text: /*
   * Copyright (c) 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_CPU_FULLY_CONNECTED_H
  #define ARM_COMPUTE_CPU_FULLY_CONNECTED_H
  
  #include "src/cpu/ICpuOperator.h"
  
  #include "arm_compute/core/TensorInfo.h"
  
  #include <memory>
  
  namespace arm_compute
  {
  namespace cpu
  {
  // Forward declarations
  class CpuConvertFullyConnectedWeights;
  class CpuFlatten;
  class CpuGemm;
  class CpuGemmLowpMatrixMultiplyCore;
  namespace kernels
  {
  class CpuTransposeKernel;
  } // namespace kernels
  /** Basic function to compute a Fully Connected layer. This function calls the following kernels:
   *  -# @ref kernels::CpuIm2ColKernel (called when the input comes from a convolutional layer)
   *  -# @ref kernels::CpuTransposeKernel (if @p are_weights_reshaped is set to false and transpose_weights is set to true ) (called once)
   *  -# @ref CpuGemm or @ref CpuGemmLowpMatrixMultiplyCore (if quantized asymmetric)
   *  -# @ref kernels::CpuGemmMatrixAdditionKernel or @ref CpuGemmLowpOutputStage (if quantized asymmetric) (if @p biases is not equal to nullptr)
   *
   * @note  The fully connected layer accepts "weights" tensors only with 2 dimensions.
   */
  class CpuFullyConnected : public ICpuOperator
  {
  public:
      /** Constructor */
      CpuFullyConnected();
      /** Destructor */
      ~CpuFullyConnected();
      /** Set the input and output tensors.
       *
       * Valid data layouts:
       * - NHWC
       * - NCHW
       *
       * Valid data type configurations:
       * |src0           |src1               |src2   |dst            |
       * |:--------------|:------------------|:------|:--------------|
       * |F16            |F16                |F16    |F16            |
       * |F32            |F32                |F32    |F32            |
       * |QASYMM8        |QASYMM8            |S32    |QASYMM8        |
       * |QASYMM8_SIGNED |QASYMM8_SIGNED     |S32    |QASYMM8_SIGNED |
       *
       * @param[in]  src     Source tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
       * @param[in]  weights Weights tensor info. The weights must be 2 dimensional.
       *                     If this function is called after a Convolution Layer, the (transposed) weights will have as many rows as the product of the first 3 input's dimensions.
       *                     If it is called after another FullyConnected Layer, the (transposed) weights will have as many rows as the input's first dimension.
       *                     Data type supported: Same as @p src.
       * @param[in]  biases  Bias tensor info. Can be nullptr. Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED.
       * @param[out] dst     Destination tensor info. Its shape should be equal to the output of a matrix multiplication between:
       *                     - The output of im2col on the input and the (transposed) 2D weights, if the function is called after a Convolution Layer
       *                     - The input tensor and the (transposed) 2D weights, if the function is called after another FullyConnected Layer.
       *                     Data type supported: Same as @p src.
       * @param[in]  fc_info (Optional) Fully connected layer additional info
       */
      void configure(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *dst,
                     FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo());
      /** Static function to check if given info will lead to a valid configuration of @ref CpuFullyConnected
       *
       * Similar to @ref CpuFullyConnected
       *
       * @return a status
       */
      static Status validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst,
                             FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo());
  
      //Inherited methods override
      void run(ITensorPack &tensors) override;
      void prepare(ITensorPack &tensors) override;
      experimental::MemoryRequirements workspace() const override;
  
  private:
      void configure_fc_fc(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *dst, const ActivationLayerInfo &act);
      void configure_conv_fc(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *dst, const ActivationLayerInfo &act);
      void configure_mm(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *dst, const ActivationLayerInfo &act);
  
      enum AuxTensorIdx
      {
          AsmGemmWorkspace = 0,
          Pretranspose,
          GemmTemp1, // Both CpuGemm and CpuGemmLowpMatrixMultiplyCore
          GemmTemp2, // Both CpuGemm and CpuGemmLowpMatrixMultiplyCore
          GemmTemp3, // Both CpuGemm and CpuGemmLowpMatrixMultiplyCore
          GemmTemp4, // CpuGemmLowpMatrixMultiplyCore only
          GemmTemp5, // CpuGemmLowpMatrixMultiplyCore only
          GemmTemp6, // CpuGemmLowpMatrixMultiplyCore only
          GemmTemp7, // CpuGemmLowpMatrixMultiplyCore only
          TransposedWeights,
          ConvertedWeights,
          FlattenedSrc,
          Count
      };
  
      std::unique_ptr<CpuFlatten>                      _flatten;
      std::unique_ptr<CpuConvertFullyConnectedWeights> _convert_weights;
      std::unique_ptr<kernels::CpuTransposeKernel>     _transpose_weights;
      std::unique_ptr<CpuGemm>                         _mm_gemm;
      std::unique_ptr<CpuGemmLowpMatrixMultiplyCore>   _mm_gemmlowp;
  
      TensorInfo   _flattened_src;
      TensorInfo   _converted_weights;
      TensorInfo   _reshaped_weights;
      TensorInfo   _trans_weights;
      AuxTensorIdx _trans_weights_idx;
  
      experimental::MemoryRequirements _aux_mem;
  
      bool _needs_weights_conversion;
      bool _needs_weights_reshape;
      bool _is_fc_after_conv;
      bool _is_quantized_asymmetric;
      bool _is_prepared;
      bool _enable_fast_math;
  };
  } // namespace cpu
  } // namespace arm_compute
  #endif /* ARM_COMPUTE_CPU_FULLY_CONNECTED_H */
  