COMPMID-1364: Add support for NHWC in NEDepthConcatenateLayer

Change-Id: I4f8e46d1c79afa9284f2c6dc00383c453a8e7bd5
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/140165
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>

20 files changed, 887 insertions, 57 deletions

diff --git a/arm_compute/core/NEON/NEKernels.h b/arm_compute/core/NEON/NEKernels.h
index b9c54b2c25..156b116ce0 100644
--- a/arm_compute/core/NEON/NEKernels.h
+++ b/arm_compute/core/NEON/NEKernels.h
@@ -112,6 +112,7 @@
 #include "arm_compute/core/NEON/kernels/NETransposeKernel.h"
 #include "arm_compute/core/NEON/kernels/NEWarpKernel.h"
 #include "arm_compute/core/NEON/kernels/NEWeightsReshapeKernel.h"
+#include "arm_compute/core/NEON/kernels/NEWidthConcatenateLayerKernel.h"
 #include "arm_compute/core/NEON/kernels/NEWinogradConvolutionLayerKernel.h"
 
 #endif /* __ARM_COMPUTE_NEKERNELS_H__ */
diff --git a/arm_compute/core/NEON/kernels/NEDepthConcatenateLayerKernel.h b/arm_compute/core/NEON/kernels/NEDepthConcatenateLayerKernel.h
index 12a5051ef8..848d89fc9f 100644
--- a/arm_compute/core/NEON/kernels/NEDepthConcatenateLayerKernel.h
+++ b/arm_compute/core/NEON/kernels/NEDepthConcatenateLayerKernel.h
@@ -55,7 +55,7 @@ public:
     ~NEDepthConcatenateLayerKernel() = default;
     /** Initialise the kernel's inputs and output
      *
-     * @param[in]     input        Input tensor. Data types supported: F16/F32.
+     * @param[in]     input        Input tensor. Data types supported: QASYMM8/F16/F32.
      * @param[in]     depth_offset The offset on the Z axis.
      * @param[in,out] output       Output tensor. Data types supported: Same as @p input.
      *
@@ -64,6 +64,15 @@ public:
      *
      */
     void configure(const ITensor *input, unsigned int depth_offset, ITensor *output);
+    /**  Static function to check if given info will lead to a valid configuration of @ref NEDepthConcatenateLayerKernel
+     *
+     * @param[in] input        Input tensor info. Data types supported: QASYMM8/F16/F32.
+     * @param[in] depth_offset The offset on the Z axis.
+     * @param[in] output       Output tensor info. Data types supported: Same as @p input.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, unsigned int depth_offset, const ITensorInfo *output);
 
