COMPMID-415: Rename and move tests

The boost validation is now "standalone" in validation_old and builds as
arm_compute_validation_old. The new validation builds now as
arm_compute_validation.

Change-Id: Ib93ba848a25680ac60afb92b461d574a0757150d
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/86187
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

22 files changed, 2904 insertions, 0 deletions

diff --git a/tests/validation/fixtures/ActivationLayerFixture.h b/tests/validation/fixtures/ActivationLayerFixture.h
new file mode 100644
index 0000000000..384e63bf49
--- /dev/null
+++ b/tests/validation/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 "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/ActivationLayer.h"
+#include "tests/validation/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 */
diff --git a/tests/validation/fixtures/BitwiseAndFixture.h b/tests/validation/fixtures/BitwiseAndFixture.h
new file mode 100644
index 0000000000..0dfff868ab
--- /dev/null
+++ b/tests/validation/fixtures/BitwiseAndFixture.h
@@ -0,0 +1,113 @@
+/*
+ * 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_BITWISE_AND_FIXTURE
+#define ARM_COMPUTE_TEST_BITWISE_AND_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/BitwiseAnd.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class BitwiseAndValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type)
+    {
+        _target    = compute_target(shape, data_type);
+        _reference = compute_reference(shape, data_type);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        library->fill_tensor_uniform(tensor, i);
+    }
+
+    TensorType compute_target(const TensorShape &shape, DataType data_type)
+    {
+        // Create tensors
+        TensorType src1 = create_tensor<TensorType>(shape, data_type);
+        TensorType src2 = create_tensor<TensorType>(shape, data_type);
+        TensorType dst  = create_tensor<TensorType>(shape, data_type);
+
+        // Create and configure function
+        FunctionType bitwise_and;
+
+        bitwise_and.configure(&src1, &src2, &dst);
+
+        ARM_COMPUTE_EXPECT(src1.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(src2.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        src1.allocator()->allocate();
+        src2.allocator()->allocate();
+        dst.allocator()->allocate();
+        ARM_COMPUTE_EXPECT(!src1.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!src2.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src1), 0);
+        fill(AccessorType(src2), 1);
+
+        // Compute function
+        bitwise_and.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type)
+    {
+        // Create reference
+        SimpleTensor<T> src1{ shape, data_type };
+        SimpleTensor<T> src2{ shape, data_type };
+
+        // Fill reference
+        fill(src1, 0);
+        fill(src2, 1);
+
+        return reference::bitwise_and<T>(src1, src2);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_BITWISE_AND_FIXTURE */
diff --git a/tests/validation/fixtures/BitwiseNotFixture.h b/tests/validation/fixtures/BitwiseNotFixture.h
new file mode 100644
index 0000000000..e5bf69992e
--- /dev/null
+++ b/tests/validation/fixtures/BitwiseNotFixture.h
@@ -0,0 +1,106 @@
+/*
+ * 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_BITWISE_NOT_FIXTURE
+#define ARM_COMPUTE_TEST_BITWISE_NOT_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/BitwiseNot.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class BitwiseNotValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type)
+    {
+        _target    = compute_target(shape, data_type);
+        _reference = compute_reference(shape, data_type);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        library->fill_tensor_uniform(tensor, 0);
+    }
+
+    TensorType compute_target(const TensorShape &shape, DataType data_type)
+    {
+        // Create tensors
+        TensorType src = create_tensor<TensorType>(shape, data_type);
+        TensorType dst = create_tensor<TensorType>(shape, data_type);
+
+        // Create and configure function
+        FunctionType bitwise_not;
+
+        bitwise_not.configure(&src, &dst);
+
+        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();
+        dst.allocator()->allocate();
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        bitwise_not.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type)
+    {
+        // Create reference
+        SimpleTensor<T> src{ shape, data_type };
+
+        // Fill reference
+        fill(src);
+
+        return reference::bitwise_not<T>(src);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_BITWISE_NOT_FIXTURE */
diff --git a/tests/validation/fixtures/BitwiseOrFixture.h b/tests/validation/fixtures/BitwiseOrFixture.h
new file mode 100644
index 0000000000..d61e767bf3
--- /dev/null
+++ b/tests/validation/fixtures/BitwiseOrFixture.h
@@ -0,0 +1,113 @@
+/*
+ * 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_BITWISE_OR_FIXTURE
+#define ARM_COMPUTE_TEST_BITWISE_OR_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/BitwiseOr.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class BitwiseOrValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type)
+    {
+        _target    = compute_target(shape, data_type);
+        _reference = compute_reference(shape, data_type);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        library->fill_tensor_uniform(tensor, i);
+    }
+
+    TensorType compute_target(const TensorShape &shape, DataType data_type)
+    {
+        // Create tensors
+        TensorType src1 = create_tensor<TensorType>(shape, data_type);
+        TensorType src2 = create_tensor<TensorType>(shape, data_type);
+        TensorType dst  = create_tensor<TensorType>(shape, data_type);
+
+        // Create and configure function
+        FunctionType bitwise_or;
+
+        bitwise_or.configure(&src1, &src2, &dst);
+
+        ARM_COMPUTE_EXPECT(src1.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(src2.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        src1.allocator()->allocate();
+        src2.allocator()->allocate();
+        dst.allocator()->allocate();
+        ARM_COMPUTE_EXPECT(!src1.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!src2.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src1), 0);
+        fill(AccessorType(src2), 1);
+
+        // Compute function
+        bitwise_or.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type)
+    {
+        // Create reference
+        SimpleTensor<T> src1{ shape, data_type };
+        SimpleTensor<T> src2{ shape, data_type };
+
+        // Fill reference
+        fill(src1, 0);
+        fill(src2, 1);
+
+        return reference::bitwise_or<T>(src1, src2);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_BITWISE_OR_FIXTURE */
diff --git a/tests/validation/fixtures/BitwiseXorFixture.h b/tests/validation/fixtures/BitwiseXorFixture.h
new file mode 100644
index 0000000000..16fa8c0422
--- /dev/null
+++ b/tests/validation/fixtures/BitwiseXorFixture.h
@@ -0,0 +1,113 @@
+/*
+ * 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_BITWISE_XOR_FIXTURE
