COMPMID-415: Move ActivationLayer to new validation

Change-Id: I38ce20d95640f9c1baf699a095c35e592ad4339f
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/81115
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>

17 files changed, 996 insertions, 810 deletions

diff --git a/support/ToolchainSupport.h b/support/ToolchainSupport.h
index 1a909d56db..c73f2486e1 100644
--- a/support/ToolchainSupport.h
+++ b/support/ToolchainSupport.h
@@ -51,7 +51,7 @@ namespace cpp11
  * @return String representation of @p value.
  */
 template <typename T, typename std::enable_if<std::is_arithmetic<typename std::decay<T>::type>::value, int>::type = 0>
-std::string to_string(T && value)
+inline std::string to_string(T && value)
 {
     std::stringstream stream;
     stream << std::forward<T>(value);
@@ -165,7 +165,7 @@ inline T copysign(T x, T y)
  * @return String representation of @p value.
  */
 template <typename T>
-std::string to_string(T &&value)
+inline std::string to_string(T &&value)
 {
     return ::std::to_string(std::forward<T>(value));
 }
@@ -261,6 +261,13 @@ inline T copysign(T x, T y)
     return std::copysign(x, y);
 }
 #endif /* __ANDROID__ */
+
+inline std::string to_string(bool value)
+{
+    std::stringstream str;
+    str << std::boolalpha << value;
+    return str.str();
+}
 } // namespace cpp11
 
 namespace cpp14
diff --git a/tests/TypePrinter.h b/tests/TypePrinter.h
index 10d33882ce..5f7313552e 100644
--- a/tests/TypePrinter.h
+++ b/tests/TypePrinter.h
@@ -240,6 +240,13 @@ inline ::std::ostream &operator<<(::std::ostream &os, const ActivationLayerInfo:
     return os;
 }
 
+inline std::string to_string(const ActivationLayerInfo::ActivationFunction &function)
+{
+    std::stringstream str;
+    str << function;
+    return str.str();
+}
+
 inline std::string to_string(const ActivationLayerInfo &info)
 {
     std::stringstream str;
diff --git a/tests/datasets_new/ActivationFunctionsDataset.h b/tests/datasets_new/ActivationFunctionsDataset.h
new file mode 100644
index 0000000000..0a11902d51
--- /dev/null
+++ b/tests/datasets_new/ActivationFunctionsDataset.h
@@ -0,0 +1,58 @@
+/*
+ * 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_ACTIVATIONFUNCTIONS_DATASET_H__
+#define __ARM_COMPUTE_TEST_ACTIVATIONFUNCTIONS_DATASET_H__
+
+#include "arm_compute/core/Types.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace datasets
+{
+class ActivationFunctions final : public framework::dataset::ContainerDataset<std::vector<ActivationLayerInfo::ActivationFunction>>
+{
+public:
+    ActivationFunctions()
+        : ContainerDataset("ActivationFunction",
+    {
+        ActivationLayerInfo::ActivationFunction::ABS,
+                            ActivationLayerInfo::ActivationFunction::LINEAR,
+                            ActivationLayerInfo::ActivationFunction::LOGISTIC,
+                            ActivationLayerInfo::ActivationFunction::RELU,
+                            ActivationLayerInfo::ActivationFunction::BOUNDED_RELU,
+                            ActivationLayerInfo::ActivationFunction::LEAKY_RELU,
+                            ActivationLayerInfo::ActivationFunction::SOFT_RELU,
+                            ActivationLayerInfo::ActivationFunction::SQRT,
+                            ActivationLayerInfo::ActivationFunction::SQUARE,
+                            ActivationLayerInfo::ActivationFunction::TANH
+    })
+    {
+    }
+};
+} // namespace datasets
+} // namespace test
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_TEST_ACTIVATIONFUNCTIONS_DATASET_H__ */
diff --git a/tests/validation/CL/ActivationLayer.cpp b/tests/validation/CL/ActivationLayer.cpp
deleted file mode 100644
index a1e00b681b..0000000000
--- a/tests/validation/CL/ActivationLayer.cpp
+++ /dev/null
@@ -1,282 +0,0 @@
-/*
- * 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.
- */
-#include "AssetsLibrary.h"
-#include "CL/CLAccessor.h"
-#include "Globals.h"
-#include "PaddingCalculator.h"
-#include "TypePrinter.h"
-#include "Utils.h"
-#include "validation/Datasets.h"
-#include "validation/Helpers.h"
-#include "validation/Reference.h"
-#include "validation/Validation.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CL/CLTensorAllocator.h"
-#include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
-
-#include "boost_wrapper.h"
-
-#include <random>
-#include <string>
-#include <tuple>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::validation;
-
-namespace
-{
-/** Define tolerance of the activation layer
- *
- * @param[in] activation           The activation function used.
- * @param[in] fixed_point_position Number of bits for the fractional part..
- *
- * @return Tolerance depending on the activation function.
- */
-float activation_layer_tolerance(ActivationLayerInfo::ActivationFunction activation, int fixed_point_position = 0)
-{
-    switch(activation)
-    {
-        case ActivationLayerInfo::ActivationFunction::LOGISTIC:
-        case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
-        case ActivationLayerInfo::ActivationFunction::SQRT:
-        case ActivationLayerInfo::ActivationFunction::TANH:
-            return (fixed_point_position != 0) ? 5.f : 0.00001f;
-            break;
-        default:
-            return 0.f;
-    }
-}
-
-/** Compute CL activation layer function.
- *
- * @param[in] in_place             Compute the activation layer in-place.
- * @param[in] shape                Shape of the input and output tensors.
- * @param[in] dt                   Shape Data type of tensors.
- * @param[in] act_info             Activation layer information.
- * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of fixed point numbers.
- *
- * @return Computed output tensor.
