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diff --git a/runtimes/libs/ARMComputeEx/arm_compute/runtime/NEON/functions/NETransposeConvLayer.h b/runtimes/libs/ARMComputeEx/arm_compute/runtime/NEON/functions/NETransposeConvLayer.h
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+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ * 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_NETRANSPOSECONVLAYER_H__
+#define __ARM_COMPUTE_NETRANSPOSECONVLAYER_H__
+
+#include "arm_compute/runtime/CPP/functions/CPPUpsampleEx.h"
+#include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h"
+#include "arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h"
+#include "arm_compute/runtime/NEON/functions/NEPermute.h"
+
+#include "arm_compute/core/CPP/kernels/CPPFlipWeightsKernel.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/IFunction.h"
+#include "arm_compute/runtime/IMemoryManager.h"
+#include "arm_compute/runtime/MemoryGroup.h"
+#include "arm_compute/runtime/Tensor.h"
+
+#include <memory>
+
+namespace arm_compute
+{
+/** Function to run the deconvolution layer.
+ *
+ * Transpose convolution Layer is the backward pass of Convolution Layer. First we transform the
+ * input depending on the stride and pad info and then perfrom a 1x1
+ * convolution pass. Input stride defines how many zeroes we should put between each element of the
+ * input, pad is the amount of padding and finaly a is a user
+ * specified value where a < stride - 1 that increases the padding top and right of the input image.
+ *
+ *  The relation between input to output is as follows:
+ *  \f[
+ *       width\_output = (width\_input - 1) \cdot stride\_x - 2 \cdot padding\_x + kernel\_x
+ *  \f]
+ *  \f[
+ *       height\_output = (height\_input - 1) \cdot stride\_y - 2 \cdot padding\_y + kernel\_y
+ *  \f]
+ *
+ *  where
+ *      width is the size of the first input dimension.
+ *      height is the size of the second input dimension.
+ *      width_output is the size of the first output dimension.
+ *      height_output is the size of the second output dimension.
+ *      kernel_x and kernel_y are the convolution sizes in x and y.
+ *      stride_x and stride_y is the input stride of the first and second dimension.
+ *
+ * The weights used by Transpose convolution are supposed to be the same as the ones used for
+ * Convolution. Therefore, it will be necessary to use the weights in the
+ * reverse order to perform an actual convolution. This is achieved by using the @ref
+ * CPPFlipWeightsKernel.
+ *
+ * This function calls the following NEON kernels/functions:
+ *
+ * -# @ref CPPUpsample
+ * -# @ref NEConvolutionLayer
+ *
+ */
+class NETransposeConvLayer : public IFunction
+{
+public:
+  /** Default constructor */
+  NETransposeConvLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+
+  /** Prevent instances of this class from being copied (As this class contains pointers) */
+  NETransposeConvLayer(const NETransposeConvLayer &) = delete;
+  /** Prevent instances of this class from being copied (As this class contains pointers) */
+  NETransposeConvLayer &operator=(const NETransposeConvLayer &) = delete;
+  /** Allow instances of this class to be moved */
+  NETransposeConvLayer(NETransposeConvLayer &&) = default;
+  /** Allow instances of this class to be moved */
+  NETransposeConvLayer &operator=(NETransposeConvLayer &&) = default;
+  /** Default destructor */
+  virtual ~NETransposeConvLayer() = default;
+
+  /** Set the input, weights, biases and output tensors.
+   *
+   * @param[in,out] input   Input tensor. 3 lower dimensions represent a single input, and an
+   * optional 4th dimension for batch of inputs. Data types supported: F32/F16/QASYMM8.
+   * @param[in]     weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type
+   * supported: Same as @p input.
+   * @param[in]     bias    Optional, ignored if NULL. The biases have one dimension. Data type
+   * supported: Data types supported: S32 for QASYMM8 input, F32 for F32 input, F16 for F16 input.
+   * @param[out]    output  Output tensor. The output has the same number of dimensions as the @p
+   * input.
+   * @param[in]     info    Contains padding and policies to be used in the deconvolution, this is
+   * decribed in @ref PadStrideInfo.
+   * @param[in]     invalid_right  The number of zeros added to right edge of the output.
+   * @param[in]     invalid_bottom The number of zeros added to top edge of the output.
+   *
+   */
+  void configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output,
+                 const PadStrideInfo &info, unsigned int invalid_right,
+                 unsigned int invalid_bottom);
+  /** Static function to check if given info will lead to a valid configuration of @ref
+   * NETransposeConvLayer
+   *
+   * @param[in] input   Input tensor info. 3 lower dimensions represent a single input, and an
+   * optional 4th dimension for batch of inputs. Data types supported: F32/F16/QASYMM8.
+   * @param[in] weights The 4d weights info with dimensions [width, height, IFM, OFM]. Data type
+   * supported: Same as @p input.
+   * @param[in] bias    (Optional) The biases have one dimension. Data type supported: Data types
+   * supported: S32 for QASYMM8 input, F32 for F32 input, F16 for F16 input.
+   * @param[in] output  Output tensor info. The output has the same number of dimensions as the @p
+   * input.
+   * @param[in] info    Contains padding and policies to be used in the deconvolution, this is
+   * decribed in @ref PadStrideInfo.
+   * @param[in] innvalid_right  The number of zeros added to right edge of the output.
+   * @param[in] invalid_bottom  The number of zeros added to top edge of the output.
+   *
+   * @return a status
+   */
+  static Status validate(const ITensorInfo *input, const ITensorInfo *weights,
+                         const ITensorInfo *bias, const ITensorInfo *output,
+                         const PadStrideInfo &info, unsigned int invalid_right,
+                         unsigned int invalid_bottom);
+
+  // Inherited methods overridden:
+  void run() override;
+  void prepare() override;
+
+private:
+  MemoryGroup _memory_group;
+  NEConvolutionLayer _conv_f;
+  CPPUpsampleEx _upsample_f;
+  CPPFlipWeightsKernel _flip_weights;
+  NEPermute _permute_input;
+  NEPermute _permute_weights;
+  NEPermute _permute_output;
+  Tensor _scaled_output;
+  Tensor _weights_flipped;
+  Tensor _permuted_input;
+  Tensor _permuted_weights;
+  Tensor _permuted_output;
+  bool _is_nchw;
+  const ITensor *_original_weights;
+  ITensor *_input;
+  PadStrideInfo _info;
+  bool _is_prepared;
+};
+} // arm_compute
+#endif /* __ARM_COMPUTE_NETRANSPOSECONVLAYER_H__ */