     // Inherited methods overridden:
     void run(const Window &window, const ThreadInfo &info) override;
diff --git a/arm_compute/core/NEON/kernels/NEWidthConcatenateLayerKernel.h b/arm_compute/core/NEON/kernels/NEWidthConcatenateLayerKernel.h
new file mode 100644
index 0000000000..4cf32736e9
--- /dev/null
+++ b/arm_compute/core/NEON/kernels/NEWidthConcatenateLayerKernel.h
@@ -0,0 +1,84 @@
+/*
+ * 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_NEWIDTHCONCATENATELAYERKERNEL_H__
+#define __ARM_COMPUTE_NEWIDTHCONCATENATELAYERKERNEL_H__
+
+#include "arm_compute/core/NEON/INEKernel.h"
+#include "arm_compute/core/Types.h"
+
+namespace arm_compute
+{
+class ITensor;
+
+/** Interface for the width concatenate kernel.
+ *  The input tensor will be concatenated into the output tensor.
+ */
+class NEWidthConcatenateLayerKernel : public INEKernel
+{
+public:
+    const char *name() const override
+    {
+        return "NEWidthConcatenateLayerKernel";
+    }
+    /** Default constructor */
+    NEWidthConcatenateLayerKernel();
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    NEWidthConcatenateLayerKernel(const NEWidthConcatenateLayerKernel &) = delete;
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    NEWidthConcatenateLayerKernel &operator=(const NEWidthConcatenateLayerKernel &) = delete;
+    /** Allow instances of this class to be moved */
+    NEWidthConcatenateLayerKernel(NEWidthConcatenateLayerKernel &&) = default;
+    /** Allow instances of this class to be moved */
+    NEWidthConcatenateLayerKernel &operator=(NEWidthConcatenateLayerKernel &&) = default;
+    /** Default destructor */
+    ~NEWidthConcatenateLayerKernel() = default;
+    /** Initialise the kernel's inputs and output
+     *
+     * @param[in]     input        Input tensor. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32
+     * @param[in]     width_offset The offset on the X axis.
+     * @param[in,out] output       Output tensor. Data types supported: Same as @p input.
+     *
+     */
+    void configure(const ITensor *input, unsigned int width_offset, ITensor *output);
+    /**  Static function to check if given info will lead to a valid configuration of @ref NEWidthConcatenateLayerKernel
+     *
+     * @param[in] input        Input tensor info. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32
+     * @param[in] width_offset The offset on the X axis.
+     * @param[in] output       Output tensor info. Data types supported: Same as @p input.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, unsigned int width_offset, const ITensorInfo *output);
+
+    // Inherited methods overridden:
+    void run(const Window &window, const ThreadInfo &info) override;
+
+private:
+    const ITensor *_input;
+    ITensor       *_output;
+    unsigned int   _width_offset;
+};
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_NEWIDTHCONCATENATELAYERKERNEL_H__ */
diff --git a/arm_compute/runtime/CL/functions/CLConcatenateLayer.h b/arm_compute/runtime/CL/functions/CLConcatenateLayer.h
index 018c58942f..4d4c62434a 100644
--- a/arm_compute/runtime/CL/functions/CLConcatenateLayer.h
+++ b/arm_compute/runtime/CL/functions/CLConcatenateLayer.h
@@ -57,7 +57,7 @@ public:
      * @param[out]    output        Output tensor. Data types supported: Same as @p input.
      * @param[in]     axis          Concatenation axis. Supported underlying concatenation axis are 0 and 2.
      */
-    void configure(std::vector<ICLTensor *> inputs_vector, ICLTensor *output, DataLayoutDimension axis);
+    void configure(const std::vector<ICLTensor *> &inputs_vector, ICLTensor *output, DataLayoutDimension axis);
     /** Static function to check if given info will lead to a valid configuration of @ref CLConcatenateLayer
      *
      * @note Input and output tensor dimensions preconditions defer depending on the concatenation axis.
diff --git a/arm_compute/runtime/CL/functions/CLDepthConcatenateLayer.h b/arm_compute/runtime/CL/functions/CLDepthConcatenateLayer.h
index bafce1c66f..aef5d63654 100644
--- a/arm_compute/runtime/CL/functions/CLDepthConcatenateLayer.h
+++ b/arm_compute/runtime/CL/functions/CLDepthConcatenateLayer.h
@@ -63,7 +63,7 @@ public:
      *                              while width and height are the maximum width and height of the input tensors.
      *                              Finally, depth is the sum of the input depths.
      */
-    void configure(std::vector<ICLTensor *> inputs_vector, ICLTensor *output);
+    void configure(const std::vector<ICLTensor *> &inputs_vector, ICLTensor *output);
     /** Static function to check if given info will lead to a valid configuration of @ref CLDepthConcatenateLayer
      *
      * @param[in] inputs_vector The vectors containing all the tensors to concatenate. Data types supported: QASYMM8/F16/F32.
diff --git a/arm_compute/runtime/NEON/NEFunctions.h b/arm_compute/runtime/NEON/NEFunctions.h
index 988eb3b791..6a3fabca67 100644
--- a/arm_compute/runtime/NEON/NEFunctions.h
+++ b/arm_compute/runtime/NEON/NEFunctions.h
@@ -41,6 +41,7 @@
 #include "arm_compute/runtime/NEON/functions/NEChannelExtract.h"
 #include "arm_compute/runtime/NEON/functions/NECol2Im.h"
 #include "arm_compute/runtime/NEON/functions/NEColorConvert.h"
+#include "arm_compute/runtime/NEON/functions/NEConcatenateLayer.h"
 #include "arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h"
 #include "arm_compute/runtime/NEON/functions/NEConvolution.h"
 #include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h"
@@ -112,6 +113,7 @@
 #include "arm_compute/runtime/NEON/functions/NETranspose.h"
 #include "arm_compute/runtime/NEON/functions/NEWarpAffine.h"
 #include "arm_compute/runtime/NEON/functions/NEWarpPerspective.h"
+#include "arm_compute/runtime/NEON/functions/NEWidthConcatenateLayer.h"
 #include "arm_compute/runtime/NEON/functions/NEWinogradConvolutionLayer.h"
 