+#define ARM_COMPUTE_TEST_BITWISE_XOR_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/BitwiseXor.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class BitwiseXorValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type)
+    {
+        _target    = compute_target(shape, data_type);
+        _reference = compute_reference(shape, data_type);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        library->fill_tensor_uniform(tensor, i);
+    }
+
+    TensorType compute_target(const TensorShape &shape, DataType data_type)
+    {
+        // Create tensors
+        TensorType src1 = create_tensor<TensorType>(shape, data_type);
+        TensorType src2 = create_tensor<TensorType>(shape, data_type);
+        TensorType dst  = create_tensor<TensorType>(shape, data_type);
+
+        // Create and configure function
+        FunctionType bitwise_xor;
+
+        bitwise_xor.configure(&src1, &src2, &dst);
+
+        ARM_COMPUTE_EXPECT(src1.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(src2.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        src1.allocator()->allocate();
+        src2.allocator()->allocate();
+        dst.allocator()->allocate();
+        ARM_COMPUTE_EXPECT(!src1.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!src2.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src1), 0);
+        fill(AccessorType(src2), 1);
+
+        // Compute function
+        bitwise_xor.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type)
+    {
+        // Create reference
+        SimpleTensor<T> src1{ shape, data_type };
+        SimpleTensor<T> src2{ shape, data_type };
+
+        // Fill reference
+        fill(src1, 0);
+        fill(src2, 1);
+
+        return reference::bitwise_xor<T>(src1, src2);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_BITWISE_XOR_FIXTURE */
diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h
new file mode 100644
index 0000000000..87b11ac130
--- /dev/null
+++ b/tests/validation/fixtures/ConvolutionLayerFixture.h
@@ -0,0 +1,152 @@
+/*
+ * 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_CONVOLUTION_LAYER_FIXTURE
+#define ARM_COMPUTE_TEST_CONVOLUTION_LAYER_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/ConvolutionLayer.h"
+#include "tests/validation/Helpers.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class ConvolutionValidationFixedPointFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, DataType data_type, int fractional_bits)
+    {
+        _fractional_bits = fractional_bits;
+        _data_type       = data_type;
+
+        _target    = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, fractional_bits);
+        _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, fractional_bits);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        switch(tensor.data_type())
+        {
+            case DataType::F16:
+            case DataType::F32:
+            {
+                std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
+                library->fill(tensor, distribution, i);
+                break;
+            }
+            default:
+                library->fill_tensor_uniform(tensor, i);
+        }
+    }
+
+    TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
+                              DataType data_type, int fixed_point_position)
+    {
+        // Create tensors
+        TensorType src     = create_tensor<TensorType>(input_shape, data_type, 1, fixed_point_position);
+        TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, fixed_point_position);
+        TensorType bias    = create_tensor<TensorType>(bias_shape, data_type, 1, fixed_point_position);
+        TensorType dst     = create_tensor<TensorType>(output_shape, data_type, 1, fixed_point_position);
+
+        // Create and configure function
+        FunctionType conv;
+        conv.configure(&src, &weights, &bias, &dst, info);
+
+        ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        src.allocator()->allocate();
+        weights.allocator()->allocate();
+        bias.allocator()->allocate();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!weights.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!bias.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src), 0);
+        fill(AccessorType(weights), 1);
+        fill(AccessorType(bias), 2);
+
+        // Compute NEConvolutionLayer function
+        conv.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
+                                      DataType data_type, int fixed_point_position)
+    {
+        // Create reference
+        SimpleTensor<T> src{ input_shape, data_type, 1, fixed_point_position };
+        SimpleTensor<T> weights{ weights_shape, data_type, 1, fixed_point_position };
+        SimpleTensor<T> bias{ bias_shape, data_type, 1, fixed_point_position };
+
+        // Fill reference
+        fill(src, 0);
+        fill(weights, 1);
+        fill(bias, 2);
+
+        return reference::convolution_layer<T>(src, weights, bias, output_shape, info);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+    int             _fractional_bits{};
+    DataType        _data_type{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class ConvolutionValidationFixture : public ConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, DataType data_type)
+    {
+        ConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, data_type, 0);
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_CONVOLUTION_LAYER_FIXTURE */
diff --git a/tests/validation/fixtures/DepthConcatenateLayerFixture.h b/tests/validation/fixtures/DepthConcatenateLayerFixture.h
new file mode 100644
index 0000000000..2a2e96e821
--- /dev/null
+++ b/tests/validation/fixtures/DepthConcatenateLayerFixture.h
@@ -0,0 +1,177 @@
+/*
+ * 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_DEPTHCONCATENATE_LAYER_FIXTURE
+#define ARM_COMPUTE_TEST_DEPTHCONCATENATE_LAYER_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/DepthConcatenateLayer.h"
+#include "tests/validation/Helpers.h"
+
+#include <random>
+
+namespace arm_compute
+{
+class ITensor;
+class Tensor;
+class ICLTensor;
+class CLTensor;
+
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DepthConcatenateValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type)
+    {
+        // Create input shapes
+        std::mt19937                    gen(library->seed());
+        std::uniform_int_distribution<> num_dis(2, 6);
+        const int                       num_tensors = num_dis(gen);
+
+        std::vector<TensorShape>         shapes(num_tensors, shape);
+        std::uniform_int_distribution<>  depth_dis(1, 7);
+        std::bernoulli_distribution      mutate_dis(0.25f);
+        std::uniform_real_distribution<> change_dis(-0.25f, 0.f);
+
+        // Generate more shapes based on the input
+        for(auto &s : shapes)
+        {
+            // Set the depth of the tensor
+            s.set(2, depth_dis(gen));
+
+            // Randomly change the first dimension
+            if(mutate_dis(gen))
+            {
+                // Decrease the dimension by a small percentage. Don't increase
+                // as that could make tensor too large. Also the change must be
+                // an even number. Otherwise out depth concatenate fails.