- */
-CLTensor compute_activation_layer(bool in_place, const TensorShape &shape, DataType dt, ActivationLayerInfo act_info, int fixed_point_position = 0)
-{
-    // Create tensors
-    CLTensor src = create_tensor<CLTensor>(shape, dt, 1, fixed_point_position);
-    CLTensor dst = create_tensor<CLTensor>(shape, dt, 1, fixed_point_position);
-
-    // Create and configure function
-    CLActivationLayer act_layer;
-
-    if(in_place)
-    {
-        act_layer.configure(&src, nullptr, act_info);
-    }
-    else
-    {
-        act_layer.configure(&src, &dst, act_info);
-    }
-
-    // Allocate tensors
-    src.allocator()->allocate();
-    BOOST_TEST(!src.info()->is_resizable());
-
-    if(!in_place)
-    {
-        dst.allocator()->allocate();
-        BOOST_TEST(!dst.info()->is_resizable());
-    }
-
-    // Fill tensors
-    if(dt == DataType::F32)
-    {
-        float min_bound = 0;
-        float max_bound = 0;
-        std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<float>(act_info.activation());
-        std::uniform_real_distribution<> distribution(min_bound, max_bound);
-        library->fill(CLAccessor(src), distribution, 0);
-    }
-    else
-    {
-        int min_bound = 0;
-        int max_bound = 0;
-        if(dt == DataType::QS8)
-        {
-            std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<int8_t>(act_info.activation(), fixed_point_position);
-        }
-        else
-        {
-            std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<int16_t>(act_info.activation(), fixed_point_position);
-        }
-        std::uniform_int_distribution<> distribution(min_bound, max_bound);
-        library->fill(CLAccessor(src), distribution, 0);
-    }
-
-    // Compute function
-    act_layer.run();
-
-    if(in_place)
-    {
-        return src;
-    }
-    else
-    {
-        return dst;
-    }
-}
-} // namespace
-
-#ifndef DOXYGEN_SKIP_THIS
-BOOST_AUTO_TEST_SUITE(CL)
-BOOST_AUTO_TEST_SUITE(ActivationLayer)
-
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
-BOOST_DATA_TEST_CASE(Configuration, boost::unit_test::data::make({ false, true }) * (SmallShapes() + LargeShapes()) * CNNDataTypes(), in_place, shape, dt)
-{
-    // Set fixed point position data type allowed
-    const int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0;
-
-    // Create tensors
-    CLTensor src = create_tensor<CLTensor>(shape, dt, 1, fixed_point_position);
-    CLTensor dst = create_tensor<CLTensor>(shape, dt, 1, fixed_point_position);
-
-    BOOST_TEST(src.info()->is_resizable());
-    BOOST_TEST(dst.info()->is_resizable());
-
-    // Create and configure function
-    CLActivationLayer act_layer;
-
-    if(in_place)
-    {
-        act_layer.configure(&src, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS));
-    }
-    else
-    {
-        act_layer.configure(&src, &dst, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS));
-    }
-
-    // Validate valid region
-    const ValidRegion valid_region = shape_to_valid_region(shape);
-    validate(src.info()->valid_region(), valid_region);
-
-    if(!in_place)
-    {
-        validate(dst.info()->valid_region(), valid_region);
-    }
-
-    // Validate padding
-    const int         step    = 16 / arm_compute::data_size_from_type(dt);
-    const PaddingSize padding = PaddingCalculator(shape.x(), step).required_padding();
-    validate(src.info()->padding(), padding);
-
-    if(!in_place)
-    {
-        validate(dst.info()->padding(), padding);
-    }
-}
-
-BOOST_AUTO_TEST_SUITE(Float)
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
-BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * CNNFloatDataTypes() * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }),
-                     in_place, shape, dt, act_function, alpha_beta)
-{
-    // Create activation layer info
-    ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta);
-
-    // Compute function
-    CLTensor dst = compute_activation_layer(in_place, shape, dt, act_info);
-
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info);
-
-    // Validate output
-    validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function));
-}
-
-BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
-BOOST_DATA_TEST_CASE(RunLarge, boost::unit_test::data::make({ false, true }) * LargeShapes() * CNNFloatDataTypes() * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }),
-                     in_place, shape, dt, act_function, alpha_beta)
-{
-    // Create activation layer info
-    ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta);
-
-    // Compute function
-    CLTensor dst = compute_activation_layer(in_place, shape, dt, act_info);
-
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info);
-
-    // Validate output
-    validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function));
-}
-BOOST_AUTO_TEST_SUITE_END()
-
-/** @note We test for fixed point precision [3,5] because [1,2] and [6,7] ranges
- *        cause overflowing issues in most of the transcendentals functions.
- */
-BOOST_AUTO_TEST_SUITE(Quantized)
-BOOST_AUTO_TEST_SUITE(QS8)
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
-BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 6, 1) * boost::unit_test::data::make({ 0.5f, 1.f }),
-                     in_place, shape, act_function, fixed_point_position, alpha_beta)
-{
-    // Create activation layer info
-    ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta);
-
-    // Compute function
-    CLTensor dst = compute_activation_layer(in_place, shape, DataType::QS8, act_info, fixed_point_position);
-
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS8, act_info, fixed_point_position);
-
-    // Validate output
-    validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function, fixed_point_position));
-}
-BOOST_AUTO_TEST_SUITE_END()
-
-BOOST_AUTO_TEST_SUITE(QS16)
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
-BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 14, 1) * boost::unit_test::data::make({ 0.5f, 1.f }),
-                     in_place, shape, act_function, fixed_point_position, alpha_beta)
-{
-    // Create activation layer info
-    ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta);
-
-    // Compute function
-    CLTensor dst = compute_activation_layer(in_place, shape, DataType::QS16, act_info, fixed_point_position);
-
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS16, act_info, fixed_point_position);
-
-    // Validate output
-    validate(CLAccessor(dst), ref_dst, activation_layer_tolerance(act_function, fixed_point_position));
-}
-BOOST_AUTO_TEST_SUITE_END()
-BOOST_AUTO_TEST_SUITE_END()
-
-BOOST_AUTO_TEST_SUITE_END()
-BOOST_AUTO_TEST_SUITE_END()
-#endif /* DOXYGEN_SKIP_THIS */
\ No newline at end of file
diff --git a/tests/validation/NEON/ActivationLayer.cpp b/tests/validation/NEON/ActivationLayer.cpp
deleted file mode 100644
index 5f1a2c6fb6..0000000000
--- a/tests/validation/NEON/ActivationLayer.cpp
+++ /dev/null
@@ -1,328 +0,0 @@
-/*
- * 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.
- */
-#include "AssetsLibrary.h"
-#include "Globals.h"
-#include "NEON/Accessor.h"
-#include "PaddingCalculator.h"
-#include "TypePrinter.h"
-#include "Utils.h"
-#include "validation/Datasets.h"
-#include "validation/Helpers.h"
-#include "validation/Reference.h"
-#include "validation/Validation.h"
-
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-
-#include "boost_wrapper.h"
-
-#include <random>
-#include <string>
-#include <tuple>
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::validation;
-
-namespace
-{
-/** Define tolerance of the activation layer
- *
- * @param[in] dt                   The data type used.
- * @param[in] activation           The activation function used.
- * @param[in] fixed_point_position Number of bits for the fractional part..
- *
- * @return Tolerance depending on the activation function.
- */
-float activation_layer_tolerance(DataType dt, ActivationLayerInfo::ActivationFunction activation, int fixed_point_position = 0)
-{
-    switch(activation)
-    {
-        case ActivationLayerInfo::ActivationFunction::LOGISTIC:
-        case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
-        case ActivationLayerInfo::ActivationFunction::SQRT:
-        case ActivationLayerInfo::ActivationFunction::TANH:
-            switch(dt)
-            {
-                case DataType::QS8:
-                    return 5.f;
-                case DataType::QS16:
-                    return 11.f;
-                case DataType::F16:
-                    return 0.01f;
-                default:
-                    return 0.00001f;
-            }
-            break;
-        default:
-            return 0.f;
-    }
-}
-
-/** Compute Neon activation layer function.
- *
- * @param[in] in_place             Compute the activation layer in-place.
- * @param[in] shape                Shape of the input and output tensors.
- * @param[in] dt                   Shape Data type of tensors.
- * @param[in] act_info             Activation layer information.
- * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of fixed point numbers.
- *
- * @return Computed output tensor.