 #endif /* __ARM_COMPUTE_NEFUNCTIONS_H__ */
\ No newline at end of file
diff --git a/arm_compute/runtime/NEON/functions/NEConcatenateLayer.h b/arm_compute/runtime/NEON/functions/NEConcatenateLayer.h
new file mode 100644
index 0000000000..2cdc720fb6
--- /dev/null
+++ b/arm_compute/runtime/NEON/functions/NEConcatenateLayer.h
@@ -0,0 +1,81 @@
+/*
+ * 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_NECONCATENATELAYER_H__
+#define __ARM_COMPUTE_NECONCATENATELAYER_H__
+
+#include "arm_compute/runtime/IFunction.h"
+
+#include "arm_compute/core/Types.h"
+
+#include <memory>
+#include <vector>
+
+namespace arm_compute
+{
+// Forward declarations
+class ITensor;
+class ITensorInfo;
+class Status;
+
+/** Basic function to execute concatenate tensors along a given axis. This function calls the following kernels:
+ *
+ * -# @ref NEWidthConcatenateLayer (if underlying concatenation axis is 0).
+ * -# @ref NEDepthConcatenateLayer (if underlying concatenation axis is 2).
+ */
+class NEConcatenateLayer : public IFunction
+{
+public:
+    /** Default constructor */
+    NEConcatenateLayer();
+    /** Initialise the kernel's inputs vector and output.
+     *
+     * @note Input and output tensor dimensions preconditions defer depending on the concatenation axis.
+     * @note Preconditions can be found respectively at @ref NEWidthConcatenateLayer and @ref NEDepthConcatenateLayer.
+     *
+     * @param[in,out] inputs_vector The vectors containing all the tensors to concatenate. Data types supported: QASYMM8/F16/F32.
+     * @param[out]    output        Output tensor. Data types supported: Same as @p input.
+     * @param[in]     axis          Concatenation axis. Supported underlying concatenation axis are 0 and 2.
+     */
+    void configure(const std::vector<ITensor *> &inputs_vector, ITensor *output, DataLayoutDimension axis);
+    /** Static function to check if given info will lead to a valid configuration of @ref NEConcatenateLayer
+     *
+     * @note Input and output tensor dimensions preconditions defer depending on the concatenation axis.
+     * @note Preconditions can be found respectively at @ref NEWidthConcatenateLayer and @ref NEDepthConcatenateLayer.
+     *
+     * @param[in] inputs_vector The vectors containing all the tensors info to concatenate. Data types supported: QASYMM8/F16/F32.
+     * @param[in] output        Output tensor info. Data types supported: Same as @p input.
+     * @param[in] axis          Concatenation axis. Supported underlying concatenation axis are 0 and 2.
+     *
+     * @return a status
+     */
+    static Status validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, DataLayoutDimension axis);
+
+    // Inherited methods overridden:
+    void run() override;
+
+private:
+    std::unique_ptr<IFunction> _concat_function;
+};
+}
+#endif /* __ARM_COMPUTE_NECONCATENATELAYER_H__ */
diff --git a/arm_compute/runtime/NEON/functions/NEDepthConcatenateLayer.h b/arm_compute/runtime/NEON/functions/NEDepthConcatenateLayer.h
index eefb5fa362..e2162ef042 100644
--- a/arm_compute/runtime/NEON/functions/NEDepthConcatenateLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEDepthConcatenateLayer.h
@@ -49,10 +49,34 @@ public:
     NEDepthConcatenateLayer();
     /** Initialise the kernel's inputs vector and output.
      *
-     * @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 inputs_vector.
+     * @param[in,out] inputs_vector The vectors containing all the tensors to concatenate. Data types supported: QASYMM8/F16/F32.
+     *                              Input dimensions might differ for each input for the first three dimensions (width, height, depth)
+     *                              and must match for the rest.
+     *                              Note that the difference between the minimum and maximum width and height among the input tensors
+     *                              must be divisible by 2 otherwise it is not clear how padding should be added on the inputs' width and
+     *                              height when they are less than the maximum input sizes.
+     * @param[out]    output        Output tensor. Data types supported: Same as @p input.
+     *                              Output tensor dimensions match the inputs' ones from the fourth dimension and above,
+     *                              while width and height are the maximum width and height of the input tensors.
+     *                              Finally, depth is the sum of the input depths.
      */
-    void configure(std::vector<ITensor *> inputs_vector, ITensor *output);
+    void configure(const std::vector<ITensor *> &inputs_vector, ITensor *output);
+    /** Static function to check if given info will lead to a valid configuration of @ref NEDepthConcatenateLayer
+     *
+     * @param[in] inputs_vector The vectors containing all the tensors to concatenate. Data types supported: QASYMM8/F16/F32.
+     *                          Input dimensions might differ for each input for the first three dimensions (width, height, depth)
+     *                          and must match for the rest.
+     *                          Note that the difference between the minimum and maximum width and height among the input tensors
+     *                          must be divisible by 2 otherwise it is not clear how padding should be added on the inputs' width and
+     *                          height when they are less than the maximum input sizes.
+     * @param[in] output        Output tensor. Data types supported: Same as @p input.
+     *                          Output tensor dimensions match the inputs' ones from the fourth dimension and above,
+     *                          while width and height are the maximum width and height of the input tensors.
+     *                          Finally, depth is the sum of the input depths.
+     *
+     * @return a status
+     */
+    static Status validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output);
 
     // Inherited methods overridden:
     void run() override;
diff --git a/arm_compute/runtime/NEON/functions/NEWidthConcatenateLayer.h b/arm_compute/runtime/NEON/functions/NEWidthConcatenateLayer.h
new file mode 100644
index 0000000000..e68525fa76
--- /dev/null
+++ b/arm_compute/runtime/NEON/functions/NEWidthConcatenateLayer.h
@@ -0,0 +1,79 @@
+/*
+ * 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_NEWIDTHCONCATENATELAYER_H__
+#define __ARM_COMPUTE_NEWIDTHCONCATENATELAYER_H__
+
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Window.h"
+#include "arm_compute/runtime/IFunction.h"
+
+#include "arm_compute/core/NEON/kernels/NEWidthConcatenateLayerKernel.h"
+
+#include <memory>
+#include <vector>
+
+namespace arm_compute
+{
+// Forward declarations
+class ITensor;
+
+/** Basic function to execute concatenate tensors along x axis. This function calls the following kernel:
+ *
+ * -# @ref NEWidthConcatenateLayerKernel
+ */
+class NEWidthConcatenateLayer : public IFunction
+{
+public:
+    /** Default constructor */
+    NEWidthConcatenateLayer();
+    /** Initialise the kernel's inputs vector and output.
+     *
+     * @param[in]  inputs_vector The vectors containing all the tensors to concatenate. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32.
+     *                           Dimensions of all the inputs should match apart for the width which can differ.
+     * @param[out] output        Output tensor. Data types supported: Same as @p input.
+     *                           Output tensor dimensions are the same with the inputs from the second dimension and above.
+     *                           The first dimension (width) is the sum of the input tensors' widths.
+     */
+    void configure(std::vector<ITensor *> inputs_vector, ITensor *output);
+    /** Static function to check if given info will lead to a valid configuration of @ref NEWidthConcatenateLayer
+     *
+     * @param[in] inputs_vector The vectors containing all the tensors to concatenate. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32.
+     *                          Dimensions of all the inputs should match apart for the width which can differ.
+     * @param[in] output        Output tensor. Data types supported: Same as @p input.
+     *                          Output tensor dimensions are the same with the inputs from the second dimension and above.
+     *                          The first dimension (width) is the sum of the input tensors' widths.
+     *
+     * @return a status
+     */
+    static Status validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output);
+
+    // Inherited methods overridden:
+    void run() override;
+
+private:
+    std::unique_ptr<NEWidthConcatenateLayerKernel[]> _concat_kernels_vector;
+    unsigned int                                     _num_inputs;
+};
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_NEWIDTHCONCATENATELAYER_H__ */
diff --git a/src/core/NEON/kernels/NEDepthConcatenateLayerKernel.cpp b/src/core/NEON/kernels/NEDepthConcatenateLayerKernel.cpp
index 38443ca4a8..1b937b5be8 100644
--- a/src/core/NEON/kernels/NEDepthConcatenateLayerKernel.cpp
+++ b/src/core/NEON/kernels/NEDepthConcatenateLayerKernel.cpp
@@ -28,37 +28,18 @@
 #include "arm_compute/core/IAccessWindow.h"
 #include "arm_compute/core/ITensor.h"
 #include "arm_compute/core/NEON/NEFixedPoint.h"
+#include "arm_compute/core/NEON/wrapper/wrapper.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Utils.h"
 #include "arm_compute/core/Validate.h"
 #include "arm_compute/core/Window.h"
 
