diff --git a/tests/dataset/ActivationLayerDataset.h b/tests/dataset/ActivationLayerDataset.h
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+/*
+ * Copyright (c) 2017 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef __ARM_COMPUTE_TEST_DATASET_ACTIVATION_LAYER_DATASET_H__
+#define __ARM_COMPUTE_TEST_DATASET_ACTIVATION_LAYER_DATASET_H__
+
+#include "TypePrinter.h"
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "dataset/GenericDataset.h"
+
+#include <sstream>
+#include <type_traits>
+
+#ifdef BOOST
+#include "boost_wrapper.h"
+#endif
+
+namespace arm_compute
+{
+namespace test
+{
+class ActivationLayerDataObject
+{
+public:
+    operator std::string() const
+    {
+        std::stringstream ss;
+        ss << "ActivationLayer";
+        ss << "_I" << shape;
+        ss << "_F_" << info.activation();
+        return ss.str();
+    }
+
+public:
+    TensorShape         shape;
+    ActivationLayerInfo info;
+};
+
+template <unsigned int Size>
+using ActivationLayerDataset = GenericDataset<ActivationLayerDataObject, Size>;
+
+class AlexNetActivationLayerDataset final : public ActivationLayerDataset<5>
+{
+public:
+    AlexNetActivationLayerDataset()
+        : GenericDataset
+    {
+        ActivationLayerDataObject{ TensorShape(55U, 55U, 96U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        ActivationLayerDataObject{ TensorShape(27U, 27U, 256U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        ActivationLayerDataObject{ TensorShape(13U, 13U, 384U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        ActivationLayerDataObject{ TensorShape(13U, 13U, 256U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        ActivationLayerDataObject{ TensorShape(4096U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+    }
+    {
+    }
+
+    ~AlexNetActivationLayerDataset() = default;
+};
+
+class LeNet5ActivationLayerDataset final : public ActivationLayerDataset<1>
+{
+public:
+    LeNet5ActivationLayerDataset()
+        : GenericDataset
+    {
+        ActivationLayerDataObject{ TensorShape(500U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+    }
+    {
+    }
+
+    ~LeNet5ActivationLayerDataset() = default;
+};
+
+class GoogLeNetActivationLayerDataset final : public ActivationLayerDataset<33>
+{
+public:
+    GoogLeNetActivationLayerDataset()
+        : GenericDataset
+    {
+        // conv1/relu_7x7
+        ActivationLayerDataObject{ TensorShape(112U, 112U, 64U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // conv2/relu_3x3_reduce
+        ActivationLayerDataObject{ TensorShape(56U, 56U, 64U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // conv2/relu_3x3
+        ActivationLayerDataObject{ TensorShape(56U, 56U, 192U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_3a/relu_1x1, inception_3b/relu_pool_proj
+        ActivationLayerDataObject{ TensorShape(28U, 28U, 64U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_3a/relu_3x3_reduce, inception_3b/relu_5x5
+        ActivationLayerDataObject{ TensorShape(28U, 28U, 96U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_3a/relu_3x3, inception_3b/relu_1x1, inception_3b/relu_3x3_reduce
+        ActivationLayerDataObject{ TensorShape(28U, 28U, 128U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_3a/relu_5x5_reduce
+        ActivationLayerDataObject{ TensorShape(28U, 28U, 16U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_3a/relu_5x5, inception_3a/relu_pool_proj, inception_3b/relu_5x5_reduce
+        ActivationLayerDataObject{ TensorShape(28U, 28U, 32U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_3b/relu_3x3
+        ActivationLayerDataObject{ TensorShape(28U, 28U, 192U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4a/relu_1x1
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 192U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4a/relu_3x3_reduce
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 96U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4a/relu_3x3
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 208U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4a/relu_5x5_reduce
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 16U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4a/relu_5x5
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 48U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4a/relu_pool_proj, inception_4b/relu_5x5, inception_4b/relu_pool_proj, inception_4c/relu_5x5, inception_4c/relu_pool_proj, inception_4d/relu_5x5, inception_4d/relu_pool_proj
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 64U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4b/relu_1x1, inception_4e/relu_3x3_reduce
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 160U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4b/relu_3x3_reduce, inception_4d/relu_1x1
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 112U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4b/relu_3x3
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 224U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4b/relu_5x5_reduce, inception_4c/relu_5x5_reduce
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 24U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4c/relu_1x1, inception_4c/relu_3x3_reduce, inception_4e/relu_5x5, inception_4e/relu_pool_proj
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 128U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4c/relu_3x3, inception_4e/relu_1x1
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 256U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4d/relu_3x3_reduce
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 144U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4d/relu_3x3
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 288U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4d/relu_5x5_reduce, inception_4e/relu_5x5_reduce
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 32U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_4e/relu_3x3
+        ActivationLayerDataObject{ TensorShape(14U, 14U, 320U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_5a/relu_1x1
+        ActivationLayerDataObject{ TensorShape(7U, 7U, 256U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_5a/relu_3x3_reduce
+        ActivationLayerDataObject{ TensorShape(7U, 7U, 160U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_5a/relu_3x3
+        ActivationLayerDataObject{ TensorShape(7U, 7U, 320U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_5a/relu_5x5_reduce
+        ActivationLayerDataObject{ TensorShape(7U, 7U, 32U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_5a/relu_5x5, inception_5a/relu_pool_proj, inception_5b/relu_5x5, inception_5b/relu_pool_proj
+        ActivationLayerDataObject{ TensorShape(7U, 7U, 128U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_5b/relu_1x1, inception_5b/relu_3x3
+        ActivationLayerDataObject{ TensorShape(7U, 7U, 384U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_5b/relu_3x3_reduce
+        ActivationLayerDataObject{ TensorShape(7U, 7U, 192U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) },
+        // inception_5b/relu_5x5_reduce
+        ActivationLayerDataObject{ TensorShape(7U, 7U, 48U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }
+    }
+    {
+    }
+
+    ~GoogLeNetActivationLayerDataset() = default;
+};
+
+} // namespace test
+} // namespace arm_compute
+#endif //__ARM_COMPUTE_TEST_DATASET_ACTIVATION_LAYER_DATASET_H__