- */
-Tensor compute_activation_layer(bool in_place, const TensorShape &shape, DataType dt, ActivationLayerInfo act_info, int fixed_point_position = 0)
-{
-    // Create tensors
-    Tensor src = create_tensor<Tensor>(shape, dt, 1, fixed_point_position);
-    Tensor dst = create_tensor<Tensor>(shape, dt, 1, fixed_point_position);
-
-    // Create and configure function
-    NEActivationLayer act_layer;
-
-    if(in_place)
-    {
-        act_layer.configure(&src, nullptr, act_info);
-    }
-    else
-    {
-        act_layer.configure(&src, &dst, act_info);
-    }
-
-    // Allocate tensors
-    src.allocator()->allocate();
-    BOOST_TEST(!src.info()->is_resizable());
-
-    if(!in_place)
-    {
-        dst.allocator()->allocate();
-        BOOST_TEST(!dst.info()->is_resizable());
-    }
-    // Fill tensors
-    switch(dt)
-    {
-        case DataType::QS8:
-        {
-            const std::pair<int8_t, int8_t> bounds = get_activation_layer_test_bounds<int8_t>(act_info.activation(), fixed_point_position);
-            std::uniform_int_distribution<> distribution(bounds.first, bounds.second);
-            library->fill(Accessor(src), distribution, 0);
-            break;
-        }
-        case DataType::QS16:
-        {
-            const std::pair<int16_t, int16_t> bounds = get_activation_layer_test_bounds<int16_t>(act_info.activation(), fixed_point_position);
-            std::uniform_int_distribution<> distribution(bounds.first, bounds.second);
-            library->fill(Accessor(src), distribution, 0);
-            break;
-        }
-#ifdef ARM_COMPUTE_ENABLE_FP16
-        case DataType::F16:
-        {
-            const std::pair<float16_t, float16_t> bounds = get_activation_layer_test_bounds<float16_t>(act_info.activation());
-            std::uniform_real_distribution<> distribution(bounds.first, bounds.second);
-            library->fill(Accessor(src), distribution, 0);
-            break;
-        }
-#endif /* ARM_COMPUTE_ENABLE_FP16 */
-        case DataType::F32:
-        {
-            const std::pair<float, float> bounds = get_activation_layer_test_bounds<float>(act_info.activation());
-            std::uniform_real_distribution<> distribution(bounds.first, bounds.second);
-            library->fill(Accessor(src), distribution, 0);
-            break;
-        }
-        default:
-        {
-            ARM_COMPUTE_ERROR("Not supported");
-            break;
-        }
-    }
-
-    // Compute function
-    act_layer.run();
-
-    if(in_place)
-    {
-        return src;
-    }
-    else
-    {
-        return dst;
-    }
-}
-} // namespace
-
-#ifndef DOXYGEN_SKIP_THIS
-BOOST_AUTO_TEST_SUITE(NEON)
-BOOST_AUTO_TEST_SUITE(ActivationLayer)
-
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit") * boost::unit_test::label("nightly"))
-BOOST_DATA_TEST_CASE(Configuration, boost::unit_test::data::make({ false, true }) * (SmallShapes() + LargeShapes()) * CNNDataTypes(), in_place, shape, dt)
-{
-    // Set fixed point position data type allowed
-    const int fixed_point_position = (arm_compute::is_data_type_fixed_point(dt)) ? 3 : 0;
-
-    // Create tensors
-    Tensor src = create_tensor<Tensor>(shape, dt, 1, fixed_point_position);
-    Tensor dst = create_tensor<Tensor>(shape, dt, 1, fixed_point_position);
-
-    BOOST_TEST(src.info()->is_resizable());
-    BOOST_TEST(dst.info()->is_resizable());
-
-    // Create and configure function
-    NEActivationLayer act_layer;
-
-    if(in_place)
-    {
-        act_layer.configure(&src, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS));
-    }
-    else
-    {
-        act_layer.configure(&src, &dst, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS));
-    }
-
-    // Validate valid region
-    const ValidRegion valid_region = shape_to_valid_region(shape);
-    validate(src.info()->valid_region(), valid_region);
-
-    if(!in_place)
-    {
-        validate(dst.info()->valid_region(), valid_region);
-    }
-
-    // Validate padding
-    const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding();
-    validate(src.info()->padding(), padding);
-
-    if(!in_place)
-    {
-        validate(dst.info()->padding(), padding);
-    }
-}
-
-#ifdef ARM_COMPUTE_ENABLE_FP16
-BOOST_AUTO_TEST_SUITE(Float16)
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
-BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * boost::unit_test::data::make(DataType::F16) * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }),
-                     in_place, shape, dt, act_function, alpha_beta)
-{
-    // Create activation layer info
-    const ActivationLayerInfo act_info(act_function, alpha_beta);
-
-    // Compute function
-    Tensor dst = compute_activation_layer(in_place, shape, dt, act_info);
-
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info);
-
-    // Validate output
-    validate(Accessor(dst), ref_dst, activation_layer_tolerance(dt, act_function));
-}
-BOOST_AUTO_TEST_SUITE_END()
-#endif /* ARM_COMPUTE_ENABLE_FP16 */
-
-BOOST_AUTO_TEST_SUITE(Float)
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
-BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * CNNFloatDataTypes() * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }),
-                     in_place, shape, dt, act_function, alpha_beta)
-{
-    // Create activation layer info
-    ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta);
-
-    // Compute function
-    Tensor dst = compute_activation_layer(in_place, shape, dt, act_info);
-
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info);
-
-    // Validate output
-    validate(Accessor(dst), ref_dst, activation_layer_tolerance(dt, act_function));
-}
-
-BOOST_TEST_DECORATOR(*boost::unit_test::label("nightly"))
-BOOST_DATA_TEST_CASE(RunLarge, boost::unit_test::data::make({ false, true }) * LargeShapes() * CNNFloatDataTypes() * ActivationFunctions() * boost::unit_test::data::make({ 0.5f, 1.f }),
-                     in_place, shape, dt, act_function, alpha_beta)
-{
-    // Create activation layer info
-    ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta);
-
-    // Compute function
-    Tensor dst = compute_activation_layer(in_place, shape, dt, act_info);
-
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, dt, act_info);
-
-    // Validate output
-    validate(Accessor(dst), ref_dst, activation_layer_tolerance(dt, act_function));
-}
-BOOST_AUTO_TEST_SUITE_END()
-
-/** @note We test for fixed point precision [3,5] because [1,2] and [6,7] ranges
- *        cause overflowing issues in most of the transcendentals functions.