-#include <arm_neon.h>
 #include <cstdint>
 
 using namespace arm_compute;
 
 namespace
 {
-// Overloads of 128-bit vector loads
-uint16x8_t loadq(const uint16_t *ptr)
-{
-    return vld1q_u16(ptr);
-}
-uint32x4_t loadq(const uint32_t *ptr)
-{
-    return vld1q_u32(ptr);
-}
-// Overloads of 128-bit vector stores
-void storeq(uint16_t *ptr, uint16x8_t val)
-{
-    return vst1q_u16(ptr, val);
-}
-void storeq(uint32_t *ptr, uint32x4_t val)
-{
-    return vst1q_u32(ptr, val);
-}
-
 template <typename T>
 void depth_concat(const ITensor *in, ITensor *out, std::pair<int, int> start_xy, int depth_offset, const Window &window)
 {
@@ -81,10 +62,54 @@ void depth_concat(const ITensor *in, ITensor *out, std::pair<int, int> start_xy,
         const auto in_ptr  = reinterpret_cast<const T *>(input_ptr + input.offset());
         const auto out_ptr = reinterpret_cast<T *>(output_ptr + output.offset());
 
-        storeq(out_ptr, loadq(in_ptr));
+        wrapper::vstore(out_ptr, wrapper::vloadq(in_ptr));
     },
     input, output);
 }
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, unsigned int depth_offset, ITensorInfo *output)
+{
+    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 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()));
+
+    Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+    return std::make_pair(err, win);
+}
+
+Status validate_arguments(const ITensorInfo *input, unsigned int depth_offset, const ITensorInfo *output)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+    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(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()
@@ -99,17 +124,8 @@ BorderSize NEDepthConcatenateLayerKernel::border_size() const
 
 void NEDepthConcatenateLayerKernel::configure(const ITensor *input, unsigned int depth_offset, ITensor *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(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);
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), depth_offset, output->info()));
 
     _func         = nullptr;
     _input        = input;
@@ -120,6 +136,9 @@ void NEDepthConcatenateLayerKernel::configure(const ITensor *input, unsigned int
 
     switch(input->info()->data_type())
     {
+        case DataType::QASYMM8:
+            _func = &depth_concat<uint8_t>;
+            break;
         case DataType::F16:
             _func = &depth_concat<uint16_t>;
             break;
@@ -130,20 +149,20 @@ void NEDepthConcatenateLayerKernel::configure(const ITensor *input, unsigned int
             ARM_COMPUTE_ERROR("Unsupported data type.");
     }
 
-    const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();
-    const unsigned int num_elems_read_per_iteration      = 16 / input->info()->element_size();
-    const unsigned int num_rows_read_per_iteration       = 1;
+    // 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));
 
-    // 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 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()));
+    INEKernel::configure(std::get<1>(win_config));
+}
 
-    INEKernel::configure(win);
+Status NEDepthConcatenateLayerKernel::validate(const arm_compute::ITensorInfo *input,
+                                               unsigned int                    depth_offset,
+                                               const arm_compute::ITensorInfo *output)
+{
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, depth_offset, output));
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), depth_offset, output->clone().get()).first);
+    return Status{};
 }
 