+                s.set(0, s[0] + 2 * static_cast<int>(s[0] * change_dis(gen)));
+            }
+
+            // Repeat the same as above for the second dimension
+            if(mutate_dis(gen))
+            {
+                s.set(1, s[1] + 2 * static_cast<int>(s[1] * change_dis(gen)));
+            }
+        }
+
+        _target    = compute_target(shapes, data_type);
+        _reference = compute_reference(shapes, data_type);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        library->fill_tensor_uniform(tensor, i);
+    }
+
+    TensorType compute_target(std::vector<TensorShape> shapes, DataType data_type)
+    {
+        using ITensorType = typename std::conditional<std::is_same<TensorType, Tensor>::value, ITensor, ICLTensor>::type;
+
+        std::vector<TensorType>    srcs;
+        std::vector<ITensorType *> src_ptrs;
+
+        // Create tensors
+        srcs.reserve(shapes.size());
+
+        for(const auto &shape : shapes)
+        {
+            srcs.emplace_back(create_tensor<TensorType>(shape, data_type, 1, _fractional_bits));
+            src_ptrs.emplace_back(&srcs.back());
+        }
+
+        TensorShape dst_shape = calculate_depth_concatenate_shape(shapes);
+        TensorType  dst       = create_tensor<TensorType>(dst_shape, data_type, 1, _fractional_bits);
+
+        // Create and configure function
+        FunctionType depth_concat;
+        depth_concat.configure(src_ptrs, &dst);
+
+        for(auto &src : srcs)
+        {
+            ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        }
+
+        ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        for(auto &src : srcs)
+        {
+            src.allocator()->allocate();
+            ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        }
+
+        dst.allocator()->allocate();
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        int i = 0;
+        for(auto &src : srcs)
+        {
+            fill(AccessorType(src), i++);
+        }
+
+        // Compute function
+        depth_concat.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(std::vector<TensorShape> shapes, DataType data_type)
+    {
+        std::vector<SimpleTensor<T>> srcs;
+
+        // Create and fill tensors
+        int i = 0;
+        for(const auto &shape : shapes)
+        {
+            srcs.emplace_back(shape, data_type, 1, _fractional_bits);
+            fill(srcs.back(), i++);
+        }
+
+        return reference::depthconcatenate_layer<T>(srcs);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+
+private:
+    int _fractional_bits{ 1 };
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_DEPTHCONCATENATE_LAYER_FIXTURE */
diff --git a/tests/validation/fixtures/DepthwiseConvolutionFixture.h b/tests/validation/fixtures/DepthwiseConvolutionFixture.h
new file mode 100644
index 0000000000..462c0f888c
--- /dev/null
+++ b/tests/validation/fixtures/DepthwiseConvolutionFixture.h
@@ -0,0 +1,120 @@
+/*
+ * 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_DEPTHWISE_CONVOLUTION_FIXTURE
+#define ARM_COMPUTE_TEST_DEPTHWISE_CONVOLUTION_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/DepthwiseConvolution.h"
+#include "tests/validation/Helpers.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DepthwiseConvolutionValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape in_shape, TensorShape weights_shape, TensorShape out_shape, PadStrideInfo pad_stride_info)
+    {
+        _target    = compute_target(in_shape, weights_shape, out_shape, pad_stride_info);
+        _reference = compute_reference(in_shape, weights_shape, out_shape, pad_stride_info);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        switch(tensor.data_type())
+        {
+            case DataType::F32:
+            {
+                std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
+                library->fill(tensor, distribution, i);
+                break;
+            }
+            default:
+                library->fill_tensor_uniform(tensor, i);
+        }
+    }
+
+    TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &output_shape, PadStrideInfo &pad_stride_info)
+    {
+        // Create tensors
+        TensorType src     = create_tensor<TensorType>(input_shape, DataType::F32);
+        TensorType weights = create_tensor<TensorType>(weights_shape, DataType::F32);
+        TensorType dst     = create_tensor<TensorType>(output_shape, DataType::F32);
+
+        // Create Depthwise Convolution configure function
+        CLDepthwiseConvolution depthwise_convolution;
+        depthwise_convolution.configure(&src, &dst, &weights, pad_stride_info);
+
+        // Allocate tensors
+        src.allocator()->allocate();
+        weights.allocator()->allocate();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!weights.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src), 0);
+        fill(AccessorType(weights), 1);
+
+        // Compute function
+        depthwise_convolution.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &in_shape, const TensorShape &weights_shape, const TensorShape &out_shape, const PadStrideInfo &pad_stride_info)
+    {
+        SimpleTensor<T> src(in_shape, DataType::F32);
+        SimpleTensor<T> weights(weights_shape, DataType::F32);
+
+        fill(src, 0);
+        fill(weights, 1);
+
+        return reference::depthwise_convolution(src, weights, out_shape, pad_stride_info);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_DEPTHWISE_CONVOLUTION_FIXTURE */
diff --git a/tests/validation/fixtures/DepthwiseSeparableConvolutionLayerFixture.h b/tests/validation/fixtures/DepthwiseSeparableConvolutionLayerFixture.h
new file mode 100644
index 0000000000..e8f6854b49
--- /dev/null
+++ b/tests/validation/fixtures/DepthwiseSeparableConvolutionLayerFixture.h
@@ -0,0 +1,139 @@
+/*
+ * 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_DEPTHWISE_SEPARABLE_CONVOLUTION_LAYER_FIXTURE
+#define ARM_COMPUTE_TEST_DEPTHWISE_SEPARABLE_CONVOLUTION_LAYER_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/DepthwiseSeparableConvolutionLayer.h"
+#include "tests/validation/Helpers.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DepthwiseSeparableConvolutionValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape in_shape, TensorShape depthwise_weights_shape, TensorShape depthwise_out_shape, TensorShape pointwise_weights_shape, TensorShape biases_shape, TensorShape output_shape,
+               PadStrideInfo pad_stride_depthwise_info, PadStrideInfo pad_stride_pointwise_info)
+    {
+        _target    = compute_target(in_shape, depthwise_weights_shape, depthwise_out_shape, pointwise_weights_shape, biases_shape, output_shape, pad_stride_depthwise_info, pad_stride_pointwise_info);
+        _reference = compute_reference(in_shape, depthwise_weights_shape, depthwise_out_shape, pointwise_weights_shape, biases_shape, output_shape, pad_stride_depthwise_info, pad_stride_pointwise_info);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        switch(tensor.data_type())
+        {
+            case DataType::F32:
+            {
+                std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
+                library->fill(tensor, distribution, i);
+                break;
+            }
+            default:
+                library->fill_tensor_uniform(tensor, i);
+        }
+    }
+
+    TensorType compute_target(const TensorShape &input_shape, const TensorShape &depthwise_weights_shape, const TensorShape &depthwise_out_shape, const TensorShape &pointwise_weights_shape,