- */
-BOOST_AUTO_TEST_SUITE(Quantized)
-BOOST_AUTO_TEST_SUITE(QS8)
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
-BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 6, 1) * boost::unit_test::data::make({ 0.5f, 1.f }),
-                     in_place, shape, act_function, fixed_point_position, alpha_beta)
-{
-    // Create activation layer info
-    ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta);
-
-    // Compute function
-    Tensor dst = compute_activation_layer(in_place, shape, DataType::QS8, act_info, fixed_point_position);
-
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS8, act_info, fixed_point_position);
-
-    // Validate output
-    validate(Accessor(dst), ref_dst, activation_layer_tolerance(DataType::QS8, act_function, fixed_point_position));
-}
-BOOST_AUTO_TEST_SUITE_END()
-
-BOOST_AUTO_TEST_SUITE(QS16)
-BOOST_TEST_DECORATOR(*boost::unit_test::label("precommit"))
-BOOST_DATA_TEST_CASE(RunSmall, boost::unit_test::data::make({ false, true }) * SmallShapes() * ActivationFunctions() * boost::unit_test::data::xrange(3, 14, 1) * boost::unit_test::data::make({ 0.5f, 1.f }),
-                     in_place, shape, act_function, fixed_point_position, alpha_beta)
-{
-    // Create activation layer info
-    ActivationLayerInfo act_info(act_function, alpha_beta, alpha_beta);
-
-    // Compute function
-    Tensor dst = compute_activation_layer(in_place, shape, DataType::QS16, act_info, fixed_point_position);
-
-    // Compute reference
-    RawTensor ref_dst = Reference::compute_reference_activation_layer(shape, DataType::QS16, act_info, fixed_point_position);
-
-    // Validate output
-    validate(Accessor(dst), ref_dst, activation_layer_tolerance(DataType::QS16, act_function, fixed_point_position));
-}
-BOOST_AUTO_TEST_SUITE_END()
-
-BOOST_AUTO_TEST_SUITE_END()
-
-BOOST_AUTO_TEST_SUITE_END()
-BOOST_AUTO_TEST_SUITE_END()
-#endif /* DOXYGEN_SKIP_THIS */
diff --git a/tests/validation/Reference.cpp b/tests/validation/Reference.cpp
index f9052f1dba..011fd091f2 100644
--- a/tests/validation/Reference.cpp
+++ b/tests/validation/Reference.cpp
@@ -453,56 +453,6 @@ RawTensor Reference::compute_reference_threshold(const TensorShape &shape, uint8
     return ref_dst;
 }
 
-RawTensor Reference::compute_reference_activation_layer(const TensorShape &shape, DataType dt, ActivationLayerInfo act_info, int fixed_point_position)
-{
-    // Create reference
-    RawTensor ref_src(shape, dt, 1, fixed_point_position);
-    RawTensor ref_dst(shape, dt, 1, fixed_point_position);
-
-    // Fill tensors
-    switch(dt)
-    {
-        case DataType::QS8:
-        {
-            const std::pair<int8_t, int8_t> bounds = get_activation_layer_test_bounds<int8_t>(act_info.activation(), fixed_point_position);
-            std::uniform_int_distribution<> distribution(bounds.first, bounds.second);
-            library->fill(ref_src, distribution, 0);
-            break;
-        }
-        case DataType::QS16:
-        {
-            const std::pair<int16_t, int16_t> bounds = get_activation_layer_test_bounds<int16_t>(act_info.activation(), fixed_point_position);
-            std::uniform_int_distribution<> distribution(bounds.first, bounds.second);
-            library->fill(ref_src, distribution, 0);
-            break;
-        }
-        case DataType::F16:
-        {
-            const std::pair<half_float::half, half_float::half> bounds = get_activation_layer_test_bounds<half_float::half>(act_info.activation());
-            std::uniform_real_distribution<> distribution(bounds.first, bounds.second);
-            library->fill(ref_src, distribution, 0);
-            break;
-        }
-        case DataType::F32:
-        {
-            const std::pair<float, float> bounds = get_activation_layer_test_bounds<float>(act_info.activation());
-            std::uniform_real_distribution<> distribution(bounds.first, bounds.second);
-            library->fill(ref_src, distribution, 0);
-            break;
-        }
-        default:
-        {
-            ARM_COMPUTE_ERROR("Not supported");
-            break;
-        }
-    }
-
-    // Compute reference
-    ReferenceCPP::activation_layer(ref_src, ref_dst, act_info);
-
-    return ref_dst;
-}
-
 RawTensor Reference::compute_reference_batch_normalization_layer(const TensorShape &shape0, const TensorShape &shape1, DataType dt, float epsilon, int fixed_point_position)
 {
     // Create reference
diff --git a/tests/validation/Reference.h b/tests/validation/Reference.h
index eeaa55c739..42c62f8d6a 100644
--- a/tests/validation/Reference.h
+++ b/tests/validation/Reference.h
@@ -295,16 +295,6 @@ public:
      * @return Computed raw tensor.
      */
     static RawTensor compute_reference_threshold(const TensorShape &shape, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper);
-    /** Compute reference activation layer.
-     *
-     * @param[in] shape                Shape of the input and output tensors.
-     * @param[in] dt                   Data type of the tensors.
-     * @param[in] act_info             Activation layer information.
-     * @param[in] fixed_point_position (Optional)Number of bits for the fractional part of fixed point numbers.
-     *
-     * @return Computed raw tensor.
-     */
-    static RawTensor compute_reference_activation_layer(const TensorShape &shape, DataType dt, ActivationLayerInfo act_info, int fixed_point_position = 0);
     /** Compute reference batch normalization layer.
      *
      * @param[in] shape0               Shape of the input and output tensors.
diff --git a/tests/validation/ReferenceCPP.cpp b/tests/validation/ReferenceCPP.cpp
index 81ec60d5b9..117fd5bebb 100644
--- a/tests/validation/ReferenceCPP.cpp
+++ b/tests/validation/ReferenceCPP.cpp
@@ -283,14 +283,6 @@ void ReferenceCPP::threshold(const RawTensor &src, RawTensor &dst, uint8_t thres
     tensor_operations::threshold(s, d, threshold, false_value, true_value, type, upper);
 }
 
-// Activation layer
-void ReferenceCPP::activation_layer(const RawTensor &input, RawTensor &output, ActivationLayerInfo act_info)
-{
-    const TensorVariant s = TensorFactory::get_tensor(input);
-    TensorVariant       d = TensorFactory::get_tensor(output);
-    boost::apply_visitor(tensor_visitors::activation_layer_visitor(s, act_info), d);
-}
-
 // Batch Normalization Layer
 void ReferenceCPP::batch_normalization_layer(const RawTensor &src, RawTensor &dst, const RawTensor &mean, const RawTensor &var, const RawTensor &beta, const RawTensor &gamma, float epsilon,
                                              int fixed_point_position)
diff --git a/tests/validation/ReferenceCPP.h b/tests/validation/ReferenceCPP.h
index 97e573cfa2..0d1bea48bd 100644
--- a/tests/validation/ReferenceCPP.h
+++ b/tests/validation/ReferenceCPP.h
@@ -253,13 +253,6 @@ public:
      * @param[in]  upper       Upper threshold. Only used when the thresholding type is RANGE.
      */
     static void threshold(const RawTensor &src, RawTensor &dst, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper);
-    /** Activation layer of @p src base on information from @p act_info.
-     *
-     * @param[in]  input    Input tensor.
-     * @param[in]  output   Second tensor.
-     * @param[out] act_info Activation layer information.
-     */
-    static void activation_layer(const RawTensor &input, RawTensor &output, ActivationLayerInfo act_info);
     /** Batch Normalization of @p src based on the information from @p norm_info.
      *
      * @param[in]  src                  Input tensor.