 void NEDepthConcatenateLayerKernel::run(const Window &window, const ThreadInfo &info)
diff --git a/src/core/NEON/kernels/NEWidthConcatenateLayerKernel.cpp b/src/core/NEON/kernels/NEWidthConcatenateLayerKernel.cpp
new file mode 100644
index 0000000000..1b38677991
--- /dev/null
+++ b/src/core/NEON/kernels/NEWidthConcatenateLayerKernel.cpp
@@ -0,0 +1,125 @@
+/*
+ * 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.
+ */
+#include "arm_compute/core/NEON/kernels/NEWidthConcatenateLayerKernel.h"
+
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/IAccessWindow.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/NEON/wrapper/wrapper.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+
+#include <cstdint>
+
+using namespace arm_compute;
+
+namespace
+{
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, unsigned int width_offset, ITensorInfo *output)
+{
+    const unsigned int num_elems_processed_per_iteration = 16 / output->element_size();
+
+    // The window needs to be based on input as we copy all the widths of input
+    Window                 win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
+    AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
+    AccessWindowHorizontal output_access(output, width_offset, num_elems_processed_per_iteration);
+    bool                   window_changed = update_window_and_padding(win, input_access, output_access);
+
+    Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+    return std::make_pair(err, win);
+}
+
+Status validate_arguments(const ITensorInfo *input, unsigned int width_offset, const ITensorInfo *output)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1,
+                                                         DataType::U8, DataType::S8, DataType::QASYMM8,
+                                                         DataType::U16, DataType::S16, DataType::F16,
+                                                         DataType::U32, DataType::F32);
+    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
+    ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(0) + width_offset > output->dimension(0));
+
+    for(size_t i = 1; i < Coordinates::num_max_dimensions; ++i)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(i) != output->dimension(i));
+    }
+    ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 3);
+
+    return Status{};
+}
+} // namespace
+
+NEWidthConcatenateLayerKernel::NEWidthConcatenateLayerKernel()
+    : _input(nullptr), _output(nullptr), _width_offset(0)
+{
+}
+
+void NEWidthConcatenateLayerKernel::configure(const ITensor *input, unsigned int width_offset, ITensor *output)
+{
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), width_offset, output->info()));
+
+    _input        = input;
+    _output       = output;
+    _width_offset = width_offset;
+
+    // Configure kernel window
+    auto win_config = validate_and_configure_window(input->info(), width_offset, output->info());
+    ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config));
+
+    INEKernel::configure(std::get<1>(win_config));
+}
+
+Status NEWidthConcatenateLayerKernel::validate(const ITensorInfo *input, unsigned int width_offset, const ITensorInfo *output)
+{
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, width_offset, output));
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), width_offset, output->clone().get()).first);
+    return Status{};
+}
+
+void NEWidthConcatenateLayerKernel::run(const Window &window, const ThreadInfo &info)
+{
+    ARM_COMPUTE_UNUSED(info);
+    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
+
+    // Offset output pointer to the correct position
+    uint8_t *output_ptr = _output->buffer() + _output->info()->offset_first_element_in_bytes() + _width_offset * _output->info()->strides_in_bytes()[0];
+
+    // Create iterators
+    Iterator input(_input, window);
+    Iterator output(_output, window);
+
+    execute_window_loop(window, [&](const Coordinates & id)
+    {
+        const auto in_ptr  = input.ptr();
+        const auto out_ptr = output_ptr + output.offset();
+
+        wrapper::vstore(out_ptr, wrapper::vloadq(in_ptr));
+    },
+    input, output);
+}
diff --git a/src/runtime/CL/functions/CLConcatenateLayer.cpp b/src/runtime/CL/functions/CLConcatenateLayer.cpp
index f4bc1ff4ac..018c674c83 100644
--- a/src/runtime/CL/functions/CLConcatenateLayer.cpp
+++ b/src/runtime/CL/functions/CLConcatenateLayer.cpp
@@ -39,7 +39,7 @@ CLConcatenateLayer::CLConcatenateLayer()
 {
 }
 
-void CLConcatenateLayer::configure(std::vector<ICLTensor *> inputs_vector, ICLTensor *output, DataLayoutDimension axis)
+void CLConcatenateLayer::configure(const std::vector<ICLTensor *> &inputs_vector, ICLTensor *output, DataLayoutDimension axis)
 {
     ARM_COMPUTE_ERROR_ON(output == nullptr);
 
@@ -48,14 +48,14 @@ void CLConcatenateLayer::configure(std::vector<ICLTensor *> inputs_vector, ICLTe
         case 0:
         {
             auto func = support::cpp14::make_unique<CLWidthConcatenateLayer>();
-            func->configure(std::move(inputs_vector), output);
+            func->configure(inputs_vector, output);
             _concat_function = std::move(func);
             break;
         }
         case 2:
         {
             auto func = support::cpp14::make_unique<CLDepthConcatenateLayer>();
-            func->configure(std::move(inputs_vector), output);
+            func->configure(inputs_vector, output);
             _concat_function = std::move(func);
             break;
         }
diff --git a/src/runtime/CL/functions/CLDepthConcatenateLayer.cpp b/src/runtime/CL/functions/CLDepthConcatenateLayer.cpp
index 174be94410..b5e8fd96d0 100644
--- a/src/runtime/CL/functions/CLDepthConcatenateLayer.cpp
+++ b/src/runtime/CL/functions/CLDepthConcatenateLayer.cpp
@@ -43,7 +43,7 @@ CLDepthConcatenateLayer::CLDepthConcatenateLayer() // NOLINT
 {
 }
 
-void CLDepthConcatenateLayer::configure(std::vector<ICLTensor *> inputs_vector, ICLTensor *output) // NOLINT
+void CLDepthConcatenateLayer::configure(const std::vector<ICLTensor *> &inputs_vector, ICLTensor *output) // NOLINT
 {
     _num_inputs = inputs_vector.size();
 