+                              const TensorShape &biases_shape,
+                              const TensorShape &output_shape, const PadStrideInfo &pad_stride_depthwise_info, const PadStrideInfo &pad_stride_pointwise_info)
+    {
+        // Create tensors
+        TensorType src               = create_tensor<TensorType>(input_shape, DataType::F32);
+        TensorType depthwise_weights = create_tensor<TensorType>(depthwise_weights_shape, DataType::F32);
+        TensorType depthwise_out     = create_tensor<TensorType>(depthwise_out_shape, DataType::F32);
+        TensorType pointwise_weights = create_tensor<TensorType>(pointwise_weights_shape, DataType::F32);
+        TensorType biases            = create_tensor<TensorType>(biases_shape, DataType::F32);
+        TensorType dst               = create_tensor<TensorType>(output_shape, DataType::F32);
+
+        // Create Depthwise Separable Convolution Layer configure function
+        CLDepthwiseSeparableConvolutionLayer depthwise_separable_convolution_layer;
+        depthwise_separable_convolution_layer.configure(&src, &depthwise_weights, &depthwise_out, &pointwise_weights, &biases, &dst, pad_stride_depthwise_info, pad_stride_pointwise_info);
+
+        // Allocate tensors
+        src.allocator()->allocate();
+        depthwise_weights.allocator()->allocate();
+        depthwise_out.allocator()->allocate();
+        pointwise_weights.allocator()->allocate();
+        biases.allocator()->allocate();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!depthwise_weights.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!depthwise_out.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!pointwise_weights.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!biases.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src), 0);
+        fill(AccessorType(depthwise_weights), 1);
+        fill(AccessorType(pointwise_weights), 2);
+        fill(AccessorType(biases), 3);
+
+        // Compute function
+        depthwise_separable_convolution_layer.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &in_shape, const TensorShape &depthwise_weights_shape, const TensorShape &depthwise_out_shape, const TensorShape &pointwise_weights_shape,
+                                      const TensorShape &biases_shape, const TensorShape &dst_shape, const PadStrideInfo &pad_stride_depthwise_info, const PadStrideInfo &pad_stride_pointwise_info)
+    {
+        SimpleTensor<T> src(in_shape, DataType::F32);
+        SimpleTensor<T> depthwise_weights(depthwise_weights_shape, DataType::F32);
+        SimpleTensor<T> pointwise_weights(pointwise_weights_shape, DataType::F32);
+        SimpleTensor<T> biases(biases_shape, DataType::F32);
+
+        fill(src, 0);
+        fill(depthwise_weights, 1);
+        fill(pointwise_weights, 2);
+        fill(biases, 3);
+
+        return reference::depthwise_separable_convolution_layer(src, depthwise_weights, depthwise_out_shape, pointwise_weights, biases, dst_shape, pad_stride_depthwise_info, pad_stride_pointwise_info);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_DEPTHWISE_SEPARABLE_CONVOLUTION_LAYER_FIXTURE */
diff --git a/tests/validation/fixtures/DequantizationLayerFixture.h b/tests/validation/fixtures/DequantizationLayerFixture.h
new file mode 100644
index 0000000000..7543eb2d2e
--- /dev/null
+++ b/tests/validation/fixtures/DequantizationLayerFixture.h
@@ -0,0 +1,147 @@
+/*
+ * 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_DEQUANTIZATION_LAYER_FIXTURE
+#define ARM_COMPUTE_TEST_DEQUANTIZATION_LAYER_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/DequantizationLayer.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DequantizationValidationFixedPointFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type)
+    {
+        // Initialize random min and max values
+        rand_min_max(&_min, &_max);
+
+        _target    = compute_target(shape, data_type, _min, _max);
+        _reference = compute_reference(shape, data_type, _min, _max);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        library->fill_tensor_uniform(tensor, 0);
+    }
+
+    TensorType compute_target(const TensorShape &shape, DataType data_type, float min, float max)
+    {
+        // Create tensors
+        TensorType src = create_tensor<TensorType>(shape, data_type);
+        TensorType dst = create_tensor<TensorType>(shape, DataType::F32);
+
+        // Create and configure function
+        FunctionType dequantization_layer;
+        dequantization_layer.configure(&src, &dst, &min, &max);
+
+        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();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        dequantization_layer.run();
+
+        return dst;
+    }
+
+    SimpleTensor<float> compute_reference(const TensorShape &shape, DataType data_type, float min, float max)
+    {
+        // Create reference
+        SimpleTensor<T> src{ shape, data_type };
+
+        // Fill reference
+        fill(src);
+
+        return reference::dequantization_layer<T>(src, min, max);
+    }
+
+    /** Generate random constant values to be used as min and max for dequantization.
+     */
+    void rand_min_max(float *min, float *max)
+    {
+        std::mt19937                          gen(library->seed());
+        std::uniform_real_distribution<float> distribution(-10000.0, 10000.0);
+
+        const float n1 = distribution(gen);
+        const float n2 = distribution(gen);
+
+        if(n1 < n2)
+        {
+            *min = n1;
+            *max = n2;
+        }
+        else
+        {
+            *min = n2;
+            *max = n1;
+        }
+    }
+
+    TensorType          _target{};
+    SimpleTensor<float> _reference{};
+    float               _min = 0.f;
+    float               _max = 0.f;
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DequantizationValidationFixture : public DequantizationValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type)
+    {
+        DequantizationValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type);
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_DEQUANTIZATION_LAYER_FIXTURE */
diff --git a/tests/validation/fixtures/DirectConvolutionLayerFixture.h b/tests/validation/fixtures/DirectConvolutionLayerFixture.h
new file mode 100644
index 0000000000..6ffebce108
--- /dev/null
+++ b/tests/validation/fixtures/DirectConvolutionLayerFixture.h
@@ -0,0 +1,86 @@
+/*
+ * 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/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/ConvolutionLayer.h"
+#include "tests/validation/Helpers.h"
+#include "tests/validation/fixtures/ConvolutionLayerFixture.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DirectConvolutionValidationFixedPointFixture : public ConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, int fractional_bits)
+    {
+        const TensorShape   weights_shape(kernel_size, kernel_size, input_shape.z(), num_kernels);
+        const TensorShape   bias_shape(num_kernels);
+        const PadStrideInfo info(stride_x, stride_y, pad_x, pad_y, DimensionRoundingType::FLOOR);
+        const TensorShape   output_shape = get_output_shape(input_shape, weights_shape, info);
+
+        ConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, data_type, fractional_bits);
+    }
+
+private:
+    TensorShape get_output_shape(TensorShape in_shape, TensorShape kernel_shape, const PadStrideInfo &info)