diff --git a/tests/validation/TensorOperations.h b/tests/validation/TensorOperations.h
index b472e3d5cf..db145c19ad 100644
--- a/tests/validation/TensorOperations.h
+++ b/tests/validation/TensorOperations.h
@@ -935,109 +935,6 @@ void threshold(const Tensor<T> &in, Tensor<T> &out, uint8_t threshold, uint8_t f
     }
 }
 
-// Activation Layer for floating point type
-template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type * = nullptr>
-void activation_layer(const Tensor<T> &in, Tensor<T> &out, ActivationLayerInfo act_info)
-{
-    const T a = static_cast<T>(act_info.a());
-    const T b = static_cast<T>(act_info.b());
-
-    for(int i = 0; i < in.num_elements(); ++i)
-    {
-        T x = in[i];
-        switch(act_info.activation())
-        {
-            case ActivationLayerInfo::ActivationFunction::ABS:
-                out[i] = std::abs(x);
-                break;
-            case ActivationLayerInfo::ActivationFunction::LINEAR:
-                out[i] = a * x + b;
-                break;
-            case ActivationLayerInfo::ActivationFunction::LOGISTIC:
-                out[i] = static_cast<T>(1) / (static_cast<T>(1) + std::exp(-x));
-                break;
-            case ActivationLayerInfo::ActivationFunction::RELU:
-                out[i] = std::max(static_cast<T>(0), x);
-                break;
-            case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
-                out[i] = std::min<T>(a, std::max(static_cast<T>(0), x));
-                break;
-            case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
-                out[i] = (x > 0) ? x : a * x;
-                break;
-            case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
-                out[i] = std::log(static_cast<T>(1) + std::exp(x));
-                break;
-            case ActivationLayerInfo::ActivationFunction::SQRT:
-                out[i] = std::sqrt(x);
-                break;
-            case ActivationLayerInfo::ActivationFunction::SQUARE:
-                out[i] = x * x;
-                break;
-            case ActivationLayerInfo::ActivationFunction::TANH:
-                out[i] = a * std::tanh(b * x);
-                break;
-            default:
-                ARM_COMPUTE_ERROR("Activation function not recognised");
-                break;
-        }
-    }
-}
-
-// Activation Layer for fixed point type
-template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type * = nullptr>
-void activation_layer(const Tensor<T> &in, Tensor<T> &out, ActivationLayerInfo act_info)
-{
-    using namespace fixed_point_arithmetic;
-    int                                     fixed_point_position = in.fixed_point_position();
-    ActivationLayerInfo::ActivationFunction act_func             = act_info.activation();
-    const fixed_point<T>                    a(act_info.a(), fixed_point_position);
-    const fixed_point<T>                    b(act_info.b(), fixed_point_position);
-    const fixed_point<T>                    const_0(0, fixed_point_position);
-    const fixed_point<T>                    const_1(1, fixed_point_position);
-
-    for(int i = 0; i < in.num_elements(); ++i)
-    {
-        fixed_point<T> x(in[i], fixed_point_position, true);
-        switch(act_func)
-        {
-            case ActivationLayerInfo::ActivationFunction::ABS:
-                out[i] = abs(x).raw();
-                break;
-            case ActivationLayerInfo::ActivationFunction::LINEAR:
-                out[i] = add(b, mul(a, x)).raw();
-                break;
-            case ActivationLayerInfo::ActivationFunction::LOGISTIC:
-                out[i] = (const_1 / (const_1 + exp(-x))).raw();
-                break;
-            case ActivationLayerInfo::ActivationFunction::RELU:
-                out[i] = max(const_0, x).raw();
-                break;
-            case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
-                out[i] = min(a, max(const_0, x)).raw();
-                break;
-            case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
-                out[i] = (x > const_0) ? x.raw() : mul(a, x).raw();
-                break;
-            case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
-                out[i] = log(const_1 + exp(x)).raw();
-                break;
-            case ActivationLayerInfo::ActivationFunction::SQRT:
-                out[i] = (const_1 / inv_sqrt(x)).raw();
-                break;
-            case ActivationLayerInfo::ActivationFunction::SQUARE:
-                out[i] = mul(x, x).raw();
-                break;
-            case ActivationLayerInfo::ActivationFunction::TANH:
-                out[i] = mul(a, tanh(mul(b, x))).raw();
-                break;
-            default:
-                ARM_COMPUTE_ERROR("Activation function not recognised");
-                break;
-        }
-    }
-}
-
 // Batch Normalization Layer for fixed point type
 template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type * = nullptr>
 void batch_normalization_layer(const Tensor<T> &in, Tensor<T> &out, const Tensor<T> &mean, const Tensor<T> &var, const Tensor<T> &beta, const Tensor<T> &gamma, float epsilon, int fixed_point_position)
diff --git a/tests/validation/TensorVisitors.h b/tests/validation/TensorVisitors.h
index 44ae6f13e8..365aac7758 100644
--- a/tests/validation/TensorVisitors.h
+++ b/tests/validation/TensorVisitors.h
@@ -228,26 +228,6 @@ private:
 template struct arm_compute::test::validation::tensor_visitors::table_lookup<uint8_t>;
 template struct arm_compute::test::validation::tensor_visitors::table_lookup<int16_t>;
 
-// Activation layer visitor
-struct activation_layer_visitor : public boost::static_visitor<>
-{
-public:
-    explicit activation_layer_visitor(const TensorVariant &in, ActivationLayerInfo act_info)
-        : _in(in), _act_info(act_info)
-    {
-    }
-
-    template <typename T>
-    void operator()(Tensor<T> &out) const
-    {
-        const auto &in = boost::get<Tensor<T>>(_in);
-        tensor_operations::activation_layer(in, out, _act_info);
-    }
-
-private:
-    const TensorVariant      &_in;
-    const ActivationLayerInfo _act_info;
-};
 // Batch Normalization Layer visitor
 struct batch_normalization_layer_visitor : public boost::static_visitor<>
 {
diff --git a/tests/validation_new/CL/ActivationLayer.cpp b/tests/validation_new/CL/ActivationLayer.cpp
new file mode 100644
index 0000000000..e1cc4e54e2
--- /dev/null
+++ b/tests/validation_new/CL/ActivationLayer.cpp
@@ -0,0 +1,245 @@
+/*
+ * 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.
+ */
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/CL/CLTensor.h"
+#include "arm_compute/runtime/CL/CLTensorAllocator.h"
+#include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
+#include "framework/Asserts.h"
+#include "framework/Macros.h"
+#include "framework/datasets/Datasets.h"
+#include "tests/CL/CLAccessor.h"
+#include "tests/PaddingCalculator.h"
+#include "tests/datasets_new/ActivationFunctionsDataset.h"
+#include "tests/datasets_new/ShapeDatasets.h"
+#include "tests/validation_new/Validation.h"
+#include "tests/validation_new/fixtures/ActivationLayerFixture.h"
+#include "tests/validation_new/half.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+/** Define tolerance of the activation layer.
+ *
+ * @param[in] activation The activation function used.
+ * @param[in] data_type  Data type.
+ *
+ * @return Tolerance depending on the activation function.
+ */
+float tolerance(ActivationLayerInfo::ActivationFunction activation, DataType data_type)
+{
+    switch(activation)
+    {
+        case ActivationLayerInfo::ActivationFunction::LINEAR:
+            return data_type == DataType::F16 ? 0.2f : 0.f;
+        case ActivationLayerInfo::ActivationFunction::SQUARE:
+            return data_type == DataType::F16 ? 0.1f : 0.f;
+        case ActivationLayerInfo::ActivationFunction::LOGISTIC:
+            if(is_data_type_fixed_point(data_type))
+            {
+                return 5.f;
+            }
+            else
+            {
+                return data_type == DataType::F16 ? 0.001f : 0.f;
+            }
+        case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
+            return data_type == DataType::F16 ? 0.00001f : 0.f;
+        case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
+        case ActivationLayerInfo::ActivationFunction::SQRT:
+            if(is_data_type_fixed_point(data_type))
+            {
+                return 5.f;
+            }
+            else
+            {
+                return data_type == DataType::F16 ? 0.01f : 0.00001f;
+            }
+        case ActivationLayerInfo::ActivationFunction::TANH:
+            if(is_data_type_fixed_point(data_type))
+            {
+                return 5.f;
+            }
+            else
+            {
+                return data_type == DataType::F16 ? 0.001f : 0.00001f;
+            }
+        default:
+            return 0.f;
+    }
+}
+
+/** CNN data types */
+const auto CNNDataTypes = framework::dataset::make("DataType",
+{
+    DataType::F16,
+    DataType::F32,
+    DataType::QS8,
+    DataType::QS16,
+});
+
+/** Input data sets. */
+const auto ActivationDataset = combine(combine(framework::dataset::make("InPlace", { false, true }), datasets::ActivationFunctions()), framework::dataset::make("AlphaBeta", { 0.5f, 1.f }));
+} // namespace
+
+TEST_SUITE(CL)
+TEST_SUITE(ActivationLayer)
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), CNNDataTypes), framework::dataset::make("InPlace", { false, true })),
+               shape, data_type, in_place)
+{
+    // Set fixed point position data type allowed
+    const int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
+
+    // Create tensors
+    CLTensor src = create_tensor<CLTensor>(shape, data_type, 1, fixed_point_position);
+    CLTensor dst = create_tensor<CLTensor>(shape, data_type, 1, fixed_point_position);
+
+    ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+    // Create and configure function
+    CLActivationLayer act_layer;
+
+    if(in_place)
+    {
+        act_layer.configure(&src, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS));
+    }
+    else
+    {
+        act_layer.configure(&src, &dst, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS));
+    }
+
+    // Validate valid region
+    const ValidRegion valid_region = shape_to_valid_region(shape);
+    validate(src.info()->valid_region(), valid_region);
+
+    if(!in_place)
+    {
+        validate(dst.info()->valid_region(), valid_region);
+    }
+
+    // Validate padding
+    const int         step    = 16 / arm_compute::data_size_from_type(data_type);
+    const PaddingSize padding = PaddingCalculator(shape.x(), step).required_padding();
+    validate(src.info()->padding(), padding);
+
+    if(!in_place)
+    {
+        validate(dst.info()->padding(), padding);
+    }
+}
+
+template <typename T>
+using CLActivationLayerFixture = ActivationValidationFixture<CLTensor, CLAccessor, CLActivationLayer, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLActivationLayerFixture<half_float::half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), ActivationDataset),
+                                                                                                                        framework::dataset::make("DataType",
+                                                                                                                                DataType::F16)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, CLActivationLayerFixture<half_float::half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), ActivationDataset),
+                                                                                                                      framework::dataset::make("DataType",
+                                                                                                                              DataType::F16)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
+}
+TEST_SUITE_END()
+
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLActivationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), ActivationDataset), framework::dataset::make("DataType",
+                                                                                                             DataType::F32)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, CLActivationLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), ActivationDataset), framework::dataset::make("DataType",
+                                                                                                           DataType::F32)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+
+template <typename T>
+using CLActivationLayerFixedPointFixture = ActivationValidationFixedPointFixture<CLTensor, CLAccessor, CLActivationLayer, T>;
+
+TEST_SUITE(Quantized)
+TEST_SUITE(QS8)
+// We test for fixed point precision [3,5] because [1,2] and [6,7] ranges cause
+// overflowing issues in most of the transcendentals functions.
