COMPMID-2051 Refactor shape_calculator::calculate_concatenate_shape

Change-Id: Ibf316718d11fa975d75f226925747b21c4efd127
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/974
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>

27 files changed, 277 insertions, 471 deletions

diff --git a/arm_compute/core/CL/kernels/CLDepthConcatenateLayerKernel.h b/arm_compute/core/CL/kernels/CLDepthConcatenateLayerKernel.h
index ff8009085f..2a1845226f 100644
--- a/arm_compute/core/CL/kernels/CLDepthConcatenateLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLDepthConcatenateLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -73,13 +73,10 @@ public:
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
-    BorderSize border_size() const override;
 
 private:
     const ICLTensor *_input;
     ICLTensor       *_output;
-    int              _top_bottom;
-    int              _left_right;
     unsigned int     _depth_offset;
 };
 } // namespace arm_compute
diff --git a/arm_compute/core/GLES_COMPUTE/kernels/GCDepthConcatenateLayerKernel.h b/arm_compute/core/GLES_COMPUTE/kernels/GCDepthConcatenateLayerKernel.h
index 06a54dd0b3..6a03170065 100644
--- a/arm_compute/core/GLES_COMPUTE/kernels/GCDepthConcatenateLayerKernel.h
+++ b/arm_compute/core/GLES_COMPUTE/kernels/GCDepthConcatenateLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -64,13 +64,10 @@ public:
 
     // Inherited methods overridden:
     void run(const Window &window) override;
-    BorderSize border_size() const override;
 
 private:
     const IGCTensor *_input;
     IGCTensor       *_output;
-    int              _top_bottom;
-    int              _left_right;
     int              _depth_offset;
 };
 }
diff --git a/arm_compute/core/NEON/kernels/NEDepthConcatenateLayerKernel.h b/arm_compute/core/NEON/kernels/NEDepthConcatenateLayerKernel.h
index 848d89fc9f..26e23a73a5 100644
--- a/arm_compute/core/NEON/kernels/NEDepthConcatenateLayerKernel.h
+++ b/arm_compute/core/NEON/kernels/NEDepthConcatenateLayerKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -76,17 +76,14 @@ public:
 
     // Inherited methods overridden:
     void run(const Window &window, const ThreadInfo &info) override;
-    BorderSize border_size() const override;
 
 private:
-    using DepthConcatFunction = void(const ITensor *in, ITensor *out, std::pair<int, int> start_xy, int depth_offset, const Window &window);
+    using DepthConcatFunction = void(const ITensor *in, ITensor *out, int depth_offset, const Window &window);
 
 private:
     DepthConcatFunction *_func;
     const ITensor       *_input;
     ITensor             *_output;
-    int                  _top_bottom;
-    int                  _left_right;
     unsigned int         _depth_offset;
 };
 } // namespace arm_compute
diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index 384bd460a0..f5058b35fb 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -1173,6 +1173,11 @@ inline TensorShape extract_shape(const TensorShape *data)
     return *data;
 }
 
+inline TensorShape extract_shape(TensorShape *data)
+{
+    return *data;
+}
+
 /** Calculate the unstack shape of a tensor
  *
  * @param[in] input_shape Input tensor shape
@@ -1187,37 +1192,6 @@ inline TensorShape calculate_unstack_shape(TensorShape input_shape, unsigned int
     return input_shape;
 }
 
-/** Calculate the depth concatenate output shape of a vector of tensors
- *
- * @param[in] inputs_vector Vector containing the shapes of the inputs
- *
- * @return the calculated shape
- */
-template <typename T>
-inline TensorShape calculate_depth_concatenate_shape(const std::vector<T *> &inputs_vector)
-{
-    TensorShape out_shape = extract_shape(inputs_vector[0]);
-
-    size_t max_x = 0;
-    size_t max_y = 0;
-    size_t depth = 0;
-
-    for(const auto &tensor : inputs_vector)
-    {
-        ARM_COMPUTE_ERROR_ON(tensor == nullptr);
-        const TensorShape shape = extract_shape(tensor);
-        max_x                   = std::max(shape.x(), max_x);
-        max_y                   = std::max(shape.y(), max_y);
-        depth += shape.z();
-    }
-
-    out_shape.set(0, max_x);
-    out_shape.set(1, max_y);
-    out_shape.set(2, depth);
-
-    return out_shape;
-}
-
 /** Calculate the concatenate output shape of the concatenate operation along a single axis
  *
  * @param[in] input Vector containing the shapes of the inputs
@@ -1230,12 +1204,27 @@ inline TensorShape calculate_concatenate_shape(const std::vector<T *> &input, si
 {
     TensorShape out_shape = extract_shape(input[0]);
 
+    // All dimensions must match except the axis one
+    for(unsigned int i = 0; i < MAX_DIMS; ++i)
+    {
+        if(i == axis)
+        {
+            continue;
+        }
+
+        for(const auto &tensor : input)
+        {
+            ARM_COMPUTE_ERROR_ON(tensor == nullptr);
+            const TensorShape shape = extract_shape(tensor);
+            ARM_COMPUTE_ERROR_ON(out_shape[i] != shape[i]);
+        }
+    }
+
+    // Calculate output shape
     size_t new_size = 0;
     for(const auto &tensor : input)
     {
-        ARM_COMPUTE_ERROR_ON(tensor == nullptr);
         const TensorShape shape = extract_shape(tensor);
-        ARM_COMPUTE_ERROR_ON(axis >= shape.num_dimensions());
         new_size += shape[axis];
     }
 