diff --git a/src/runtime/NEON/functions/NEConcatenateLayer.cpp b/src/runtime/NEON/functions/NEConcatenateLayer.cpp
new file mode 100644
index 0000000000..21ab47d3fe
--- /dev/null
+++ b/src/runtime/NEON/functions/NEConcatenateLayer.cpp
@@ -0,0 +1,90 @@
+/*
+ * 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.
+ */
+#include "arm_compute/runtime/NEON/functions/NEConcatenateLayer.h"
+
+#include "arm_compute/runtime/NEON/functions/NEDepthConcatenateLayer.h"
+#include "arm_compute/runtime/NEON/functions/NEWidthConcatenateLayer.h"
+
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "support/ToolchainSupport.h"
+
+namespace arm_compute
+{
+NEConcatenateLayer::NEConcatenateLayer()
+    : _concat_function(nullptr)
+{
+}
+
+void NEConcatenateLayer::configure(const std::vector<ITensor *> &inputs_vector, ITensor *output, DataLayoutDimension axis)
+{
+    ARM_COMPUTE_ERROR_ON(output == nullptr);
+
+    switch(get_data_layout_dimension_index(output->info()->data_layout(), axis))
+    {
+        case 0:
+        {
+            auto func = support::cpp14::make_unique<NEWidthConcatenateLayer>();
+            func->configure(inputs_vector, output);
+            _concat_function = std::move(func);
+            break;
+        }
+        case 2:
+        {
+            auto func = support::cpp14::make_unique<NEDepthConcatenateLayer>();
+            func->configure(inputs_vector, output);
+            _concat_function = std::move(func);
+            break;
+        }
+        default:
+            ARM_COMPUTE_ERROR("Concatenation is supported across width and depth only!");
+    }
+}
+
+Status NEConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, DataLayoutDimension axis)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON(output == nullptr);
+
+    switch(get_data_layout_dimension_index(output->data_layout(), axis))
+    {
+        case 0:
+            ARM_COMPUTE_RETURN_ON_ERROR(NEWidthConcatenateLayer::validate(inputs_vector, output));
+            break;
+        case 2:
+            ARM_COMPUTE_RETURN_ON_ERROR(NEDepthConcatenateLayer::validate(inputs_vector, output));
+            break;
+        default:
+            ARM_COMPUTE_RETURN_ERROR_MSG("Concatenation is supported across width and depth only!");
+    }
+    return Status{};
+}
+
+void NEConcatenateLayer::run()
+{
+    ARM_COMPUTE_ERROR_ON(_concat_function == nullptr);
+    _concat_function->run();
+}
+} // namespace arm_compute
diff --git a/src/runtime/NEON/functions/NEDepthConcatenateLayer.cpp b/src/runtime/NEON/functions/NEDepthConcatenateLayer.cpp
index cb0157664b..49db855f21 100644
--- a/src/runtime/NEON/functions/NEDepthConcatenateLayer.cpp
+++ b/src/runtime/NEON/functions/NEDepthConcatenateLayer.cpp
@@ -27,6 +27,7 @@
 #include "arm_compute/core/Helpers.h"
 #include "arm_compute/core/ITensor.h"
 #include "arm_compute/core/PixelValue.h"
+#include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Types.h"
 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
 #include "arm_compute/runtime/NEON/NEScheduler.h"
@@ -42,10 +43,8 @@ NEDepthConcatenateLayer::NEDepthConcatenateLayer() // NOLINT
 {
 }
 
-void NEDepthConcatenateLayer::configure(std::vector<ITensor *> inputs_vector, ITensor *output) // NOLINT
+void NEDepthConcatenateLayer::configure(const std::vector<ITensor *> &inputs_vector, ITensor *output) // NOLINT
 {
-    ARM_COMPUTE_ERROR_ON(inputs_vector.size() < 2);
-
     _num_inputs             = inputs_vector.size();
     _concat_kernels_vector  = arm_compute::support::cpp14::make_unique<NEDepthConcatenateLayerKernel[]>(_num_inputs);
     _border_handlers_vector = arm_compute::support::cpp14::make_unique<NEFillBorderKernel[]>(_num_inputs);
@@ -59,6 +58,7 @@ void NEDepthConcatenateLayer::configure(std::vector<ITensor *> inputs_vector, IT
 
     // Output auto inizialitation if not yet initialized
     auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
+    ARM_COMPUTE_ERROR_THROW_ON(NEDepthConcatenateLayer::validate(inputs_vector_info, output->info()));
 
     unsigned int depth_offset = 0;
     for(unsigned int i = 0; i < _num_inputs; ++i)
@@ -73,6 +73,27 @@ void NEDepthConcatenateLayer::configure(std::vector<ITensor *> inputs_vector, IT
     output->info()->set_valid_region(ValidRegion(Coordinates(), output_shape));
 }
 