+FIXTURE_DATA_TEST_CASE(RunSmall, CLActivationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), ActivationDataset),
+                                                                                                                        framework::dataset::make("DataType",
+                                                                                                                                DataType::QS8)),
+                                                                                                                        framework::dataset::make("FractionalBits", 3, 6)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, CLActivationLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), ActivationDataset),
+                                                                                                                      framework::dataset::make("DataType",
+                                                                                                                              DataType::QS8)),
+                                                                                                                      framework::dataset::make("FractionalBits", 3, 6)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
+}
+TEST_SUITE_END()
+
+TEST_SUITE(QS16)
+// Testing for fixed point position [1,14) as reciprocal limits the maximum fixed point position to 14
+FIXTURE_DATA_TEST_CASE(RunSmall, CLActivationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), ActivationDataset),
+                       framework::dataset::make("DataType",
+                                                DataType::QS16)),
+                       framework::dataset::make("FractionalBits", 1, 14)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, CLActivationLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), ActivationDataset),
+                                                                                                                       framework::dataset::make("DataType",
+                                                                                                                               DataType::QS16)),
+                                                                                                                       framework::dataset::make("FractionalBits", 1, 14)))
+{
+    // Validate output
+    validate(CLAccessor(_target), _reference, tolerance(_function, _data_type));
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+
+TEST_SUITE_END()
+TEST_SUITE_END()
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation_new/CPP/ActivationLayer.cpp b/tests/validation_new/CPP/ActivationLayer.cpp
new file mode 100644
index 0000000000..052c3aa566
--- /dev/null
+++ b/tests/validation_new/CPP/ActivationLayer.cpp
@@ -0,0 +1,158 @@
+/*
+ * 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.
+ */
+#include "ActivationLayer.h"
+
+#include "tests/validation_new/FixedPoint.h"
+#include "tests/validation_new/Helpers.h"
+#include "tests/validation_new/half.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type>
+SimpleTensor<T> activation_layer(const SimpleTensor<T> &src, ActivationLayerInfo info)
+{
+    // Create reference
+    SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
+
+    // Compute reference
+    const T a(info.a());
+    const T b(info.b());
+
+    for(int i = 0; i < src.num_elements(); ++i)
+    {
+        T x = src[i];
+
+        switch(info.activation())
+        {
+            case ActivationLayerInfo::ActivationFunction::ABS:
+                dst[i] = std::abs(x);
+                break;
+            case ActivationLayerInfo::ActivationFunction::LINEAR:
+                dst[i] = a * x + b;
+                break;
+            case ActivationLayerInfo::ActivationFunction::LOGISTIC:
+                dst[i] = static_cast<T>(1) / (static_cast<T>(1) + std::exp(-x));
+                break;
+            case ActivationLayerInfo::ActivationFunction::RELU:
+                dst[i] = std::max<T>(static_cast<T>(0), x);
+                break;
+            case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
+                dst[i] = std::min<T>(a, std::max(static_cast<T>(0), x));
+                break;
+            case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
+                dst[i] = (x > 0) ? x : a * x;
+                break;
+            case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
+                dst[i] = std::log(static_cast<T>(1) + std::exp(x));
+                break;
+            case ActivationLayerInfo::ActivationFunction::SQRT:
+                dst[i] = std::sqrt(x);
+                break;
+            case ActivationLayerInfo::ActivationFunction::SQUARE:
+                dst[i] = x * x;
+                break;
+            case ActivationLayerInfo::ActivationFunction::TANH:
+                dst[i] = a * std::tanh(b * x);
+                break;
+            default:
+                ARM_COMPUTE_ERROR("Unsupported activation function");
+        }
+    }
+
+    return dst;
+}
+
+template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type>
+SimpleTensor<T> activation_layer(const SimpleTensor<T> &src, ActivationLayerInfo info)
+{
+    using namespace fixed_point_arithmetic;
+
+    // Create reference
+    SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
+
+    // Compute reference
+    const int            fixed_point_position = src.fixed_point_position();
+    const fixed_point<T> a(info.a(), fixed_point_position);
+    const fixed_point<T> b(info.b(), fixed_point_position);
+    const fixed_point<T> const_0(0, fixed_point_position);
+    const fixed_point<T> const_1(1, fixed_point_position);
+
+    for(int i = 0; i < src.num_elements(); ++i)
+    {
+        fixed_point<T> x(src[i], fixed_point_position, true);
+
+        switch(info.activation())
+        {
+            case ActivationLayerInfo::ActivationFunction::ABS:
+                dst[i] = abs(x).raw();
+                break;
+            case ActivationLayerInfo::ActivationFunction::LINEAR:
+                dst[i] = add(b, mul(a, x)).raw();
+                break;
+            case ActivationLayerInfo::ActivationFunction::LOGISTIC:
+                dst[i] = (const_1 / (const_1 + exp(-x))).raw();
+                break;
+            case ActivationLayerInfo::ActivationFunction::RELU:
+                dst[i] = max(const_0, x).raw();
+                break;
+            case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
+                dst[i] = min(a, max(const_0, x)).raw();
+                break;
+            case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
+                dst[i] = (x > const_0) ? x.raw() : mul(a, x).raw();
+                break;
+            case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
+                dst[i] = log(const_1 + exp(x)).raw();
+                break;
+            case ActivationLayerInfo::ActivationFunction::SQRT:
+                dst[i] = (const_1 / inv_sqrt(x)).raw();