diff --git a/arm_compute/runtime/GLES_COMPUTE/GCFunctions.h b/arm_compute/runtime/GLES_COMPUTE/GCFunctions.h
index 6f338568c2..7e01480801 100644
--- a/arm_compute/runtime/GLES_COMPUTE/GCFunctions.h
+++ b/arm_compute/runtime/GLES_COMPUTE/GCFunctions.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -29,6 +29,7 @@
 #include "arm_compute/runtime/GLES_COMPUTE/functions/GCActivationLayer.h"
 #include "arm_compute/runtime/GLES_COMPUTE/functions/GCArithmeticAddition.h"
 #include "arm_compute/runtime/GLES_COMPUTE/functions/GCBatchNormalizationLayer.h"
+#include "arm_compute/runtime/GLES_COMPUTE/functions/GCConcatenateLayer.h"
 #include "arm_compute/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.h"
 #include "arm_compute/runtime/GLES_COMPUTE/functions/GCDepthConcatenateLayer.h"
 #include "arm_compute/runtime/GLES_COMPUTE/functions/GCDepthwiseConvolutionLayer.h"
diff --git a/arm_compute/runtime/GLES_COMPUTE/functions/GCConcatenateLayer.h b/arm_compute/runtime/GLES_COMPUTE/functions/GCConcatenateLayer.h
new file mode 100644
index 0000000000..c57b282dbe
--- /dev/null
+++ b/arm_compute/runtime/GLES_COMPUTE/functions/GCConcatenateLayer.h
@@ -0,0 +1,68 @@
+/*
+ * Copyright (c) 2019 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_GCDEPTHCONCATENATELAYER_H__
+#define __ARM_COMPUTE_GCDEPTHCONCATENATELAYER_H__
+
+#include "arm_compute/core/GLES_COMPUTE/OpenGLES.h"
+#include "arm_compute/core/GLES_COMPUTE/kernels/GCDepthConcatenateLayerKernel.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/IFunction.h"
+
+#include <memory>
+#include <vector>
+
+namespace arm_compute
+{
+class IGCTensor;
+
+/** Basic function to execute concatenate tensors along a given axis. This function calls the following kernels:
+ *
+ * @note only axis z is supported
+ * -# @ref GCDepthConcatenateLayerKernel
+ */
+class GCConcatenateLayer : public IFunction
+{
+public:
+    /** Default constructor */
+    GCConcatenateLayer();
+    /** Initialise the kernel's inputs vector and output.
+     *
+     * @note Input and output tensor dimensions preconditions defer depending on the concatenation axis.
+     *
+     * @param[in,out] inputs_vector The vectors containing all the tensors to concatenate. Data types supported: F16/F32.
+     * @param[out]    output        Output tensor. Data types supported: Same as @p input.
+     * @param[in]     axis          Concatenation axis. Supported underlying concatenation axis is 2.
+     */
+    void configure(std::vector<IGCTensor *> inputs_vector, IGCTensor *output, size_t axis);
+
+    // Inherited methods overridden:
+    void run() override;
+
+private:
+    std::vector<std::unique_ptr<IGCKernel>> _concat_kernels;
+    unsigned int                            _num_inputs;
+    unsigned int                            _axis;
+};
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_GCDEPTHCONCATENATELAYER_H__ */
diff --git a/arm_compute/runtime/GLES_COMPUTE/functions/GCDepthConcatenateLayer.h b/arm_compute/runtime/GLES_COMPUTE/functions/GCDepthConcatenateLayer.h
index 1151399f92..307ec49952 100644
--- a/arm_compute/runtime/GLES_COMPUTE/functions/GCDepthConcatenateLayer.h
+++ b/arm_compute/runtime/GLES_COMPUTE/functions/GCDepthConcatenateLayer.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -39,6 +39,7 @@ class IGCTensor;
 
 /** Basic function to execute concatenate tensors along z axis. This function calls the following kernels:
  *
+ * @deprecated This function is deprecated and will be removed in release 19.08
  * -# @ref GCFillBorderKernel (executed if input's lowest two dimensions are smaller than respective output's dimensions)
  * -# @ref GCDepthConcatenateLayerKernel
  *
diff --git a/docs/00_introduction.dox b/docs/00_introduction.dox
index 3094573add..45eb4c696d 100644
--- a/docs/00_introduction.dox
+++ b/docs/00_introduction.dox
@@ -236,6 +236,15 @@ If there is more than one release in a month then an extra sequential number is
 
 @subsection S2_2_changelog Changelog
 
+v19.05 Public major release
+ - Deprecated functions/interfaces
+    -  @ref GCDepthConcatenateLayer
+    -  @ref NEWidthConcatenateLayer
+    -  @ref NEDepthConcatenateLayer
+    -  @ref CLWidthConcatenateLayer
+    -  @ref CLDepthConcatenateLayer
+
+
 v19.02 Public major release
  - Various bug fixes.
  - Various optimisations.
diff --git a/src/core/CL/cl_kernels/concatenate.cl b/src/core/CL/cl_kernels/concatenate.cl
index 99f4659960..23ebcf91b6 100644
--- a/src/core/CL/cl_kernels/concatenate.cl
+++ b/src/core/CL/cl_kernels/concatenate.cl
@@ -409,19 +409,19 @@ __kernel void concatenate_height(
 __kernel void concatenate_depth(
     TENSOR3D_DECLARATION(src),
     TENSOR3D_DECLARATION(dst),
-    int3 offsets)
+    int offset)
 {
     Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src);
     Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst);
 
     VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
-    source_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor3D_offset(&src, -offsets.x, -offsets.y, 0));
+    source_values = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)src.ptr);
 
 #if defined(OFFSET_IN1) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_OUT)
     source_values = requantize(source_values, OFFSET_IN1, OFFSET_OUT, SCALE_IN1, SCALE_OUT);
 #endif /* defined(OFFSET_IN1) && defined(OFFSET_OUT) && defined(SCALE_IN1) && defined(SCALE_OUT) */
 
     VSTORE(VEC_SIZE)
-    (source_values, 0, (__global DATA_TYPE *)(dst.ptr + offsets.z));
+    (source_values, 0, (__global DATA_TYPE *)(dst.ptr + offset));
 }
 #endif /* defined(DATA_TYPE) && defined(VEC_SIZE) */
diff --git a/src/core/CL/kernels/CLDepthConcatenateLayerKernel.cpp b/src/core/CL/kernels/CLDepthConcatenateLayerKernel.cpp
index 3fccc0447d..1cae3712dc 100644
--- a/src/core/CL/kernels/CLDepthConcatenateLayerKernel.cpp
+++ b/src/core/CL/kernels/CLDepthConcatenateLayerKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -47,19 +47,13 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, unsi
 {
     ARM_COMPUTE_UNUSED(depth_offset);
 
-    // Configure kernel window
-    const int left_right = (output->dimension(0) - input->dimension(0)) / 2;
-    const int top_bottom = (output->dimension(1) - input->dimension(1)) / 2;
-
     const unsigned int num_elems_processed_per_iteration = 16 / input->element_size();
-    const unsigned int num_elems_read_per_iteration      = 16 / input->element_size();
-    const unsigned int num_rows_read_per_iteration       = 1;
 
     // The window needs to be based on input as we copy all the depths of input
     Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
     win.set(Window::DimZ, Window::Dimension(0, input->tensor_shape().z(), 1));
 
-    AccessWindowRectangle  input_access(input, -left_right, -top_bottom, num_elems_read_per_iteration, num_rows_read_per_iteration);
+    AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
     AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
     bool                   window_changed = update_window_and_padding(win, input_access, output_access);
     output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape()));
@@ -74,30 +68,20 @@ Status validate_arguments(const ITensorInfo *input, unsigned int depth_offset, c
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
 
+    ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimX) != output->dimension(Window::DimX));
+    ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimY) != output->dimension(Window::DimY));
     ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) + depth_offset > output->dimension(2));
-    ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(0) > output->dimension(0));
-    ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(1) > output->dimension(1));
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(3, input, output);
 
