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diff --git a/tests/validation/fixtures/UnstackFixture.h b/tests/validation/fixtures/UnstackFixture.h
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+/*
+ * Copyright (c) 2018 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_UNSTACK_FIXTURE
+#define ARM_COMPUTE_TEST_UNSTACK_FIXTURE
+
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.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/Helpers.h"
+#include "tests/validation/reference/Unstack.h"
+
+#include <random>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename ITensorType, typename AccessorType, typename FunctionType, typename T>
+class UnstackValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape input_shape, int axis, int num, DataType data_type)
+    {
+        _target    = compute_target(input_shape, axis, num, data_type);
+        _reference = compute_reference(input_shape, axis, num, data_type);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        library->fill_tensor_uniform(tensor, i);
+    }
+
+    std::vector<TensorType> compute_target(TensorShape input_shape, int axis, unsigned int num, DataType data_type)
+    {
+        TensorType                 input_tensor = create_tensor<TensorType>(input_shape, data_type);
+        const unsigned int         axis_u       = wrap_around(axis, static_cast<int>(input_shape.num_dimensions()));
+        const unsigned int         axis_size    = input_shape[axis_u];
+        const unsigned int         num_slices   = std::min(num, axis_size);
+        std::vector<TensorType>    output_slices(num_slices);
+        std::vector<ITensorType *> output_ptrs(num_slices);
+        for(size_t k = 0; k < num_slices; ++k)
+        {
+            output_ptrs[k] = &output_slices[k];
+        }
+        // Create and configure function
+        FunctionType unstack;
+        unstack.configure(&input_tensor, output_ptrs, axis);
+        // Allocate tensors
+        for(auto &out : output_slices)
+        {
+            out.allocator()->allocate();
+            ARM_COMPUTE_EXPECT(!out.info()->is_resizable(), framework::LogLevel::ERRORS);
+        }
+        input_tensor.allocator()->allocate();
+        ARM_COMPUTE_EXPECT(!input_tensor.info()->is_resizable(), framework::LogLevel::ERRORS);
+        fill(AccessorType(input_tensor), 0);
+        // Compute function
+        unstack.run();
+        return output_slices;
+    }
+
+    std::vector<SimpleTensor<T>> compute_reference(TensorShape input_shape, int axis, unsigned int num, DataType data_type)
+    {
+        const unsigned int axis_u             = wrap_around(axis, static_cast<int>(input_shape.num_dimensions()));
+        const unsigned int axis_size          = input_shape[axis_u];
+        const unsigned int num_output_tensors = (num == 0) ? axis_size : std::min(axis_size, num);
+        // create and fill input tensor
+        SimpleTensor<T> input_tensor{ input_shape, data_type };
+        fill(input_tensor, 0);
+        // create output tensors
+        const TensorShape            slice_shape = arm_compute::misc::shape_calculator::calculate_unstack_shape(input_shape, axis_u);
+        std::vector<SimpleTensor<T>> output_tensors(num_output_tensors);
+        for(size_t k = 0; k < num_output_tensors; ++k)
+        {
+            output_tensors[k] = SimpleTensor<T>(slice_shape, data_type);
+        }
+
+        return reference::unstack<T>(input_tensor, output_tensors, axis);
+    }
+
+    std::vector<TensorType>      _target{};
+    std::vector<SimpleTensor<T>> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_UNSTACK_FIXTURE */