+    {
+        TensorShape out_shape(in_shape);
+        const std::pair<unsigned int, unsigned int> scaled_dims = scaled_dimensions(in_shape.x(),
+                                                                                    in_shape.y(),
+                                                                                    kernel_shape.x(),
+                                                                                    kernel_shape.y(),
+                                                                                    info);
+        out_shape.set(0, scaled_dims.first);
+        out_shape.set(1, scaled_dims.second);
+        out_shape.set(2, kernel_shape[3]);
+        return out_shape;
+    }
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class DirectConvolutionValidationFixture : public DirectConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type)
+    {
+        DirectConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0);
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/fixtures/FloorFixture.h b/tests/validation/fixtures/FloorFixture.h
new file mode 100644
index 0000000000..3f948412af
--- /dev/null
+++ b/tests/validation/fixtures/FloorFixture.h
@@ -0,0 +1,107 @@
+/*
+ * 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_FLOOR_FIXTURE
+#define ARM_COMPUTE_TEST_FLOOR_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/Floor.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class FloorValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type)
+    {
+        _target    = compute_target(shape, data_type);
+        _reference = compute_reference(shape, data_type);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        library->fill_tensor_uniform(tensor, 0);
+    }
+
+    TensorType compute_target(const TensorShape &shape, DataType data_type)
+    {
+        // Create tensors
+        TensorType src = create_tensor<TensorType>(shape, data_type);
+        TensorType dst = create_tensor<TensorType>(shape, data_type);
+
+        // Create and configure function
+        FunctionType floor_func;
+        floor_func.configure(&src, &dst);
+
+        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();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        floor_func.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type)
+    {
+        // Create reference
+        SimpleTensor<T> src{ shape, data_type };
+
+        // Fill reference
+        fill(src);
+
+        return reference::floor_layer<T>(src);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_FLOOR_FIXTURE */
diff --git a/tests/validation/fixtures/FullyConnectedLayerFixture.h b/tests/validation/fixtures/FullyConnectedLayerFixture.h
new file mode 100644
index 0000000000..d4d68f1af8
--- /dev/null
+++ b/tests/validation/fixtures/FullyConnectedLayerFixture.h
@@ -0,0 +1,250 @@
+/*
+ * 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_FULLY_CONNECTED_LAYER_FIXTURE
+#define ARM_COMPUTE_TEST_FULLY_CONNECTED_LAYER_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Utils.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/RawTensor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/FullyConnectedLayer.h"
+#include "tests/validation/Helpers.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+RawTensor transpose(const RawTensor &src, int interleave = 1)
+{
+    // Create reference
+    TensorShape dst_shape(src.shape());
+    dst_shape.set(0, src.shape().y() * interleave);
+    dst_shape.set(1, std::ceil(src.shape().x() / static_cast<float>(interleave)));
+
+    RawTensor dst{ dst_shape, src.data_type() };
+
+    // Compute reference
+    uint8_t *out_ptr = dst.data();
+
+    for(int i = 0; i < dst.num_elements(); i += interleave)
+    {
+        Coordinates coord   = index2coord(dst.shape(), i);
+        size_t      coord_x = coord.x();
+        coord.set(0, coord.y() * interleave);
+        coord.set(1, coord_x / interleave);
+
+        const int num_elements = std::min<int>(interleave, src.shape().x() - coord.x());
+
+        std::copy_n(static_cast<const uint8_t *>(src(coord)), num_elements * src.element_size(), out_ptr);
+
+        out_ptr += interleave * dst.element_size();
+    }
+
+    return dst;
+}
+} // namespace
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool run_interleave>
+class FullyConnectedLayerValidationFixedPointFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, bool transpose_weights, bool reshape_weights, DataType data_type, int fractional_bits)
+    {
+        ARM_COMPUTE_UNUSED(weights_shape);
+        ARM_COMPUTE_UNUSED(bias_shape);
+
+        _fractional_bits = fractional_bits;
+        _data_type       = data_type;
+
+        _target    = compute_target(input_shape, weights_shape, bias_shape, output_shape, transpose_weights, reshape_weights, data_type, fractional_bits);
+        _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, transpose_weights, reshape_weights, data_type, fractional_bits);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        if(is_data_type_float(_data_type))
+        {
+            std::uniform_real_distribution<> distribution(0.5f, 1.f);
+            library->fill(tensor, distribution, i);
+        }
+        else
+        {
+            library->fill_tensor_uniform(tensor, i);
+        }
+    }
+
+    TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, bool transpose_weights,
+                              bool reshape_weights, DataType data_type, int fixed_point_position)
+    {
+        TensorShape reshaped_weights_shape(weights_shape);
+
+        // Test actions depending on the target settings
+        //
+        //            | reshape   | !reshape
+        // -----------+-----------+---------------------------
+        //  transpose |           | ***
+        // -----------+-----------+---------------------------
+        // !transpose | transpose | transpose &
+        //            |           | transpose1xW (if required)
+        //
+        // ***: That combination is invalid. But we can ignore the transpose flag and handle all !reshape the same
+        if(!reshape_weights || !transpose_weights)
+        {
+            const size_t shape_x = reshaped_weights_shape.x();
+            reshaped_weights_shape.set(0, reshaped_weights_shape.y());
+            reshaped_weights_shape.set(1, shape_x);
+
+            // Weights have to be passed reshaped
+            // Transpose 1xW for batched version
+            if(!reshape_weights && output_shape.y() > 1 && run_interleave)
+            {
+                const int   transpose_width = 16 / data_size_from_type(data_type);
+                const float shape_x         = reshaped_weights_shape.x();
+                reshaped_weights_shape.set(0, reshaped_weights_shape.y() * transpose_width);
+                reshaped_weights_shape.set(1, static_cast<unsigned int>(std::ceil(shape_x / transpose_width)));
+            }
+        }
+
+        // Create tensors
+        TensorType src     = create_tensor<TensorType>(input_shape, data_type, 1, fixed_point_position);
+        TensorType weights = create_tensor<TensorType>(reshaped_weights_shape, data_type, 1, fixed_point_position);
+        TensorType bias    = create_tensor<TensorType>(bias_shape, data_type, 1, fixed_point_position);
+        TensorType dst     = create_tensor<TensorType>(output_shape, data_type, 1, fixed_point_position);
+
+        // Create and configure function.
