IVGCVSW-1946: Remove armnn/src from the include paths
Change-Id: I663a0a0fccb43ee960ec070121a59df9db0bb04e
diff --git a/src/backends/backendsCommon/test/ActivationFixture.hpp b/src/backends/backendsCommon/test/ActivationFixture.hpp
new file mode 100644
index 0000000..8ff77f6
--- /dev/null
+++ b/src/backends/backendsCommon/test/ActivationFixture.hpp
@@ -0,0 +1,61 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#pragma once
+
+#include "TensorCopyUtils.hpp"
+#include "WorkloadTestUtils.hpp"
+
+#include <test/TensorHelpers.hpp>
+
+#include <boost/numeric/conversion/cast.hpp>
+#include <boost/multi_array.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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