-    // The gaps between the two lowest dimensions of input and output need to be divisible by 2
-    // Otherwise it is not clear how the padding should be added onto the input tensor
-    ARM_COMPUTE_RETURN_ERROR_ON((output->dimension(0) - input->dimension(0)) % 2);
-    ARM_COMPUTE_RETURN_ERROR_ON((output->dimension(1) - input->dimension(1)) % 2);
-
     return Status{};
 }
 } // namespace
 
 CLDepthConcatenateLayerKernel::CLDepthConcatenateLayerKernel()
-    : _input(nullptr), _output(nullptr), _top_bottom(0), _left_right(0), _depth_offset(0)
+    : _input(nullptr), _output(nullptr), _depth_offset(0)
 {
 }
 
-BorderSize CLDepthConcatenateLayerKernel::border_size() const
-{
-    return BorderSize(_top_bottom, _left_right);
-}
-
 void CLDepthConcatenateLayerKernel::configure(const ICLTensor *input, unsigned int depth_offset, ICLTensor *output)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
@@ -125,10 +109,6 @@ void CLDepthConcatenateLayerKernel::configure(const ICLTensor *input, unsigned i
     _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("concatenate_depth", build_opts.options()));
 
     // Configure kernel window
-    _left_right = (output->info()->dimension(0) - input->info()->dimension(0)) / 2;
-    _top_bottom = (output->info()->dimension(1) - input->info()->dimension(1)) / 2;
-
-    // Configure kernel window
     auto win_config = validate_and_configure_window(input->info(), depth_offset, output->info());
     ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
 
@@ -153,16 +133,8 @@ void CLDepthConcatenateLayerKernel::run(const Window &window, cl::CommandQueue &
 
     const int offset_to_first_elements_in_bytes = _depth_offset * _output->info()->strides_in_bytes()[2];
 
-    unsigned int  idx = 2 * num_arguments_per_3D_tensor(); // Skip the input and output parameters
-    const cl_int3 offsets =
-    {
-        {
-            static_cast<cl_int>(_left_right),
-            static_cast<cl_int>(_top_bottom),
-            static_cast<cl_int>(offset_to_first_elements_in_bytes),
-        }
-    };
-    _kernel.setArg<cl_int3>(idx, offsets);
+    unsigned int idx = 2 * num_arguments_per_3D_tensor(); // Skip the input and output parameters
+    _kernel.setArg<cl_int>(idx, offset_to_first_elements_in_bytes);
 
     do
     {
diff --git a/src/core/GLES_COMPUTE/cs_shaders/concatenate.cs b/src/core/GLES_COMPUTE/cs_shaders/concatenate.cs
index 69ac50b4d0..49b3954fca 100644
--- a/src/core/GLES_COMPUTE/cs_shaders/concatenate.cs
+++ b/src/core/GLES_COMPUTE/cs_shaders/concatenate.cs
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -53,7 +53,7 @@ void main(void)
     Tensor3DIterator src_iter = CONVERT_TO_TENSOR3D_ITERATOR(src_attrs, src_shift);
     Tensor3DIterator dst_iter = CONVERT_TO_TENSOR3D_ITERATOR(dst_attrs, dst_shift);
 
-    float tmp = LOAD(src_ptr, TENSOR3D_OFFSET(src_iter, -OFFSET_X, -OFFSET_Y, 0));
+    float tmp = LOAD_CURRENT_ITEM(src_ptr, src_iter);
     STORE_CURRENT_ITEM(dst_ptr, dst_iter, tmp);
 }
 
@@ -66,7 +66,7 @@ void main(void)
     Tensor3DIterator src_iter = CONVERT_TO_TENSOR3D_ITERATOR(src_attrs, src_shift);
     Tensor3DIterator dst_iter = CONVERT_TO_TENSOR3D_ITERATOR(dst_attrs, dst_shift);
 
-    uvec2 tmp = LOAD(src_ptr, TENSOR3D_OFFSET(src_iter, -OFFSET_X, -OFFSET_Y, 0));
+    uvec2 tmp = LOAD_CURRENT_ITEM(src_ptr, src_iter);
     STORE_CURRENT_ITEM(dst_ptr, dst_iter, tmp);
 }
 #endif /*DATA_TYPE_FP16*/
diff --git a/src/core/GLES_COMPUTE/kernels/GCDepthConcatenateLayerKernel.cpp b/src/core/GLES_COMPUTE/kernels/GCDepthConcatenateLayerKernel.cpp
index 36d1b29bba..6f70efe5c7 100644
--- a/src/core/GLES_COMPUTE/kernels/GCDepthConcatenateLayerKernel.cpp
+++ b/src/core/GLES_COMPUTE/kernels/GCDepthConcatenateLayerKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -38,29 +38,19 @@
 using namespace arm_compute;
 
 GCDepthConcatenateLayerKernel::GCDepthConcatenateLayerKernel()
-    : _input(nullptr), _output(nullptr), _top_bottom(0), _left_right(0), _depth_offset(0)
+    : _input(nullptr), _output(nullptr), _depth_offset(0)
 {
 }
-
-BorderSize GCDepthConcatenateLayerKernel::border_size() const
-{
-    return BorderSize(_top_bottom, _left_right);
-}
-
 void GCDepthConcatenateLayerKernel::configure(const IGCTensor *input, unsigned int depth_offset, IGCTensor *output)
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+
+    ARM_COMPUTE_ERROR_ON(input->info()->dimension(Window::DimX) != output->info()->dimension(Window::DimX));
+    ARM_COMPUTE_ERROR_ON(input->info()->dimension(Window::DimY) != output->info()->dimension(Window::DimY));
     ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) + depth_offset > output->info()->dimension(2));
-    ARM_COMPUTE_ERROR_ON(input->info()->dimension(0) > output->info()->dimension(0));
-    ARM_COMPUTE_ERROR_ON(input->info()->dimension(1) > output->info()->dimension(1));
     ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(3, input, output);
 
-    // The gaps between the two lowest dimensions of input and output need to be divisible by 2
-    // Otherwise it is not clear how the padding should be added onto the input tensor
-    ARM_COMPUTE_ERROR_ON((output->info()->dimension(0) - input->info()->dimension(0)) % 2);
-    ARM_COMPUTE_ERROR_ON((output->info()->dimension(1) - input->info()->dimension(1)) % 2);
-
     _input        = input;
     _output       = output;
     _depth_offset = depth_offset;
@@ -73,35 +63,20 @@ void GCDepthConcatenateLayerKernel::configure(const IGCTensor *input, unsigned i
     build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1));
     build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1));
 