+        FunctionType fc;
+        fc.configure(&src, &weights, &bias, &dst, transpose_weights, !reshape_weights);
+
+        ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        src.allocator()->allocate();
+        weights.allocator()->allocate();
+        bias.allocator()->allocate();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!weights.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!bias.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src), 0);
+        fill(AccessorType(bias), 2);
+
+        if(!reshape_weights || !transpose_weights)
+        {
+            TensorShape tmp_shape(weights_shape);
+            RawTensor   tmp(tmp_shape, data_type, 1, fixed_point_position);
+
+            // Fill with original shape
+            fill(tmp, 1);
+
+            // Transpose elementwise
+            tmp = transpose(tmp);
+
+            // Reshape weights for batched runs
+            if(!reshape_weights && output_shape.y() > 1 && run_interleave)
+            {
+                // Transpose with interleave
+                const int interleave_size = 16 / tmp.element_size();
+                tmp                       = transpose(tmp, interleave_size);
+            }
+
+            AccessorType weights_accessor(weights);
+
+            for(int i = 0; i < tmp.num_elements(); ++i)
+            {
+                Coordinates coord = index2coord(tmp.shape(), i);
+                std::copy_n(static_cast<const RawTensor::value_type *>(tmp(coord)),
+                            tmp.element_size(),
+                            static_cast<RawTensor::value_type *>(weights_accessor(coord)));
+            }
+        }
+        else
+        {
+            fill(AccessorType(weights), 1);
+        }
+
+        // Compute NEFullyConnectedLayer function
+        fc.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, bool transpose_weights,
+                                      bool reshape_weights, DataType data_type, int fixed_point_position = 0)
+    {
+        // Create reference
+        SimpleTensor<T> src{ input_shape, data_type, 1, fixed_point_position };
+        SimpleTensor<T> weights{ weights_shape, data_type, 1, fixed_point_position };
+        SimpleTensor<T> bias{ bias_shape, data_type, 1, fixed_point_position };
+
+        // Fill reference
+        fill(src, 0);
+        fill(weights, 1);
+        fill(bias, 2);
+
+        return reference::fully_connected_layer<T>(src, weights, bias, output_shape);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+    int             _fractional_bits{};
+    DataType        _data_type{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool run_interleave>
+class FullyConnectedLayerValidationFixture : public FullyConnectedLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T, run_interleave>
+{
+public:
+    template <typename...>
+    void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, bool transpose_weights, bool reshape_weights, DataType data_type)
+    {
+        FullyConnectedLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T, run_interleave>::setup(input_shape, weights_shape, bias_shape, output_shape, transpose_weights,
+                                                                                                                         reshape_weights, data_type,
+                                                                                                                         0);
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_FULLY_CONNECTED_LAYER_FIXTURE */
diff --git a/tests/validation/fixtures/GEMMFixture.h b/tests/validation/fixtures/GEMMFixture.h
new file mode 100644
index 0000000000..923a29c7d0
--- /dev/null
+++ b/tests/validation/fixtures/GEMMFixture.h
@@ -0,0 +1,152 @@
+/*
+ * 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_GEMM_FIXTURE
+#define ARM_COMPUTE_TEST_GEMM_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/GEMM.h"
+#include "tests/validation/Helpers.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class GEMMValidationFixedPointFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_c, TensorShape output_shape, float alpha, float beta, DataType data_type, int fractional_bits)
+    {
+        _fractional_bits = fractional_bits;
+        _data_type       = data_type;
+
+        _target    = compute_target(shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type, fractional_bits);
+        _reference = compute_reference(shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type, fractional_bits);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        switch(tensor.data_type())
+        {
+            case DataType::F16:
+            case DataType::F32:
+            {
+                std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
+                library->fill(tensor, distribution, i);
+                break;
+            }
+            default:
+                library->fill_tensor_uniform(tensor, i);
+        }
+    }
+
+    TensorType compute_target(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c, const TensorShape &output_shape, float alpha, float beta,
+                              DataType data_type, int fixed_point_position)
+    {
+        // Create tensors
+        TensorType a   = create_tensor<TensorType>(shape_a, data_type, 1, fixed_point_position);
+        TensorType b   = create_tensor<TensorType>(shape_b, data_type, 1, fixed_point_position);
+        TensorType c   = create_tensor<TensorType>(shape_c, data_type, 1, fixed_point_position);
+        TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, fixed_point_position);
+
+        // Create and configure function
+        FunctionType gemm;
+        gemm.configure(&a, &b, &c, &dst, alpha, beta);
+
+        ARM_COMPUTE_EXPECT(a.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(b.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(c.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        a.allocator()->allocate();
+        b.allocator()->allocate();
+        c.allocator()->allocate();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!a.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!b.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!c.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(a), 0);
+        fill(AccessorType(b), 1);
+        fill(AccessorType(c), 2);
+
+        // Compute GEMM function
+        gemm.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape_a, const TensorShape &shape_b, const TensorShape &shape_c, const TensorShape &output_shape, float alpha, float beta,
+                                      DataType data_type, int fixed_point_position)
+    {
+        // Create reference
+        SimpleTensor<T> a{ shape_a, data_type, 1, fixed_point_position };
+        SimpleTensor<T> b{ shape_b, data_type, 1, fixed_point_position };
+        SimpleTensor<T> c{ shape_c, data_type, 1, fixed_point_position };
+
+        // Fill reference
+        fill(a, 0);
+        fill(b, 1);
+        fill(c, 2);
+
+        return reference::gemm<T>(a, b, c, alpha, beta);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+    int             _fractional_bits{};
+    DataType        _data_type{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class GEMMValidationFixture : public GEMMValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_c, TensorShape output_shape, float alpha, float beta, DataType data_type)
+    {
+        GEMMValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape_a, shape_b, shape_c, output_shape, alpha, beta, data_type, 0);
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_GEMM_FIXTURE */
diff --git a/tests/validation/fixtures/L2NormalizeFixture.h b/tests/validation/fixtures/L2NormalizeFixture.h
new file mode 100644
index 0000000000..e6113937f1
--- /dev/null
+++ b/tests/validation/fixtures/L2NormalizeFixture.h
@@ -0,0 +1,107 @@
+/*
+ * 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_L2NORMALIZE_FIXTURE
+#define ARM_COMPUTE_TEST_L2NORMALIZE_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/L2Normalize.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class L2NormalizeValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type, unsigned int axis, float epsilon)
+    {
+        _target    = compute_target(shape, data_type, axis, epsilon);
+        _reference = compute_reference(shape, data_type, axis, epsilon);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        library->fill_tensor_uniform(tensor, 0);
+    }
+
+    TensorType compute_target(const TensorShape &shape, DataType data_type, unsigned int axis, float epsilon)
+    {
+        // Create tensors
+        TensorType src = create_tensor<TensorType>(shape, data_type);
+        TensorType dst = create_tensor<TensorType>(shape, data_type);
+
