diff --git a/tests/datasets_new/ActivationLayerDataset.h b/tests/datasets_new/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_ACTIVATION_LAYER_DATASET
+#define ARM_COMPUTE_TEST_ACTIVATION_LAYER_DATASET
+
+#include "framework/datasets/Datasets.h"
+
+#include "tests/TypePrinter.h"
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace datasets
+{
+class AlexNetActivationLayerDataset final : public
+    framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>>
+{
+public:
+    AlexNetActivationLayerDataset()
+        : CartesianProductDataset
+    {
+        framework::dataset::make("Shape", {
+            TensorShape(55U, 55U, 96U), TensorShape(27U, 27U, 256U),
+            TensorShape(13U, 13U, 384U), TensorShape(13U, 13U, 256U),
+            TensorShape(4096U) }),
+        framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
+    }
+    {
+    }
+    AlexNetActivationLayerDataset(AlexNetActivationLayerDataset &&) = default;
+    ~AlexNetActivationLayerDataset()                                = default;
+};
+
+class LeNet5ActivationLayerDataset final : public
+    framework::dataset::CartesianProductDataset<framework::dataset::SingletonDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>>
+{
+public:
+    LeNet5ActivationLayerDataset()
+        : CartesianProductDataset
+    {
+        framework::dataset::make("Shape", TensorShape(500U)),
+        framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
+    }
+    {
+    }
+    LeNet5ActivationLayerDataset(LeNet5ActivationLayerDataset &&) = default;
+    ~LeNet5ActivationLayerDataset()                               = default;
+};
+
+class GoogLeNetActivationLayerDataset final : public
+    framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>>
+{
+public:
+    GoogLeNetActivationLayerDataset()
+        : CartesianProductDataset
+    {
+        framework::dataset::make("Shape", { // conv1/relu_7x7
+            TensorShape(112U, 112U, 64U),
+            // conv2/relu_3x3_reduce
+            TensorShape(56U, 56U, 64U),
+            // conv2/relu_3x3
+            TensorShape(56U, 56U, 192U),
+            // inception_3a/relu_1x1, inception_3b/relu_pool_proj
+            TensorShape(28U, 28U, 64U),
+            // inception_3a/relu_3x3_reduce, inception_3b/relu_5x5
+            TensorShape(28U, 28U, 96U),
+            // inception_3a/relu_3x3, inception_3b/relu_1x1, inception_3b/relu_3x3_reduce
+            TensorShape(28U, 28U, 128U),
+            // inception_3a/relu_5x5_reduce
+            TensorShape(28U, 28U, 16U),
+            // inception_3a/relu_5x5, inception_3a/relu_pool_proj, inception_3b/relu_5x5_reduce
+            TensorShape(28U, 28U, 32U),
+            // inception_3b/relu_3x3
+            TensorShape(28U, 28U, 192U),
+            // inception_4a/relu_1x1
+            TensorShape(14U, 14U, 192U),
+            // inception_4a/relu_3x3_reduce
+            TensorShape(14U, 14U, 96U),
+            // inception_4a/relu_3x3
+            TensorShape(14U, 14U, 208U),
+            // inception_4a/relu_5x5_reduce
+            TensorShape(14U, 14U, 16U),
+            // inception_4a/relu_5x5
+            TensorShape(14U, 14U, 48U),
+            // 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
+            TensorShape(14U, 14U, 64U),
+            // inception_4b/relu_1x1, inception_4e/relu_3x3_reduce
+            TensorShape(14U, 14U, 160U),
+            // inception_4b/relu_3x3_reduce, inception_4d/relu_1x1
+            TensorShape(14U, 14U, 112U),
+            // inception_4b/relu_3x3
+            TensorShape(14U, 14U, 224U),
+            // inception_4b/relu_5x5_reduce, inception_4c/relu_5x5_reduce
+            TensorShape(14U, 14U, 24U),
+            // inception_4c/relu_1x1, inception_4c/relu_3x3_reduce, inception_4e/relu_5x5, inception_4e/relu_pool_proj
+            TensorShape(14U, 14U, 128U),
+            // inception_4c/relu_3x3, inception_4e/relu_1x1
+            TensorShape(14U, 14U, 256U),
+            // inception_4d/relu_3x3_reduce
+            TensorShape(14U, 14U, 144U),
+            // inception_4d/relu_3x3
+            TensorShape(14U, 14U, 288U),
+            // inception_4d/relu_5x5_reduce, inception_4e/relu_5x5_reduce
+            TensorShape(14U, 14U, 32U),
+            // inception_4e/relu_3x3
+            TensorShape(14U, 14U, 320U),
+            // inception_5a/relu_1x1
+            TensorShape(7U, 7U, 256U),
+            // inception_5a/relu_3x3_reduce
+            TensorShape(7U, 7U, 160U),
+            // inception_5a/relu_3x3
+            TensorShape(7U, 7U, 320U),
+            // inception_5a/relu_5x5_reduce
+            TensorShape(7U, 7U, 32U),
+            // inception_5a/relu_5x5, inception_5a/relu_pool_proj, inception_5b/relu_5x5, inception_5b/relu_pool_proj
+            TensorShape(7U, 7U, 128U),
+            // inception_5b/relu_1x1, inception_5b/relu_3x3
+            TensorShape(7U, 7U, 384U),
+            // inception_5b/relu_3x3_reduce
+            TensorShape(7U, 7U, 192U),
+            // inception_5b/relu_5x5_reduce
+            TensorShape(7U, 7U, 48U) }),
+        framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
+    }
+    {
+    }
+    GoogLeNetActivationLayerDataset(GoogLeNetActivationLayerDataset &&) = default;
+    ~GoogLeNetActivationLayerDataset()                                  = default;
+};
+} // namespace datasets
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_ACTIVATION_LAYER_DATASET */