-    // Configure kernel window
-    _left_right = (output->info()->dimension(0) - input->info()->dimension(0)) / 2;
-    _top_bottom = (output->info()->dimension(1) - input->info()->dimension(1)) / 2;
-
-    build_opts.emplace("#define OFFSET_X " + support::cpp11::to_string(_left_right));
-    build_opts.emplace("#define OFFSET_Y " + support::cpp11::to_string(_top_bottom));
-
     // Create kernel
     _kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("concatenate_depth", build_opts));
 
     unsigned int num_elems_processed_per_iteration = 1;
-    unsigned int num_elems_read_per_iteration      = 1;
-    if(input->info()->data_type() == DataType::F32)
-    {
-        num_elems_processed_per_iteration = 1;
-        num_elems_read_per_iteration      = 1;
-    }
-    else if(input->info()->data_type() == DataType::F16)
+    if(input->info()->data_type() == DataType::F16)
     {
         num_elems_processed_per_iteration = 4;
-        num_elems_read_per_iteration      = 4;
     }
-    const unsigned int num_rows_read_per_iteration = 1;
 
     // The window needs to be based on input as we copy all the depths of input
     Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration));
     win.set(Window::DimZ, Window::Dimension(0, input->info()->tensor_shape().z(), 1));
 
-    AccessWindowRectangle  input_access(input->info(), -_left_right, -_top_bottom, num_elems_read_per_iteration, num_rows_read_per_iteration);
+    AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
     AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
     update_window_and_padding(win, input_access, output_access);
     output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape()));
@@ -118,11 +93,9 @@ void GCDepthConcatenateLayerKernel::run(const Window &window)
 
     _output->set_needs_shifting(true);
 
-    Window slice     = window.first_slice_window_3D();
     Window slice_in  = window.first_slice_window_3D();
     Window slice_out = window.first_slice_window_3D();
 
-    slice.shift(Window::DimX, -(_output->info()->padding()).left);
     slice_out.set(Window::DimZ, Window::Dimension(_depth_offset));
 
     do
@@ -133,7 +106,7 @@ void GCDepthConcatenateLayerKernel::run(const Window &window)
 
         _kernel.update_shader_params();
 
-        enqueue(*this, slice);
+        enqueue(*this, slice_in);
     }
-    while(window.slide_window_slice_3D(slice) && window.slide_window_slice_3D(slice_in));
+    while(window.slide_window_slice_3D(slice_in));
 }
diff --git a/src/core/NEON/kernels/NEDepthConcatenateLayerKernel.cpp b/src/core/NEON/kernels/NEDepthConcatenateLayerKernel.cpp
index 8352c94586..b360e9e6be 100644
--- a/src/core/NEON/kernels/NEDepthConcatenateLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEDepthConcatenateLayerKernel.cpp
@@ -42,18 +42,13 @@ using namespace arm_compute;
 namespace
 {
 template <typename T>
-void depth_concat(const ITensor *in, ITensor *out, std::pair<int, int> start_xy, int depth_offset, const Window &window)
+void depth_concat(const ITensor *in, ITensor *out, int depth_offset, const Window &window)
 {
-    const int start_x = start_xy.first;
-    const int start_y = start_xy.second;
-
     // Offset input
-    const int input_offset_to_first_elements_in_bytes = in->info()->offset_first_element_in_bytes() - start_x * in->info()->strides_in_bytes()[0] - start_y * in->info()->strides_in_bytes()[1];
-    uint8_t *input_ptr                               = in->buffer() + input_offset_to_first_elements_in_bytes;
+    uint8_t *input_ptr = in->buffer() + in->info()->offset_first_element_in_bytes();
 
     // Offset output
-    const unsigned int output_offset_to_first_elements_in_bytes = out->info()->offset_first_element_in_bytes() + depth_offset * out->info()->strides_in_bytes()[2];
-    uint8_t           *output_ptr                               = out->buffer() + output_offset_to_first_elements_in_bytes;
+    uint8_t *output_ptr = out->buffer() + out->info()->offset_first_element_in_bytes() + depth_offset * out->info()->strides_in_bytes()[2];
 
     Iterator input(in, window);
     Iterator output(out, window);
@@ -88,19 +83,13 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, unsi
 {
     ARM_COMPUTE_UNUSED(depth_offset);
 
-    // Configure kernel window
-    const int left_right = (output->dimension(0) - input->dimension(0)) / 2;
-    const int top_bottom = (output->dimension(1) - input->dimension(1)) / 2;
-
     const unsigned int num_elems_processed_per_iteration = 16 / input->element_size();
-    const unsigned int num_elems_read_per_iteration      = 16 / input->element_size();
-    const unsigned int num_rows_read_per_iteration       = 1;
 
     // The window needs to be based on input as we copy all the depths of input
     Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
     win.set(Window::DimZ, Window::Dimension(0, input->tensor_shape().z(), 1));
 
-    AccessWindowRectangle  input_access(input, -left_right, -top_bottom, num_elems_read_per_iteration, num_rows_read_per_iteration);
+    AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
     AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
     bool                   window_changed = update_window_and_padding(win, input_access, output_access);
     output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape()));
@@ -116,28 +105,18 @@ Status validate_arguments(const ITensorInfo *input, unsigned int depth_offset, c
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
 
+    ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimX) != output->dimension(Window::DimX));
+    ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimY) != output->dimension(Window::DimY));
     ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) + depth_offset > output->dimension(2));
-    ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(0) > output->dimension(0));
-    ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(1) > output->dimension(1));
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(3, input, output);
 
-    // The gaps between the two lowest dimensions of input and output need to be divisible by 2
-    // Otherwise it is not clear how the padding should be added onto the input tensor
-    ARM_COMPUTE_RETURN_ERROR_ON((output->dimension(0) - input->dimension(0)) % 2);
-    ARM_COMPUTE_RETURN_ERROR_ON((output->dimension(1) - input->dimension(1)) % 2);
-
     return Status{};
 }
 } // namespace
 
 NEDepthConcatenateLayerKernel::NEDepthConcatenateLayerKernel()
-    : _func(nullptr), _input(nullptr), _output(nullptr), _top_bottom(0), _left_right(0), _depth_offset(0)
-{
-}
-
-BorderSize NEDepthConcatenateLayerKernel::border_size() const
+    : _func(nullptr), _input(nullptr), _output(nullptr), _depth_offset(0)
 {
-    return BorderSize(_top_bottom, _left_right);
 }
 
 void NEDepthConcatenateLayerKernel::configure(const ITensor *input, unsigned int depth_offset, ITensor *output)
@@ -149,8 +128,6 @@ void NEDepthConcatenateLayerKernel::configure(const ITensor *input, unsigned int
     _input        = input;
     _output       = output;
     _depth_offset = depth_offset;
-    _left_right   = (output->info()->dimension(0) - input->info()->dimension(0)) / 2;
-    _top_bottom   = (output->info()->dimension(1) - input->info()->dimension(1)) / 2;
 
     switch(input->info()->data_type())
     {
@@ -190,5 +167,5 @@ void NEDepthConcatenateLayerKernel::run(const Window &window, const ThreadInfo &
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
     ARM_COMPUTE_ERROR_ON(_func == nullptr);
 