+        // Create and configure function
+        FunctionType l2_norm_func;
+        l2_norm_func.configure(&src, &dst, axis, epsilon);
+
+        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();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        l2_norm_func.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, DataType data_type, unsigned int axis, float epsilon)
+    {
+        // Create reference
+        SimpleTensor<T> src{ shape, data_type };
+
+        // Fill reference
+        fill(src);
+
+        return reference::l2_normalize<T>(src, axis, epsilon);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_L2NORMALIZE_FIXTURE */
diff --git a/tests/validation/fixtures/MeanStdDevFixture.h b/tests/validation/fixtures/MeanStdDevFixture.h
new file mode 100644
index 0000000000..37f538b216
--- /dev/null
+++ b/tests/validation/fixtures/MeanStdDevFixture.h
@@ -0,0 +1,102 @@
+/*
+ * 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_MEAN_STD_DEV_FIXTURE
+#define ARM_COMPUTE_TEST_MEAN_STD_DEV_FIXTURE
+
+#include "tests/Globals.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/MeanStdDev.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class MeanStdDevValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type)
+    {
+        _target    = compute_target(shape, data_type);
+        _reference = compute_reference(shape, data_type);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        library->fill_tensor_uniform(tensor, 0);
+    }
+
+    std::pair<float, float> compute_target(const TensorShape &shape, DataType data_type)
+    {
+        // Create tensors
+        TensorType src = create_tensor<TensorType>(shape, data_type);
+
+        // Create output variables
+        float mean    = 0.0f;
+        float std_dev = 0.0f;
+
+        // Create and configure function
+        FunctionType mean_std_dev;
+        mean_std_dev.configure(&src, &mean, &std_dev);
+
+        ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        src.allocator()->allocate();
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        mean_std_dev.run();
+
+        return std::make_pair(mean, std_dev);
+    }
+
+    std::pair<float, float> compute_reference(const TensorShape &shape, DataType data_type)
+    {
+        // Create reference
+        SimpleTensor<T> src{ shape, data_type };
+
+        // Fill reference
+        fill(src);
+
+        // Compute reference
+        return reference::mean_and_standard_deviation<T>(src);
+    }
+
+    std::pair<float, float> _target{};
+    std::pair<float, float> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_MEAN_STD_DEV_FIXTURE */
diff --git a/tests/validation/fixtures/NormalizationLayerFixture.h b/tests/validation/fixtures/NormalizationLayerFixture.h
new file mode 100644
index 0000000000..696d14fbbb
--- /dev/null
+++ b/tests/validation/fixtures/NormalizationLayerFixture.h
@@ -0,0 +1,133 @@
+/*
+ * 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_NORMALIZATION_LAYER_FIXTURE
+#define ARM_COMPUTE_TEST_NORMALIZATION_LAYER_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/NormalizationLayer.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class NormalizationValidationFixedPointFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, NormType norm_type, int norm_size, float beta, DataType data_type, int fractional_bits)
+    {
+        _fractional_bits = fractional_bits;
+        NormalizationLayerInfo info(norm_type, norm_size, 5, beta);
+
+        _target    = compute_target(shape, info, data_type, fractional_bits);
+        _reference = compute_reference(shape, info, data_type, fractional_bits);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        if(_fractional_bits == 0)
+        {
+            library->fill_tensor_uniform(tensor, 0);
+        }
+        else
+        {
+            const int                       one_fixed = 1 << _fractional_bits;
+            std::uniform_int_distribution<> distribution(-one_fixed, one_fixed);
+            library->fill(tensor, distribution, 0);
+        }
+    }
+
+    TensorType compute_target(const TensorShape &shape, NormalizationLayerInfo 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 norm_layer;
+        norm_layer.configure(&src, &dst, 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();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        norm_layer.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, NormalizationLayerInfo 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::normalization_layer<T>(src, info);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+    int             _fractional_bits{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class NormalizationValidationFixture : public NormalizationValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, NormType norm_type, int norm_size, float beta, DataType data_type)
+    {
+        NormalizationValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, norm_type, norm_size, beta, data_type, 0);
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_NORMALIZATION_LAYER_FIXTURE */
diff --git a/tests/validation/fixtures/PoolingLayerFixture.h b/tests/validation/fixtures/PoolingLayerFixture.h
new file mode 100644
index 0000000000..5ce4aa6755
--- /dev/null
+++ b/tests/validation/fixtures/PoolingLayerFixture.h
@@ -0,0 +1,134 @@
+/*
+ * 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_POOLING_LAYER_FIXTURE
+#define ARM_COMPUTE_TEST_POOLING_LAYER_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/PoolingLayer.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class PoolingLayerValidationFixedPointFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, DataType data_type, int fractional_bits)
+    {
+        _fractional_bits = fractional_bits;
+        PoolingLayerInfo info(pool_type, pool_size, pad_stride_info);
+
+        _target    = compute_target(shape, info, data_type, fractional_bits);
+        _reference = compute_reference(shape, info, data_type, fractional_bits);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        if(_fractional_bits == 0)
+        {
+            std::uniform_real_distribution<> distribution(-1.f, 1.f);
+            library->fill(tensor, distribution, 0);
+        }
+        else
+        {
+            const int                       one_fixed = 1 << _fractional_bits;
+            std::uniform_int_distribution<> distribution(-one_fixed, one_fixed);
+            library->fill(tensor, distribution, 0);
+        }
+    }
+
+    TensorType compute_target(const TensorShape &shape, PoolingLayerInfo 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 and configure function
+        FunctionType pool_layer;
+        pool_layer.configure(&src, &dst, 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();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        pool_layer.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, PoolingLayerInfo 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::pooling_layer<T>(src, info);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+    int             _fractional_bits{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class PoolingLayerValidationFixture : public PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, DataType data_type)
+    {
+        PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, pool_size, pad_stride_info, data_type, 0);
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_POOLING_LAYER_FIXTURE */
diff --git a/tests/validation/fixtures/QuantizationLayerFixture.h b/tests/validation/fixtures/QuantizationLayerFixture.h
new file mode 100644
index 0000000000..83ee0495f3
--- /dev/null
+++ b/tests/validation/fixtures/QuantizationLayerFixture.h
@@ -0,0 +1,120 @@
+/*
+ * 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_QUANTIZATION_LAYER_FIXTURE
+#define ARM_COMPUTE_TEST_QUANTIZATION_LAYER_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/QuantizationLayer.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class QuantizationValidationFixedPointFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type)
+    {
+        _target    = compute_target(shape, data_type);
+        _reference = compute_reference(shape, data_type);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        library->fill_tensor_uniform(tensor, 0);
+    }
+
+    TensorType compute_target(const TensorShape &shape, DataType data_type)
+    {
+        // Create tensors
+        TensorType src = create_tensor<TensorType>(shape, data_type);
+        TensorType dst = create_tensor<TensorType>(shape, DataType::U8);
+
+        // Create and configure function
+        FunctionType quantization_layer;
+        quantization_layer.configure(&src, &dst);
+