+                break;
+            case ActivationLayerInfo::ActivationFunction::SQUARE:
+                dst[i] = mul(x, x).raw();
+                break;
+            case ActivationLayerInfo::ActivationFunction::TANH:
+                dst[i] = mul(a, tanh(mul(b, x))).raw();
+                break;
+            default:
+                ARM_COMPUTE_ERROR("Unsupported activation function");
+        }
+    }
+
+    return dst;
+}
+
+template SimpleTensor<float> activation_layer(const SimpleTensor<float> &src, ActivationLayerInfo info);
+template SimpleTensor<half_float::half> activation_layer(const SimpleTensor<half_float::half> &src, ActivationLayerInfo info);
+template SimpleTensor<qint8_t> activation_layer(const SimpleTensor<qint8_t> &src, ActivationLayerInfo info);
+template SimpleTensor<qint16_t> activation_layer(const SimpleTensor<qint16_t> &src, ActivationLayerInfo info);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation_new/CPP/ActivationLayer.h b/tests/validation_new/CPP/ActivationLayer.h
new file mode 100644
index 0000000000..5f4ef46827
--- /dev/null
+++ b/tests/validation_new/CPP/ActivationLayer.h
@@ -0,0 +1,47 @@
+/*
+ * 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_H__
+#define __ARM_COMPUTE_TEST_ACTIVATION_LAYER_H__
+
+#include "tests/validation_new/Helpers.h"
+#include "tests/validation_new/SimpleTensor.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace reference
+{
+template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type = 0>
+SimpleTensor<T> activation_layer(const SimpleTensor<T> &src, ActivationLayerInfo info);
+
+template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type = 0>
+SimpleTensor<T> activation_layer(const SimpleTensor<T> &src, ActivationLayerInfo info);
+} // namespace reference
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_TEST_ACTIVATION_LAYER_H__ */
diff --git a/tests/validation_new/Helpers.h b/tests/validation_new/Helpers.h
index e25b684c11..3058b8eaee 100644
--- a/tests/validation_new/Helpers.h
+++ b/tests/validation_new/Helpers.h
@@ -24,9 +24,13 @@
 #ifndef __ARM_COMPUTE_TEST_VALIDATION_HELPERS_H__
 #define __ARM_COMPUTE_TEST_VALIDATION_HELPERS_H__
 
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Utils.h"
 #include "tests/validation/half.h"
 
+#include <random>
 #include <type_traits>
+#include <utility>
 
 namespace arm_compute
 {
@@ -43,6 +47,87 @@ template <>
 struct is_floating_point<half_float::half> : public std::true_type
 {
 };
+
+/** Helper function to get the testing range for each activation layer.
+ *
+ * @param[in] activation           Activation function to test.
+ * @param[in] data_type            Data type.
+ * @param[in] fixed_point_position Number of bits for the fractional part. Defaults to 1.
+ *
+ * @return A pair containing the lower upper testing bounds for a given function.
+ */
+template <typename T>
+std::pair<T, T> get_activation_layer_test_bounds(ActivationLayerInfo::ActivationFunction activation, DataType data_type, int fixed_point_position = 0)
+{
+    std::pair<T, T> bounds;
+
+    switch(data_type)
+    {
+        case DataType::F16:
+        {
+            using namespace half_float::literal;
+
+            switch(activation)
+            {
+                case ActivationLayerInfo::ActivationFunction::SQUARE:
+                case ActivationLayerInfo::ActivationFunction::LOGISTIC:
+                case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
+                    // Reduce range as exponent overflows
+                    bounds = std::make_pair(-10._h, 10._h);
+                    break;
+                case ActivationLayerInfo::ActivationFunction::SQRT:
+                    // Reduce range as sqrt should take a non-negative number
+                    bounds = std::make_pair(0._h, 255._h);
+                    break;
+                default:
+                    bounds = std::make_pair(-255._h, 255._h);
+                    break;
+            }
+            break;
+        }
+        case DataType::F32:
+            switch(activation)
+            {
+                case ActivationLayerInfo::ActivationFunction::LOGISTIC:
+                case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
+                    // Reduce range as exponent overflows
+                    bounds = std::make_pair(-40.f, 40.f);
+                    break;
+                case ActivationLayerInfo::ActivationFunction::SQRT:
+                    // Reduce range as sqrt should take a non-negative number
+                    bounds = std::make_pair(0.f, 255.f);
+                    break;
+                default:
+                    bounds = std::make_pair(-255.f, 255.f);
+                    break;
+            }
+            break;
+        case DataType::QS8:
+        case DataType::QS16:
+            switch(activation)
+            {
+                case ActivationLayerInfo::ActivationFunction::LOGISTIC:
+                case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
+                case ActivationLayerInfo::ActivationFunction::TANH:
+                    // Reduce range as exponent overflows
+                    bounds = std::make_pair(-(1 << fixed_point_position), 1 << fixed_point_position);
+                    break;
+                case ActivationLayerInfo::ActivationFunction::SQRT:
+                    // Reduce range as sqrt should take a non-negative number
+                    // Can't be zero either as inv_sqrt is used in NEON.
+                    bounds = std::make_pair(1, std::numeric_limits<T>::max());
+                    break;
+                default:
+                    bounds = std::make_pair(std::numeric_limits<T>::lowest(), std::numeric_limits<T>::max());
+                    break;
+            }
+            break;
+        default:
+            ARM_COMPUTE_ERROR("Unsupported data type");
+    }
+
+    return bounds;
+}
 } // namespace validation
 } // namespace test
 } // namespace arm_compute
diff --git a/tests/validation_new/NEON/ActivationLayer.cpp b/tests/validation_new/NEON/ActivationLayer.cpp
new file mode 100644
index 0000000000..db0faaecdf
--- /dev/null
+++ b/tests/validation_new/NEON/ActivationLayer.cpp
@@ -0,0 +1,230 @@
+/*
+ * 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.
+ */
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+#include "framework/Asserts.h"
+#include "framework/Macros.h"
+#include "framework/datasets/Datasets.h"
+#include "tests/NEON/Accessor.h"
+#include "tests/PaddingCalculator.h"
+#include "tests/datasets_new/ActivationFunctionsDataset.h"
+#include "tests/datasets_new/ShapeDatasets.h"
+#include "tests/validation_new/Validation.h"
+#include "tests/validation_new/fixtures/ActivationLayerFixture.h"
+#include "tests/validation_new/half.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+/** Define tolerance of the activation layer.
+ *
+ * @param[in] data_type  The data type used.
+ * @param[in] activation The activation function used.
+ *
+ * @return Tolerance depending on the activation function.