-    (*_func)(_input, _output, std::make_pair(_left_right, _top_bottom), _depth_offset, window);
+    (*_func)(_input, _output, _depth_offset, window);
 }
diff --git a/src/graph/nodes/ConcatenateLayerNode.cpp b/src/graph/nodes/ConcatenateLayerNode.cpp
index 48da8b6e9e..ff515c4427 100644
--- a/src/graph/nodes/ConcatenateLayerNode.cpp
+++ b/src/graph/nodes/ConcatenateLayerNode.cpp
@@ -68,6 +68,7 @@ TensorDescriptor ConcatenateLayerNode::compute_output_descriptor(const std::vect
 
     TensorDescriptor output_descriptor = input_descriptors[0];
     const int        axis_idx          = get_dimension_idx(output_descriptor.layout, axis);
+    ARM_COMPUTE_ERROR_ON_MSG(axis_idx > 2, "Unsupported concatenation axis!");
 
     // Extract shapes
     std::vector<const TensorShape *> shapes;
@@ -76,18 +77,7 @@ TensorDescriptor ConcatenateLayerNode::compute_output_descriptor(const std::vect
         shapes.emplace_back(&input_descriptor.shape);
     }
 
-    if(axis_idx < 2)
-    {
-        output_descriptor.shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(shapes, axis_idx);
-    }
-    else if(axis_idx == 2)
-    {
-        output_descriptor.shape = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(shapes);
-    }
-    else
-    {
-        ARM_COMPUTE_ERROR("Unsupported concatenation axis!");
-    }
+    output_descriptor.shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(shapes, axis_idx);
 
     return output_descriptor;
 }
diff --git a/src/runtime/CL/functions/CLConcatenateLayer.cpp b/src/runtime/CL/functions/CLConcatenateLayer.cpp
index b9b3c5bb80..b8224d2cce 100644
--- a/src/runtime/CL/functions/CLConcatenateLayer.cpp
+++ b/src/runtime/CL/functions/CLConcatenateLayer.cpp
@@ -56,15 +56,7 @@ void CLConcatenateLayer::configure(const std::vector<ICLTensor *> &inputs_vector
         ARM_COMPUTE_ERROR_ON_NULLPTR(t);
         return t->info();
     });
-    TensorShape output_shape{};
-    if(_axis == Window::DimZ)
-    {
-        output_shape = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector);
-    }
-    else
-    {
-        output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, _axis);
-    }
+    TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, _axis);
 
     // Output auto inizialitation if not yet initialized
     auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
@@ -143,19 +135,6 @@ Status CLConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vec
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
     ARM_COMPUTE_RETURN_ERROR_ON(num_inputs < 2);
 
-    // Output auto inizialitation if not yet initialized
-    TensorInfo  tmp_output_info = *output->clone();
-    TensorShape output_shape{};
-    if(axis == Window::DimZ)
-    {
-        output_shape = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector);
-    }
-    else
-    {
-        output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, axis);
-    }
-    auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
-
     unsigned int offset = 0;
     switch(axis)
     {
@@ -166,19 +145,19 @@ Status CLConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vec
                 case 2:
                     // Validate WidthConcatenate2Tensors kernels if there are 2 inputs
                     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(inputs_vector[0], inputs_vector[1]);
-                    ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenate2TensorsKernel::validate(inputs_vector[0], inputs_vector[1], &tmp_output_info));
+                    ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenate2TensorsKernel::validate(inputs_vector[0], inputs_vector[1], output));
                     break;
                 case 4:
                     // Validate WidthConcatenate4Tensors kernels if there are 4 inputs
                     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(inputs_vector[0], inputs_vector[1], inputs_vector[2], inputs_vector[3]);
-                    ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenate4TensorsKernel::validate(inputs_vector[0], inputs_vector[1], inputs_vector[2], inputs_vector[3], &tmp_output_info));
+                    ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenate4TensorsKernel::validate(inputs_vector[0], inputs_vector[1], inputs_vector[2], inputs_vector[3], output));
                     break;
                 default:
                     // Validate generic case of WidthConcatenate kernel
                     for(const auto &input : inputs_vector)
                     {
                         ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
-                        ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
+                        ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenateLayerKernel::validate(input, offset, output));
                         offset += input->dimension(axis);
                     }
                     break;
@@ -189,7 +168,7 @@ Status CLConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vec
         {
             for(const auto &input : inputs_vector)
             {
-                ARM_COMPUTE_RETURN_ON_ERROR(CLHeightConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
+                ARM_COMPUTE_RETURN_ON_ERROR(CLHeightConcatenateLayerKernel::validate(input, offset, output));
                 offset += input->dimension(axis);
             }
             break;
@@ -198,7 +177,7 @@ Status CLConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vec
         {
             for(const auto &input : inputs_vector)
             {
-                ARM_COMPUTE_RETURN_ON_ERROR(CLDepthConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
+                ARM_COMPUTE_RETURN_ON_ERROR(CLDepthConcatenateLayerKernel::validate(input, offset, output));
                 offset += input->dimension(axis);
             }
             break;
@@ -207,6 +186,12 @@ Status CLConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vec
             ARM_COMPUTE_ERROR("Axis not supported");
     }
 
+    if(output->total_size() != 0)
+    {
+        TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, axis);
+        ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() != output->tensor_shape().total_size());
+    }
+
     return Status{};
 }
 
diff --git a/src/runtime/CL/functions/CLDepthConcatenateLayer.cpp b/src/runtime/CL/functions/CLDepthConcatenateLayer.cpp
index e46647a20c..4a5f845631 100644
--- a/src/runtime/CL/functions/CLDepthConcatenateLayer.cpp
+++ b/src/runtime/CL/functions/CLDepthConcatenateLayer.cpp
@@ -56,7 +56,7 @@ void CLDepthConcatenateLayer::configure(const std::vector<ICLTensor *> &inputs_v
     _concat_kernels_vector  = arm_compute::support::cpp14::make_unique<CLDepthConcatenateLayerKernel[]>(_num_inputs);
     _border_handlers_vector = arm_compute::support::cpp14::make_unique<CLFillBorderKernel[]>(_num_inputs);
 
-    TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector_info);
+    TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector_info, Window::DimZ);
 
     // Output auto inizialitation if not yet initialized
     auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
@@ -82,7 +82,7 @@ Status CLDepthConcatenateLayer::validate(const std::vector<ITensorInfo *> &input
 
