.resize(boostArrayExtents); - outputExpected.resize(boostArrayExtents); - input.resize(boostArrayExtents); - - unsigned int inputShape[] = { batchSize, channels, height, width }; - unsigned int outputShape[] = { batchSize, channels, height, width }; - - inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32); - outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32); - - input = MakeRandomTensor<float, 4>(inputTensorInfo, 21453); - } - - unsigned int width = 17; - unsigned int height = 29; - unsigned int channels = 2; - unsigned int batchSize = 5; - - boost::multi_array<float, 4> output; - boost::multi_array<float, 4> outputExpected; - boost::multi_array<float, 4> input; - - armnn::TensorInfo inputTensorInfo; - armnn::TensorInfo outputTensorInfo; - - // Parameters used by some of the activation functions. - float a = 0.234f; - float b = -12.345f; -}; - - -struct PositiveActivationFixture : public ActivationFixture -{ - PositiveActivationFixture() - { - input = MakeRandomTensor<float, 4>(inputTensorInfo, 2342423, 0.0f, 1.0f); - } -};
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