+ */
+float tolerance(DataType data_type, ActivationLayerInfo::ActivationFunction activation)
+{
+    switch(activation)
+    {
+        case ActivationLayerInfo::ActivationFunction::LOGISTIC:
+        case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
+        case ActivationLayerInfo::ActivationFunction::SQRT:
+        case ActivationLayerInfo::ActivationFunction::TANH:
+            switch(data_type)
+            {
+                case DataType::QS8:
+                    return 5.f;
+                case DataType::QS16:
+                    return 11.f;
+                case DataType::F16:
+                    return 0.01f;
+                default:
+                    return 0.00001f;
+            }
+            break;
+        default:
+            return 0.f;
+    }
+}
+
+/** CNN data types */
+const auto CNNDataTypes = framework::dataset::make("DataType",
+{
+#ifdef ARM_COMPUTE_ENABLE_FP16
+    DataType::F16,
+#endif /* ARM_COMPUTE_ENABLE_FP16 */
+    DataType::F32,
+    DataType::QS8,
+    DataType::QS16,
+});
+
+/** Input data sets. */
+const auto ActivationDataset = combine(combine(framework::dataset::make("InPlace", { false, true }), datasets::ActivationFunctions()), framework::dataset::make("AlphaBeta", { 0.5f, 1.f }));
+} // namespace
+
+TEST_SUITE(NEON)
+TEST_SUITE(ActivationLayer)
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(concat(datasets::SmallShapes(), datasets::LargeShapes()), CNNDataTypes), framework::dataset::make("InPlace", { false, true })),
+               shape, data_type, in_place)
+{
+    // Set fixed point position data type allowed
+    const int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
+
+    // Create tensors
+    Tensor src = create_tensor<Tensor>(shape, data_type, 1, fixed_point_position);
+    Tensor dst = create_tensor<Tensor>(shape, data_type, 1, fixed_point_position);
+
+    ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+    // Create and configure function
+    NEActivationLayer act_layer;
+
+    if(in_place)
+    {
+        act_layer.configure(&src, nullptr, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS));
+    }
+    else
+    {
+        act_layer.configure(&src, &dst, ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::ABS));
+    }
+
+    // Validate valid region
+    const ValidRegion valid_region = shape_to_valid_region(shape);
+    validate(src.info()->valid_region(), valid_region);
+
+    if(!in_place)
+    {
+        validate(dst.info()->valid_region(), valid_region);
+    }
+
+    // Validate padding
+    const PaddingSize padding = PaddingCalculator(shape.x(), 16).required_padding();
+    validate(src.info()->padding(), padding);
+
+    if(!in_place)
+    {
+        validate(dst.info()->padding(), padding);
+    }
+}
+
+template <typename T>
+using NEActivationLayerFixture = ActivationValidationFixture<Tensor, Accessor, NEActivationLayer, T>;
+
+TEST_SUITE(Float)
+#ifdef ARM_COMPUTE_ENABLE_FP16
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEActivationLayerFixture<half_float::half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), ActivationDataset),
+                                                                                                                        framework::dataset::make("DataType",
+                                                                                                                                DataType::F16)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance(_data_type, _function));
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NEActivationLayerFixture<half_float::half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), ActivationDataset),
+                                                                                                                      framework::dataset::make("DataType",
+                                                                                                                              DataType::F16)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance(_data_type, _function));
+}
+TEST_SUITE_END()
+#endif /* ARM_COMPUTE_ENABLE_FP16 */
+
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEActivationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), ActivationDataset), framework::dataset::make("DataType",
+                                                                                                             DataType::F32)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance(_data_type, _function));
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NEActivationLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), ActivationDataset), framework::dataset::make("DataType",
+                                                                                                           DataType::F32)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance(_data_type, _function));
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+
+template <typename T>
+using NEActivationLayerFixedPointFixture = ActivationValidationFixedPointFixture<Tensor, Accessor, NEActivationLayer, T>;
+
+TEST_SUITE(Quantized)
+TEST_SUITE(QS8)
+// We test for fixed point precision [3,5] because [1,2] and [6,7] ranges cause
+// overflowing issues in most of the transcendentals functions.
+FIXTURE_DATA_TEST_CASE(RunSmall, NEActivationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), ActivationDataset),
+                                                                                                                        framework::dataset::make("DataType",
+                                                                                                                                DataType::QS8)),
+                                                                                                                        framework::dataset::make("FractionalBits", 3, 6)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance(_data_type, _function));
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NEActivationLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), ActivationDataset),
+                                                                                                                      framework::dataset::make("DataType",
+                                                                                                                              DataType::QS8)),
+                                                                                                                      framework::dataset::make("FractionalBits", 3, 6)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance(_data_type, _function));
+}
+TEST_SUITE_END()
+
+TEST_SUITE(QS16)
+// Testing for fixed point position [1,14) as reciprocal limits the maximum fixed point position to 14
+FIXTURE_DATA_TEST_CASE(RunSmall, NEActivationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), ActivationDataset),
+                       framework::dataset::make("DataType",
+                                                DataType::QS16)),
+                       framework::dataset::make("FractionalBits", 1, 14)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance(_data_type, _function));
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NEActivationLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), ActivationDataset),
+                                                                                                                       framework::dataset::make("DataType",
+                                                                                                                               DataType::QS16)),
+                                                                                                                       framework::dataset::make("FractionalBits", 1, 14)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference, tolerance(_data_type, _function));
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+
+TEST_SUITE_END()
+TEST_SUITE_END()
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation_new/fixtures/ActivationLayerFixture.h b/tests/validation_new/fixtures/ActivationLayerFixture.h
new file mode 100644
index 0000000000..bf0e7ba6ea
--- /dev/null
+++ b/tests/validation_new/fixtures/ActivationLayerFixture.h
@@ -0,0 +1,157 @@
+/*
+ * 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_FIXTURE
+#define ARM_COMPUTE_TEST_ACTIVATION_LAYER_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "framework/Asserts.h"
+#include "framework/Fixture.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/validation_new/CPP/ActivationLayer.h"
+#include "tests/validation_new/Helpers.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class ActivationValidationFixedPointFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, bool in_place, ActivationLayerInfo::ActivationFunction function, float alpha_beta, DataType data_type, int fractional_bits)
+    {
+        _fractional_bits = fractional_bits;
+        _data_type       = data_type;
+        _function        = function;
+
+        ActivationLayerInfo info(function, alpha_beta, alpha_beta);
+
+        _target    = compute_target(shape, in_place, info, data_type, fractional_bits);
+        _reference = compute_reference(shape, info, data_type, fractional_bits);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        if(is_data_type_float(_data_type))
+        {
+            float min_bound = 0;
+            float max_bound = 0;
+            std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<T>(_function, _data_type);
+            std::uniform_real_distribution<> distribution(min_bound, max_bound);
+            library->fill(tensor, distribution, 0);
+        }
+        else
+        {
+            int min_bound = 0;
+            int max_bound = 0;
+            std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<T>(_function, _data_type, _fractional_bits);
+            std::uniform_int_distribution<> distribution(min_bound, max_bound);
+            library->fill(tensor, distribution, 0);
+        }
+    }
+
+    TensorType compute_target(const TensorShape &shape, bool in_place, ActivationLayerInfo info, DataType data_type, int fixed_point_position = 0)
+    {
+        // Create tensors
+        TensorType src = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position);
+        TensorType dst = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position);
+
+        // Create and configure function
+        FunctionType act_layer;
+
+        TensorType *dst_ptr = in_place ? &src : &dst;
+
+        act_layer.configure(&src, dst_ptr, info);
+
+        ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        src.allocator()->allocate();
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        if(!in_place)
+        {
+            dst.allocator()->allocate();
+            ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+        }
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        act_layer.run();
+
+        if(in_place)
+        {
+            return src;
+        }
+        else
+        {
+            return dst;
+        }
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, ActivationLayerInfo info, DataType data_type, int fixed_point_position = 0)
+    {
+        // Create reference
+        SimpleTensor<T> src{ shape, data_type, 1, fixed_point_position };
+
+        // Fill reference
+        fill(src);
+
+        return reference::activation_layer<T>(src, info);
+    }
+
+    TensorType                              _target{};
+    SimpleTensor<T>                         _reference{};
+    int                                     _fractional_bits{};
+    DataType                                _data_type{};
+    ActivationLayerInfo::ActivationFunction _function{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class ActivationValidationFixture : public ActivationValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, bool in_place, ActivationLayerInfo::ActivationFunction function, float alpha_beta, DataType data_type)
+    {
+        ActivationValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, in_place, function, alpha_beta, data_type, 0);
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_ACTIVATION_LAYER_FIXTURE */