     // Output auto inizialitation if not yet initialized
     TensorInfo  tmp_output_info = *output->clone();
-    TensorShape output_shape    = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector);
+    TensorShape output_shape    = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimZ);
     auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
 
     unsigned int depth_offset = 0;
diff --git a/src/runtime/GLES_COMPUTE/functions/GCConcatenateLayer.cpp b/src/runtime/GLES_COMPUTE/functions/GCConcatenateLayer.cpp
new file mode 100644
index 0000000000..506f648171
--- /dev/null
+++ b/src/runtime/GLES_COMPUTE/functions/GCConcatenateLayer.cpp
@@ -0,0 +1,81 @@
+/*
+ * Copyright (c) 2019 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/runtime/GLES_COMPUTE/functions/GCConcatenateLayer.h"
+
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/GLES_COMPUTE/IGCTensor.h"
+#include "arm_compute/core/PixelValue.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h"
+#include "support/ToolchainSupport.h"
+
+namespace arm_compute
+{
+GCConcatenateLayer::GCConcatenateLayer()
+    : _concat_kernels(),
+      _num_inputs(0),
+      _axis(Window::DimZ)
+{
+}
+
+void GCConcatenateLayer::configure(std::vector<IGCTensor *> inputs_vector, IGCTensor *output, size_t axis)
+{
+    ARM_COMPUTE_ERROR_ON(inputs_vector.size() < 2);
+
+    _num_inputs = inputs_vector.size();
+    _axis       = axis;
+
+    TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, axis);
+
+    // Output auto inizialitation if not yet initialized
+    auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
+
+    unsigned int offset = 0;
+    switch(axis)
+    {
+        case Window::DimZ:
+        {
+            for(unsigned int i = 0; i < _num_inputs; ++i)
+            {
+                auto kernel = support::cpp14::make_unique<GCDepthConcatenateLayerKernel>();
+                kernel->configure(inputs_vector.at(i), offset, output);
+                offset += inputs_vector.at(i)->info()->dimension(axis);
+                _concat_kernels.emplace_back(std::move(kernel));
+            }
+            break;
+        }
+        default:
+            ARM_COMPUTE_ERROR("Axis not supported");
+    }
+}
+
+void GCConcatenateLayer::run()
+{
+    for(auto &kernel : _concat_kernels)
+    {
+        GCScheduler::get().dispatch(*kernel, true);
+    }
+}
+} // namespace arm_compute
diff --git a/src/runtime/NEON/functions/NEConcatenateLayer.cpp b/src/runtime/NEON/functions/NEConcatenateLayer.cpp
index e02c0c2c7a..b8cfa2b8f2 100644
--- a/src/runtime/NEON/functions/NEConcatenateLayer.cpp
+++ b/src/runtime/NEON/functions/NEConcatenateLayer.cpp
@@ -56,15 +56,7 @@ void NEConcatenateLayer::configure(const std::vector<ITensor *> &inputs_vector,
         ARM_COMPUTE_ERROR_ON_NULLPTR(inputs_vector.at(i));
         inputs_vector_info.emplace_back(inputs_vector.at(i)->info());
     }
-    TensorShape output_shape{};
-    if(_axis == Window::DimZ)
-    {
-        output_shape = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector);
-    }
-    else
-    {
-        output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, _axis);
-    }
+    TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, _axis);
 
     // Output auto inizialitation if not yet initialized
     auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
@@ -109,19 +101,6 @@ Status NEConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vec
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
     ARM_COMPUTE_RETURN_ERROR_ON(inputs_vector.size() < 2);
 
-    // Output auto inizialitation if not yet initialized
-    TensorInfo  tmp_output_info = *output->clone();
-    TensorShape output_shape{};
-    if(axis == Window::DimZ)
-    {
-        output_shape = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector);
-    }
-    else
-    {
-        output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, axis);
-    }
-    auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
-
     unsigned int offset = 0;
     for(const auto &input : inputs_vector)
     {
@@ -130,17 +109,17 @@ Status NEConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vec
         {
             case Window::DimX:
             {
-                ARM_COMPUTE_RETURN_ON_ERROR(NEWidthConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
+                ARM_COMPUTE_RETURN_ON_ERROR(NEWidthConcatenateLayerKernel::validate(input, offset, output));
                 break;
             }
             case Window::DimY:
             {
-                ARM_COMPUTE_RETURN_ON_ERROR(NEHeightConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
+                ARM_COMPUTE_RETURN_ON_ERROR(NEHeightConcatenateLayerKernel::validate(input, offset, output));
                 break;
             }
             case Window::DimZ:
             {
-                ARM_COMPUTE_RETURN_ON_ERROR(NEDepthConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
+                ARM_COMPUTE_RETURN_ON_ERROR(NEDepthConcatenateLayerKernel::validate(input, offset, output));
                 break;
             }
             default:
@@ -149,6 +128,12 @@ Status NEConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vec
         offset += input->dimension(axis);
     }
 
+    if(output->total_size() != 0)
+    {
+        TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, axis);
+        ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() != output->tensor_shape().total_size());
+    }
+
     return Status{};
 }
 
diff --git a/src/runtime/NEON/functions/NEDepthConcatenateLayer.cpp b/src/runtime/NEON/functions/NEDepthConcatenateLayer.cpp
index 49db855f21..b814bffa96 100644
--- a/src/runtime/NEON/functions/NEDepthConcatenateLayer.cpp
+++ b/src/runtime/NEON/functions/NEDepthConcatenateLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -54,7 +54,7 @@ void NEDepthConcatenateLayer::configure(const std::vector<ITensor *> &inputs_vec
     {
         inputs_vector_info.emplace_back(inputs_vector.at(i)->info());
     }
-    TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector_info);
+    TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector_info, Window::DimZ);
 
     // Output auto inizialitation if not yet initialized
     auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
@@ -80,7 +80,7 @@ Status NEDepthConcatenateLayer::validate(const std::vector<ITensorInfo *> &input
 
     // Output auto inizialitation if not yet initialized
     TensorInfo  tmp_output_info = *output->clone();
-    TensorShape output_shape    = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector);
+    TensorShape output_shape    = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, Window::DimZ);
     auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
 
     unsigned int depth_offset = 0;
diff --git a/tests/benchmark/fixtures/DepthConcatenateLayerFixture.h b/tests/benchmark/fixtures/DepthConcatenateLayerFixture.h
index 7f7ed8b20b..4db27e707a 100644
--- a/tests/benchmark/fixtures/DepthConcatenateLayerFixture.h
+++ b/tests/benchmark/fixtures/DepthConcatenateLayerFixture.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -100,7 +100,7 @@ public:
             src_ptrs.emplace_back(&_srcs.back());
         }
 
-        TensorShape dst_shape = misc::shape_calculator::calculate_depth_concatenate_shape(src_ptrs);
+        TensorShape dst_shape = misc::shape_calculator::calculate_concatenate_shape(src_ptrs, Window::DimZ);
         _dst                  = create_tensor<TensorType>(dst_shape, data_type, 1);
 