+Status NEDepthConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output)
+{
+    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    = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector);
+    auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
+
+    unsigned int depth_offset = 0;
+    for(const auto &input : inputs_vector)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
+        ARM_COMPUTE_RETURN_ON_ERROR(NEDepthConcatenateLayerKernel::validate(input, depth_offset, &tmp_output_info));
+        depth_offset += input->dimension(2);
+    }
+
+    return Status{};
+}
+
 void NEDepthConcatenateLayer::run()
 {
     for(unsigned i = 0; i < _num_inputs; ++i)
diff --git a/src/runtime/NEON/functions/NEWidthConcatenateLayer.cpp b/src/runtime/NEON/functions/NEWidthConcatenateLayer.cpp
new file mode 100644
index 0000000000..097605c062
--- /dev/null
+++ b/src/runtime/NEON/functions/NEWidthConcatenateLayer.cpp
@@ -0,0 +1,96 @@
+/*
+ * 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.
+ */
+#include "arm_compute/runtime/NEON/functions/NEWidthConcatenateLayer.h"
+
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/runtime/NEON/NEScheduler.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "support/ToolchainSupport.h"
+
+using namespace arm_compute;
+
+NEWidthConcatenateLayer::NEWidthConcatenateLayer()
+    : _concat_kernels_vector(),
+      _num_inputs(0)
+{
+}
+
+Status NEWidthConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output)
+{
+    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    = arm_compute::misc::shape_calculator::calculate_width_concatenate_shape(inputs_vector);
+    auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
+
+    unsigned int width_offset = 0;
+    for(const auto &input : inputs_vector)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
+        ARM_COMPUTE_RETURN_ON_ERROR(NEWidthConcatenateLayerKernel::validate(input, width_offset, &tmp_output_info));
+        width_offset += input->dimension(0);
+    }
+
+    return Status{};
+}
+
+void NEWidthConcatenateLayer::configure(std::vector<ITensor *> inputs_vector, ITensor *output)
+{
+    _num_inputs = inputs_vector.size();
+
+    std::vector<ITensorInfo *> inputs_vector_info;
+    for(unsigned int i = 0; i < _num_inputs; i++)
+    {
+        inputs_vector_info.emplace_back(inputs_vector.at(i)->info());
+    }
+    TensorShape output_shape = arm_compute::misc::shape_calculator::calculate_width_concatenate_shape(inputs_vector);
+
+    // Output auto inizialitation if not yet initialized
+    auto_init_if_empty(*output->info(), output_shape, 1, inputs_vector[0]->info()->data_type());
+    ARM_COMPUTE_ERROR_THROW_ON(NEWidthConcatenateLayer::validate(inputs_vector_info, output->info()));
+
+    unsigned int width_offset = 0;
+
+    _concat_kernels_vector = arm_compute::support::cpp14::make_unique<NEWidthConcatenateLayerKernel[]>(_num_inputs);
+
+    for(unsigned int i = 0; i < _num_inputs; i++)
+    {
+        _concat_kernels_vector[i].configure(inputs_vector.at(i), width_offset, output);
+        width_offset += inputs_vector.at(i)->info()->dimension(0);
+    }
+}
+
+void NEWidthConcatenateLayer::run()
+{
+    for(unsigned i = 0; i < _num_inputs; i++)
+    {
+        NEScheduler::get().schedule(_concat_kernels_vector.get() + i, Window::DimY);
+    }
+}
diff --git a/tests/validation/NEON/DepthConcatenateLayer.cpp b/tests/validation/NEON/DepthConcatenateLayer.cpp
index 0e0b674e41..24e7649e7d 100644
--- a/tests/validation/NEON/DepthConcatenateLayer.cpp
+++ b/tests/validation/NEON/DepthConcatenateLayer.cpp
@@ -42,6 +42,44 @@ namespace validation
 TEST_SUITE(NEON)
 TEST_SUITE(DepthConcatenateLayer)
 
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+        framework::dataset::make("InputInfo1", {  TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32), // Mismatching data type input/output
+                                                  TensorInfo(TensorShape(24U, 27U, 4U), 1, DataType::F32), // Mismatching x dimension
+                                                  TensorInfo(TensorShape(23U, 27U, 3U), 1, DataType::F32), // Mismatching total depth
+                                                  TensorInfo(TensorShape(16U, 27U, 6U), 1, DataType::F32)
+        }),
+        framework::dataset::make("InputInfo2", {  TensorInfo(TensorShape(23U, 27U, 4U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(23U, 27U, 4U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(16U, 27U, 6U), 1, DataType::F32)
+        })),
+                                                              framework::dataset::make("OutputInfo", {  TensorInfo(TensorShape(23U, 27U, 9U), 1, DataType::F16),
+                                                                                                        TensorInfo(TensorShape(25U, 12U, 9U), 1, DataType::F32),
+                                                                                                        TensorInfo(TensorShape(23U, 27U, 8U), 1, DataType::F32),
+                                                                                                        TensorInfo(TensorShape(16U, 27U, 12U), 1, DataType::F32)
+                                                              })),
+                                                          framework::dataset::make("Expected", { false, false, false, true })),
+               input_info1, input_info2, output_info,expected)
+{
+    std::vector<TensorInfo> inputs_vector_info;
+    inputs_vector_info.emplace_back(std::move(input_info1));
+    inputs_vector_info.emplace_back(std::move(input_info2));
+
+    std::vector<ITensorInfo *> inputs_vector_info_raw;
+    for(auto &input : inputs_vector_info)
+    {
+        inputs_vector_info_raw.emplace_back(&input);
+    }
+
+    bool is_valid = bool(NEDepthConcatenateLayer::validate(inputs_vector_info_raw,
+                                                           &output_info.clone()->set_is_resizable(false)));
+    ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
 TEST_CASE(Configuration, framework::DatasetMode::ALL)
 {
     // Create tensors
@@ -100,6 +138,23 @@ FIXTURE_DATA_TEST_CASE(RunLarge, NEDepthConcatenateLayerFixture<float>, framewor
 TEST_SUITE_END()
 TEST_SUITE_END()
 
