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diff --git a/tests/validation/fixtures/BatchToSpaceLayerFixture.h b/tests/validation/fixtures/BatchToSpaceLayerFixture.h
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+++ b/tests/validation/fixtures/BatchToSpaceLayerFixture.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_BATCH_TO_SPACE_LAYER_FIXTURE
+#define ARM_COMPUTE_TEST_BATCH_TO_SPACE_LAYER_FIXTURE
+
+#include "tests/Globals.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/reference/BatchToSpaceLayer.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class BatchToSpaceLayerValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape input_shape, TensorShape block_shape_shape, TensorShape output_shape, DataType data_type)
+    {
+        _target    = compute_target(input_shape, block_shape_shape, output_shape, data_type);
+        _reference = compute_reference(input_shape, block_shape_shape, output_shape, data_type);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i)
+    {
+        std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
+        library->fill(tensor, distribution, i);
+    }
+    TensorType compute_target(const TensorShape &input_shape, const TensorShape &block_shape_shape, const TensorShape &output_shape,
+                              DataType data_type)
+    {
+        // Create tensors
+        TensorType input       = create_tensor<TensorType>(input_shape, data_type);
+        TensorType block_shape = create_tensor<TensorType>(block_shape_shape, DataType::S32);
+        TensorType output      = create_tensor<TensorType>(output_shape, data_type);
+
+        // Create and configure function
+        FunctionType batch_to_space;
+        batch_to_space.configure(&input, &block_shape, &output);
+
+        ARM_COMPUTE_EXPECT(input.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(block_shape.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(output.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        input.allocator()->allocate();
+        block_shape.allocator()->allocate();
+        output.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!input.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!block_shape.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!output.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(input), 0);
+        {
+            auto block_shape_data = AccessorType(block_shape);
+            for(unsigned int i = 0; i < block_shape_shape.x(); ++i)
+            {
+                static_cast<int32_t *>(block_shape_data.data())[i] = output_shape[i] / input_shape[i];
+            }
+        }
+        // Compute function
+        batch_to_space.run();
+
+        return output;
+    }
+
+    SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &block_shape_shape,
+                                      const TensorShape &output_shape, DataType data_type)
+    {
+        // Create reference
+        SimpleTensor<T>       input{ input_shape, data_type };
+        SimpleTensor<int32_t> block_shape{ block_shape_shape, DataType::S32 };
+
+        // Fill reference
+        fill(input, 0);
+        for(unsigned int i = 0; i < block_shape_shape.x(); ++i)
+        {
+            block_shape[i] = output_shape[i] / input_shape[i];
+        }
+
+        // Compute reference
+        return reference::batch_to_space(input, block_shape, output_shape);
+    }
+
+    TensorType      _target{};
+    SimpleTensor<T> _reference{};
+};
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_BATCH_TO_SPACE_LAYER_FIXTURE */