text: /*
   * Copyright (c) 2018-2021 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_H
  #define ARM_COMPUTE_NERNNLAYER_H
  
  #include "arm_compute/core/Types.h"
  #include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
  #include "arm_compute/runtime/NEON/functions/NEArithmeticAddition.h"
  #include "arm_compute/runtime/NEON/functions/NECopy.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 NERNNLayer */
  class NERNNLayer : public IFunction
  {
  public:
      /** Default constructor */
      NERNNLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      NERNNLayer(const NERNNLayer &) = delete;
      /** Prevent instances of this class from being moved (As this class contains pointers) */
      NERNNLayer(NERNNLayer &&) = delete;
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      NERNNLayer &operator=(const NERNNLayer &) = delete;
      /** Prevent instances of this class from being moved (As this class contains pointers) */
      NERNNLayer &operator=(NERNNLayer &&) = delete;
      /** Default destructor */
      ~NERNNLayer();
      /** 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;
      NEArithmeticAddition  _add_f;
      NEActivationLayer     _activation;
      NEFullyConnectedLayer _fully_connected;
      NECopy                _copy_f;
      Tensor                _fully_connected_out;
      Tensor                _gemm_output;
      Tensor                _add_output;
      bool                  _is_prepared;
  };
  } // namespace arm_compute
  #endif /* ARM_COMPUTE_NERNNLAYER_H */
  