+        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();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        quantization_layer.run();
+
+        return dst;
+    }
+
+    SimpleTensor<uint8_t> compute_reference(const TensorShape &shape, DataType data_type)
+    {
+        // Create reference
+        SimpleTensor<T> src{ shape, data_type };
+
+        // Fill reference
+        fill(src);
+
+        return reference::quantization_layer<T>(src);
+    }
+
+    TensorType            _target{};
+    SimpleTensor<uint8_t> _reference{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class QuantizationValidationFixture : public QuantizationValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type)
+    {
+        QuantizationValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type);
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_QUANTIZATION_LAYER_FIXTURE */
diff --git a/tests/validation/fixtures/ReductionOperationFixture.h b/tests/validation/fixtures/ReductionOperationFixture.h
new file mode 100644
index 0000000000..7c871aed3b
--- /dev/null
+++ b/tests/validation/fixtures/ReductionOperationFixture.h
@@ -0,0 +1,116 @@
+/*
+ * 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_REDUCTION_OPERATION_FIXTURE
+#define ARM_COMPUTE_TEST_REDUCTION_OPERATION_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/ReductionOperation.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class ReductionOperationValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type, unsigned int axis, ReductionOperation op)
+    {
+        const TensorShape output_shape = get_output_shape(shape, axis);
+        _target                        = compute_target(shape, output_shape, data_type, axis, op);
+        _reference                     = compute_reference(shape, output_shape, data_type, axis, op);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        library->fill_tensor_uniform(tensor, 0);
+    }
+
+    TensorType compute_target(const TensorShape &src_shape, const TensorShape &dst_shape, DataType data_type, unsigned int axis, ReductionOperation op)
+    {
+        // Create tensors
+        TensorType src = create_tensor<TensorType>(src_shape, data_type);
+        TensorType dst = create_tensor<TensorType>(dst_shape, data_type);
+
+        // Create and configure function
+        FunctionType reduction_func;
+        reduction_func.configure(&src, &dst, axis, op);
+
+        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();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        reduction_func.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &src_shape, const TensorShape &dst_shape, DataType data_type, unsigned int axis, ReductionOperation op)
+    {
+        // Create reference
+        SimpleTensor<T> src{ src_shape, data_type };
+
+        // Fill reference
+        fill(src);
+
+        return reference::reduction_operation<T>(src, dst_shape, axis, op);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+
+private:
+    TensorShape get_output_shape(TensorShape shape, unsigned int axis)
+    {
+        TensorShape output_shape(shape);
+        output_shape.set(axis, 1);
+        return output_shape;
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_REDUCTION_OPERATION_FIXTURE */
diff --git a/tests/validation/fixtures/ScaleFixture.h b/tests/validation/fixtures/ScaleFixture.h
new file mode 100644
index 0000000000..53bb0f2124
--- /dev/null
+++ b/tests/validation/fixtures/ScaleFixture.h
@@ -0,0 +1,127 @@
+/*
+ * 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_SCALE_FIXTURE
+#define ARM_COMPUTE_TEST_SCALE_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/Scale.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class ScaleValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type, InterpolationPolicy policy, BorderMode border_mode)
+    {
+        _shape       = shape;
+        _policy      = policy;
+        _border_mode = border_mode;
+        _data_type   = data_type;
+
+        std::mt19937                           generator(library->seed());
+        std::uniform_real_distribution<float>  distribution_float(0.25, 4);
+        const float                            scale_x = distribution_float(generator);
+        const float                            scale_y = distribution_float(generator);
+        std::uniform_int_distribution<uint8_t> distribution_u8(0, 255);
+        uint8_t                                constant_border_value = distribution_u8(generator);
+
+        _target    = compute_target(shape, scale_x, scale_y, policy, border_mode, constant_border_value);
+        _reference = compute_reference(shape, scale_x, scale_y, policy, border_mode, constant_border_value);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        library->fill_tensor_uniform(tensor, 0);
+    }
+
+    TensorType compute_target(const TensorShape &shape, const float scale_x, const float scale_y,
+                              InterpolationPolicy policy, BorderMode border_mode, uint8_t constant_border_value)
+    {
+        // Create tensors
+        TensorType  src = create_tensor<TensorType>(shape, _data_type);
+        TensorShape shape_scaled(shape);
+        shape_scaled.set(0, shape[0] * scale_x);
+        shape_scaled.set(1, shape[1] * scale_y);
+        TensorType dst = create_tensor<TensorType>(shape_scaled, _data_type);
+
+        // Create and configure function
+        FunctionType scale;
+
+        scale.configure(&src, &dst, policy, border_mode, constant_border_value);
+
+        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();
+        dst.allocator()->allocate();
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        scale.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, const float scale_x, const float scale_y,
+                                      InterpolationPolicy policy, BorderMode border_mode, uint8_t constant_border_value)
+    {
+        // Create reference
+        SimpleTensor<T> src{ shape, _data_type };
+
+        // Fill reference
+        fill(src);
+
+        return reference::scale<T>(src, scale_x, scale_y, policy, border_mode, constant_border_value);
+    }
+
+    TensorType          _target{};
+    SimpleTensor<T>     _reference{};
+    TensorShape         _shape{};
+    InterpolationPolicy _policy{};
+    BorderMode          _border_mode{};
+    DataType            _data_type{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_SCALE_FIXTURE */
\ No newline at end of file
diff --git a/tests/validation/fixtures/SoftmaxLayerFixture.h b/tests/validation/fixtures/SoftmaxLayerFixture.h
new file mode 100644
index 0000000000..9c8f044e81
--- /dev/null
+++ b/tests/validation/fixtures/SoftmaxLayerFixture.h
@@ -0,0 +1,133 @@
+/*
+ * 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_SOFTMAX_LAYER_FIXTURE
+#define ARM_COMPUTE_TEST_SOFTMAX_LAYER_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/CPP/SoftmaxLayer.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class SoftmaxValidationFixedPointFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type, int fractional_bits)
+    {
+        _fractional_bits = fractional_bits;
+
+        _target    = compute_target(shape, data_type, fractional_bits);
+        _reference = compute_reference(shape, data_type, fractional_bits);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor)
+    {
+        if(_fractional_bits == 0)
+        {
+            std::uniform_real_distribution<> distribution(-1000.f, 1000.f);
+            library->fill(tensor, distribution, 0);
+        }
+        else
+        {
+            const int                       one_fixed = 1 << _fractional_bits;
+            std::uniform_int_distribution<> distribution(-one_fixed, one_fixed);
+            library->fill(tensor, distribution, 0);
+        }
+    }
+
+    TensorType compute_target(const TensorShape &shape, 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 smx_layer;
+        smx_layer.configure(&src, &dst);
+
+        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();
+        dst.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(src));
+
+        // Compute function
+        smx_layer.run();
+
+        return dst;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &shape, 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::softmax_layer<T>(src);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+    int             _fractional_bits{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class SoftmaxValidationFixture : public SoftmaxValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+    template <typename...>
+    void setup(TensorShape shape, DataType data_type)
+    {
+        SoftmaxValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, data_type, 0);
+    }
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_SOFTMAX_LAYER_FIXTURE */