+TEST_SUITE(Quantized)
+TEST_SUITE(QASYMM8)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEDepthConcatenateLayerFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::Small2DShapes(), framework::dataset::make("DataType",
+                                                                                                                     DataType::QASYMM8)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NEDepthConcatenateLayerFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(datasets::DepthConcatenateLayerShapes(), framework::dataset::make("DataType",
+                                                                                                                   DataType::QASYMM8)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+
 TEST_SUITE_END()
 TEST_SUITE_END()
 } // namespace validation
diff --git a/tests/validation/NEON/WidthConcatenateLayer.cpp b/tests/validation/NEON/WidthConcatenateLayer.cpp
new file mode 100644
index 0000000000..6f3abe1494
--- /dev/null
+++ b/tests/validation/NEON/WidthConcatenateLayer.cpp
@@ -0,0 +1,142 @@
+/*
+ * 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.
+ */
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/NEON/functions/NEWidthConcatenateLayer.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+#include "tests/NEON/Accessor.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/WidthConcatenateLayerFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+TEST_SUITE(NEON)
+TEST_SUITE(WidthConcatenateLayer)
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+        framework::dataset::make("InputInfo1", {  TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32), // Mismatching data type input/output
+                                                  TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32), // Mismatching y dimension
+                                                  TensorInfo(TensorShape(23U, 27U, 5U), 1, DataType::F32), // Mismatching total width
+                                                  TensorInfo(TensorShape(16U, 27U, 5U), 1, DataType::F32)
+        }),
+        framework::dataset::make("InputInfo2", {  TensorInfo(TensorShape(24U, 27U, 4U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(52U, 27U, 5U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(52U, 27U, 5U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(16U, 27U, 5U), 1, DataType::F32)
+        })),
+        framework::dataset::make("OutputInfo", {  TensorInfo(TensorShape(47U, 27U, 5U), 1, DataType::F16),
+                                                  TensorInfo(TensorShape(75U, 12U, 5U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(11U, 27U, 5U), 1, DataType::F32),
+                                                  TensorInfo(TensorShape(32U, 27U, 5U), 1, DataType::F32)
+        })),
+        framework::dataset::make("Expected", { false, false, false, true })),
+        input_info1, input_info2, output_info,expected)
+{
+    std::vector<TensorInfo> inputs_vector_info;
+    inputs_vector_info.emplace_back(std::move(input_info1));
+    inputs_vector_info.emplace_back(std::move(input_info2));
+
+    std::vector<ITensorInfo *> inputs_vector_info_raw;
+    for(auto &input : inputs_vector_info)
+    {
+        inputs_vector_info_raw.emplace_back(&input);
+    }
+
+    bool is_valid = bool(NEWidthConcatenateLayer::validate(inputs_vector_info_raw,
+                                                           &output_info.clone()->set_is_resizable(false)));
+    ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+TEST_CASE(Configuration, framework::DatasetMode::ALL)
+{
+    // Create tensors
+    Tensor src1 = create_tensor<Tensor>(TensorShape(128U, 32U, 32U), DataType::F32, 1);
+    Tensor src2 = create_tensor<Tensor>(TensorShape(32U, 32U, 32U), DataType::F32, 1);
+    Tensor src3 = create_tensor<Tensor>(TensorShape(15U, 32U, 32U), DataType::F32, 1);
+    Tensor dst;
+
+    ARM_COMPUTE_EXPECT(src1.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(src2.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(src3.info()->is_resizable(), framework::LogLevel::ERRORS);
+    ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+    // Create and configure function
+    NEWidthConcatenateLayer concat_layer;
+
+    concat_layer.configure({ &src1, &src2, &src3 }, &dst);
+}
+
+template <typename T>
+using NEWidthConcatenateLayerFixture = WidthConcatenateLayerValidationFixture<Tensor, ITensor, Accessor, NEWidthConcatenateLayer, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEWidthConcatenateLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::Small2DShapes(), framework::dataset::make("DataType",
+                                                                                                                   DataType::F32)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NEWidthConcatenateLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::WidthConcatenateLayerShapes(), framework::dataset::make("DataType",
+                                                                                                                 DataType::F32)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+
+TEST_SUITE(Quantized)
+TEST_SUITE(QASYMM8)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEWidthConcatenateLayerFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(datasets::Small2DShapes(), framework::dataset::make("DataType",
+                                                                                                                     DataType::QASYMM8)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, NEWidthConcatenateLayerFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(datasets::WidthConcatenateLayerShapes(), framework::dataset::make("DataType",
+                                                                                                                   DataType::QASYMM8)))
+{
+    // Validate output
+    validate(Accessor(_target), _reference);
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+
+TEST_SUITE_END()
+TEST_SUITE_END()
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
diff --git a/tests/validation/reference/DepthConcatenateLayer.cpp b/tests/validation/reference/DepthConcatenateLayer.cpp
index dbcd575e9a..90fbd915b1 100644
--- a/tests/validation/reference/DepthConcatenateLayer.cpp
+++ b/tests/validation/reference/DepthConcatenateLayer.cpp
@@ -92,6 +92,7 @@ SimpleTensor<T> depthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs)
     return dst;
 }
 
+template SimpleTensor<uint8_t> depthconcatenate_layer(const std::vector<SimpleTensor<uint8_t>> &srcs);
 template SimpleTensor<float> depthconcatenate_layer(const std::vector<SimpleTensor<float>> &srcs);
 template SimpleTensor<half> depthconcatenate_layer(const std::vector<SimpleTensor<half>> &srcs);
 } // namespace reference
diff --git a/tests/validation/reference/WidthConcatenateLayer.cpp b/tests/validation/reference/WidthConcatenateLayer.cpp
index 7a5ece8f5e..8662199306 100644
--- a/tests/validation/reference/WidthConcatenateLayer.cpp
+++ b/tests/validation/reference/WidthConcatenateLayer.cpp
@@ -84,6 +84,7 @@ SimpleTensor<T> widthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs)
 
 template SimpleTensor<float> widthconcatenate_layer(const std::vector<SimpleTensor<float>> &srcs);
 template SimpleTensor<half> widthconcatenate_layer(const std::vector<SimpleTensor<half>> &srcs);
+template SimpleTensor<uint8_t> widthconcatenate_layer(const std::vector<SimpleTensor<uint8_t>> &srcs);
 } // namespace reference
 } // namespace validation
 } // namespace test