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diff --git a/runtimes/libs/ARMComputeEx/arm_compute/runtime/NEON/functions/NERNNLayerEx.h b/runtimes/libs/ARMComputeEx/arm_compute/runtime/NEON/functions/NERNNLayerEx.h
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+++ b/runtimes/libs/ARMComputeEx/arm_compute/runtime/NEON/functions/NERNNLayerEx.h
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+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ * 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_NERNNLAYER_EX_H__
+#define __ARM_COMPUTE_NERNNLAYER_EX_H__
+
+#include "arm_compute/core/NEON/kernels/NEActivationLayerKernel.h"
+#include "arm_compute/core/NEON/kernels/NEArithmeticAdditionKernel.h"
+#include "arm_compute/core/NEON/kernels/NECopyKernel.h"
+
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h"
+#include "arm_compute/runtime/NEON/functions/NEGEMM.h"
+
+namespace arm_compute
+{
+// Forward declarations
+class ITensor;
+
+/** Basic function to run @ref NERNNLayerEx */
+class NERNNLayerEx : public IFunction
+{
+public:
+  /** Default constructor */
+  NERNNLayerEx(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+  /** Prevent instances of this class from being copied (As this class contains pointers) */
+  NERNNLayerEx(const NERNNLayerEx &) = delete;
+  /** Default move constructor */
+  NERNNLayerEx(NERNNLayerEx &&) = default;
+  /** Prevent instances of this class from being copied (As this class contains pointers) */
+  NERNNLayerEx &operator=(const NERNNLayerEx &) = delete;
+  /** Default move assignment operator */
+  NERNNLayerEx &operator=(NERNNLayerEx &&) = default;
+  /** Initialize the function
+   *
+   * @param[in]     input             Input is a 2-D tensor of shape [input_size, batch_size]. Data
+   * types supported: F16/F32
+   * @param[in]     weights           Weights tensor of shape [input_size, num_units] that
+   * multiplies the input. Data types supported: Same as @p input
+   * @param[in]     recurrent_weights Weights tensor of shape [num_units, num_units] that multiplies
+   * the current 'state'. Data types supported: Same as @p input
+   * @param[in]     bias              Bias vector of shape [num_units]. Data types supported: Same
+   * as @p input
+   * @param[out]    output            Output tensor of shape [num_units, batch_size]. Data types
+   * supported: Same as @p input
+   * @param[in,out] hidden_state      Output tensor of shape [num_units, batch_size]. Data types
+   * supported: Same as @p input
+   * @param[in]     info              Activation layer parameter.
+   */
+  void configure(const ITensor *input, const ITensor *weights, const ITensor *recurrent_weights,
+                 const ITensor *bias, ITensor *hidden_state, ITensor *output,
+                 ActivationLayerInfo &info);
+  /** Initialize the function
+   *
+   * @param[in] input             Input is a 2-D tensor of shape [input_size, batch_size]. Data
+   * types supported: F16/F32
+   * @param[in] weights           Weights tensor of shape [input_size, num_units] that multiplies
+   * the input. Data types supported: Same as @p input
+   * @param[in] recurrent_weights Weights tensor of shape [num_units, num_units] that multiplies the
+   * current 'state'. Data types supported: Same as @p input
+   * @param[in] bias              Bias vector of shape [num_units]. Data types supported: Same as @p
+   * input
+   * @param[in] output            Output tensor of shape [num_units, batch_size]. Data types
+   * supported: Same as @p input
+   * @param[in] hidden_state      Output tensor of shape [num_units, batch_size]. Data types
+   * supported: Same as @p input
+   * @param[in] info              Activation layer parameter.
+   *
+   * @return a status
+   */
+  static Status validate(const ITensorInfo *input, const ITensorInfo *weights,
+                         const ITensorInfo *recurrent_weights, const ITensorInfo *bias,
+                         const ITensorInfo *hidden_state, const ITensorInfo *output,
+                         const ActivationLayerInfo &info);
+
+  // Inherited methods overridden:
+  void run() override;
+  void prepare() override;
+
+private:
+  MemoryGroup _memory_group;
+  NEGEMM _gemm_state_f;
+  NEArithmeticAdditionKernel _add_kernel;
+  NEActivationLayerKernel _activation_kernel;
+  NEFullyConnectedLayer _fully_connected_kernel;
+  NECopyKernel _copy_kernel;
+  Tensor _fully_connected_out;
+  Tensor _gemm_output;
+  Tensor _add_output;
+  bool _is_prepared;
+};
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_NERNNLAYER_EX_H__ */