         _depth_concat.configure(src_ptrs, &_dst);
diff --git a/tests/validation/CL/DepthConcatenateLayer.cpp b/tests/validation/CL/DepthConcatenateLayer.cpp
index 5da8a34351..beda637ef3 100644
--- a/tests/validation/CL/DepthConcatenateLayer.cpp
+++ b/tests/validation/CL/DepthConcatenateLayer.cpp
@@ -83,8 +83,8 @@ TEST_CASE(Configuration, framework::DatasetMode::ALL)
 {
     // Create tensors
     CLTensor src1 = create_tensor<CLTensor>(TensorShape(128U, 32U, 32U), DataType::F32, 1);
-    CLTensor src2 = create_tensor<CLTensor>(TensorShape(32U, 32U, 32U), DataType::F32, 1);
-    CLTensor src3 = create_tensor<CLTensor>(TensorShape(16U, 32U, 32U), DataType::F32, 1);
+    CLTensor src2 = create_tensor<CLTensor>(TensorShape(128U, 32U, 32U), DataType::F32, 1);
+    CLTensor src3 = create_tensor<CLTensor>(TensorShape(128U, 32U, 32U), DataType::F32, 1);
     CLTensor dst;
 
     ARM_COMPUTE_EXPECT(src1.info()->is_resizable(), framework::LogLevel::ERRORS);
diff --git a/tests/validation/CL/LSTMLayer.cpp b/tests/validation/CL/LSTMLayer.cpp
index ea20bd6c2c..71a9383d93 100644
--- a/tests/validation/CL/LSTMLayer.cpp
+++ b/tests/validation/CL/LSTMLayer.cpp
@@ -109,7 +109,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                         TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
-                                                        TensorInfo(TensorShape(11U, 13U), 1, DataType::F32),
+                                                        TensorInfo(TensorShape(11U, 2U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
                })),
                framework::dataset::make("ScratchInfo", { TensorInfo(TensorShape(64U, 2U), 1, DataType::F32),
diff --git a/tests/validation/GLES_COMPUTE/DepthConcatenateLayer.cpp b/tests/validation/GLES_COMPUTE/DepthConcatenateLayer.cpp
index 7af3050c1d..04e91d63ae 100644
--- a/tests/validation/GLES_COMPUTE/DepthConcatenateLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/DepthConcatenateLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -24,14 +24,14 @@
 #include "arm_compute/core/Types.h"
 #include "arm_compute/runtime/GLES_COMPUTE/GCTensor.h"
 #include "arm_compute/runtime/GLES_COMPUTE/GCTensorAllocator.h"
-#include "arm_compute/runtime/GLES_COMPUTE/functions/GCDepthConcatenateLayer.h"
+#include "arm_compute/runtime/GLES_COMPUTE/functions/GCConcatenateLayer.h"
 #include "tests/GLES_COMPUTE/GCAccessor.h"
 #include "tests/datasets/ShapeDatasets.h"
 #include "tests/framework/Asserts.h"
 #include "tests/framework/Macros.h"
 #include "tests/framework/datasets/Datasets.h"
 #include "tests/validation/Validation.h"
-#include "tests/validation/fixtures/DepthConcatenateLayerFixture.h"
+#include "tests/validation/fixtures/ConcatenateLayerFixture.h"
 
 namespace arm_compute
 {
@@ -42,21 +42,23 @@ namespace validation
 TEST_SUITE(GC)
 TEST_SUITE(DepthConcatenateLayer)
 
-//TODO(COMPMID-415): Add configuration test?
-
 template <typename T>
-using GCDepthConcatenateLayerFixture = DepthConcatenateLayerValidationFixture<GCTensor, IGCTensor, GCAccessor, GCDepthConcatenateLayer, T>;
+using GCDepthConcatenateLayerFixture = ConcatenateLayerValidationFixture<GCTensor, IGCTensor, GCAccessor, GCConcatenateLayer, T>;
 
 TEST_SUITE(Float)
 TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(RunSmall, GCDepthConcatenateLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::Small2DShapes(), framework::dataset::make("DataType",
-                                                                                                                  DataType::F16)))
+FIXTURE_DATA_TEST_CASE(RunSmall, GCDepthConcatenateLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::Small3DShapes(),
+                                                                                                                  framework::dataset::make("DataType",
+                                                                                                                          DataType::F16)),
+                                                                                                                  framework::dataset::make("Axis", 2)))
 {
     // Validate output
     validate(GCAccessor(_target), _reference);
 }
-FIXTURE_DATA_TEST_CASE(RunLarge, GCDepthConcatenateLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(datasets::Large2DShapes(), framework::dataset::make("DataType",
-                                                                                                                DataType::F16)))
+FIXTURE_DATA_TEST_CASE(RunLarge, GCDepthConcatenateLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::Large3DShapes(),
+                                                                                                                        framework::dataset::make("DataType",
+                                                                                                                                DataType::F16)),
+                                                                                                                framework::dataset::make("Axis", 2)))
 {
     // Validate output
     validate(GCAccessor(_target), _reference);
@@ -64,14 +66,17 @@ FIXTURE_DATA_TEST_CASE(RunLarge, GCDepthConcatenateLayerFixture<half>, framework
 TEST_SUITE_END()
 
 TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(RunSmall, GCDepthConcatenateLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::Small2DShapes(), framework::dataset::make("DataType",
-                                                                                                                   DataType::F32)))
+FIXTURE_DATA_TEST_CASE(RunSmall, GCDepthConcatenateLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::Small3DShapes(),
+                                                                                                                   framework::dataset::make("DataType",
+                                                                                                                           DataType::F32)),
+                                                                                                                   framework::dataset::make("Axis", 2)))
 {
     // Validate output
     validate(GCAccessor(_target), _reference);
 }
-FIXTURE_DATA_TEST_CASE(RunLarge, GCDepthConcatenateLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::DepthConcatenateLayerShapes(), framework::dataset::make("DataType",
-                                                                                                                 DataType::F32)))
+FIXTURE_DATA_TEST_CASE(RunLarge, GCDepthConcatenateLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::Large3DShapes(), framework::dataset::make("DataType",
+                                                                                                                 DataType::F32)),
+                                                                                                                 framework::dataset::make("Axis", 2)))
 {
     // Validate output
     validate(GCAccessor(_target), _reference);
diff --git a/tests/validation/Helpers.cpp b/tests/validation/Helpers.cpp
index e9612f2223..504dbfd3a4 100644
--- a/tests/validation/Helpers.cpp
+++ b/tests/validation/Helpers.cpp
@@ -74,46 +74,6 @@ void fill_mask_from_pattern(uint8_t *mask, int cols, int rows, MatrixPattern pat
     }
 }
 
-TensorShape calculate_depth_concatenate_shape(const std::vector<TensorShape> &input_shapes)
-{
-    ARM_COMPUTE_ERROR_ON(input_shapes.empty());
-
-    TensorShape out_shape = input_shapes[0];
-
-    size_t max_x = 0;
-    size_t max_y = 0;
-    size_t depth = 0;
-
-    for(const auto &shape : input_shapes)
-    {
-        max_x = std::max(shape.x(), max_x);
-        max_y = std::max(shape.y(), max_y);
-        depth += shape.z();
-    }
-
-    out_shape.set(0, max_x);
-    out_shape.set(1, max_y);
-    out_shape.set(2, depth);
-
-    return out_shape;
-}
-
-TensorShape calculate_concatenate_shape(const std::vector<TensorShape> &input_shapes, size_t axis)
-{
-    ARM_COMPUTE_ERROR_ON(input_shapes.empty());
-    TensorShape out_shape = input_shapes[0];
-    ARM_COMPUTE_ERROR_ON(axis >= out_shape.num_dimensions());
-
-    const int new_size = std::accumulate(input_shapes.begin(), input_shapes.end(), 0, [&](int sum, const TensorShape & shape)
-    {
-        ARM_COMPUTE_ERROR_ON(axis >= shape.num_dimensions());
-        return sum + shape[axis];
-    });
-    out_shape.set(axis, new_size);
-
-    return out_shape;
-}
-
 HarrisCornersParameters harris_corners_parameters()
 {
     HarrisCornersParameters params;
diff --git a/tests/validation/NEON/LSTMLayer.cpp b/tests/validation/NEON/LSTMLayer.cpp
index 5dfd32b8e5..b27dfae8fa 100644
--- a/tests/validation/NEON/LSTMLayer.cpp
+++ b/tests/validation/NEON/LSTMLayer.cpp
@@ -109,7 +109,7 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zi
                                                         TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
-                                                        TensorInfo(TensorShape(11U, 13U), 1, DataType::F32),
+                                                        TensorInfo(TensorShape(11U, 2U), 1, DataType::F32),
                                                         TensorInfo(TensorShape(16U, 2U), 1, DataType::F32),
                })),
                framework::dataset::make("ScratchInfo", { TensorInfo(TensorShape(64U, 2U), 1, DataType::F32),
diff --git a/tests/validation/fixtures/ConcatenateLayerFixture.h b/tests/validation/fixtures/ConcatenateLayerFixture.h
index 39d4f9f95d..d1eed63d41 100644
--- a/tests/validation/fixtures/ConcatenateLayerFixture.h
+++ b/tests/validation/fixtures/ConcatenateLayerFixture.h
@@ -73,7 +73,7 @@ public:
         // Generate more shapes based on the input
         for(auto &s : shapes)
         {
-            // Randomly change the first dimension
+            // Randomly change the dimension
             if(mutate_dis(gen))
             {
                 // Decrease the dimension by a small percentage. Don't increase
@@ -144,18 +144,20 @@ protected:
         return dst;
     }
 
-    SimpleTensor<T> compute_reference(const std::vector<TensorShape> &shapes, const std::vector<QuantizationInfo> &qinfo, DataType data_type, unsigned int axis)
+    SimpleTensor<T> compute_reference(std::vector<TensorShape> &shapes, const std::vector<QuantizationInfo> &qinfo, DataType data_type, unsigned int axis)
     {
         std::vector<SimpleTensor<T>> srcs;
+        std::vector<TensorShape *>   src_ptrs;
 
         // Create and fill tensors
         for(size_t j = 0; j < shapes.size(); ++j)
         {
             srcs.emplace_back(shapes[j], data_type, 1, qinfo[j]);
             fill(srcs.back(), j);
+            src_ptrs.emplace_back(&shapes[j]);
         }
 
-        const TensorShape dst_shape = calculate_concatenate_shape(shapes, axis);
+        const TensorShape dst_shape = misc::shape_calculator::calculate_concatenate_shape(src_ptrs, axis);
         SimpleTensor<T>   dst{ dst_shape, data_type, 1, qinfo[shapes.size()] };
         return reference::concatenate_layer<T>(srcs, dst, axis);
     }
diff --git a/tests/validation/fixtures/DepthConcatenateLayerFixture.h b/tests/validation/fixtures/DepthConcatenateLayerFixture.h
deleted file mode 100644
index edeefa228a..0000000000
--- a/tests/validation/fixtures/DepthConcatenateLayerFixture.h
+++ /dev/null
@@ -1,183 +0,0 @@
-/*
- * Copyright (c) 2017-2019 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 "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/DepthConcatenateLayer.h"
-
-#include <random>
-
-namespace arm_compute
-{
-namespace test
-{
-namespace validation
-{
-template <typename TensorType, typename ITensorType, typename AccessorType, typename FunctionType, typename T>
-class DepthConcatenateLayerValidationFixture : 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, 4);
-        std::uniform_int_distribution<> offset_dis(0, 20);
-
-        const int num_tensors = num_dis(gen);
-
-        std::vector<TensorShape> shapes(num_tensors, shape);
-
-        // vector holding the quantization info:
-        //      the last element is the output quantization info
-        //      all other elements are the quantization info for the input tensors
-        std::vector<QuantizationInfo> qinfo(num_tensors + 1, QuantizationInfo());
-
-        for(auto &qi : qinfo)
-        {
-            qi = QuantizationInfo(1.f / 255.f, offset_dis(gen));
-        }
-
-        std::uniform_int_distribution<>  depth_dis(1, 3);
-        std::bernoulli_distribution      mutate_dis(0.5f);
-        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, qinfo, data_type);
-        _reference = compute_reference(shapes, qinfo, 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, const std::vector<QuantizationInfo> &qinfo, DataType data_type)
-    {
-        std::vector<TensorType>    srcs;
-        std::vector<ITensorType *> src_ptrs;
-
-        // Create tensors
-        srcs.reserve(shapes.size());
-
-        for(size_t j = 0; j < shapes.size(); ++j)
-        {
-            srcs.emplace_back(create_tensor<TensorType>(shapes[j], data_type, 1, qinfo[j]));
-            src_ptrs.emplace_back(&srcs.back());
-        }
-
-        TensorShape dst_shape = misc::shape_calculator::calculate_depth_concatenate_shape(src_ptrs);
-        TensorType  dst       = create_tensor<TensorType>(dst_shape, data_type, 1, qinfo[shapes.size()]);
-
-        // 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, const std::vector<QuantizationInfo> &qinfo, DataType data_type)
-    {
-        std::vector<SimpleTensor<T>> srcs;
-
-        // Create and fill tensors
-        for(size_t j = 0; j < shapes.size(); ++j)
-        {
-            srcs.emplace_back(shapes[j], data_type, 1, qinfo[j]);
-            fill(srcs.back(), j);
-        }
-
-        const TensorShape dst_shape = calculate_depth_concatenate_shape(shapes);
-        SimpleTensor<T>   dst{ dst_shape, data_type, 1, qinfo[shapes.size()] };
-
-        return reference::depthconcatenate_layer<T>(srcs, dst);
-    }
-
-    TensorType      _target{};
-    SimpleTensor<T> _reference{};
-};
-} // namespace validation
-} // namespace test
-} // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_DEPTHCONCATENATE_LAYER_FIXTURE */