text: /****************************************************************************
  *
  *    Copyright (c) 2020 Vivante Corporation
  *
  *    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 <string.h>
  
  #include "vsi_nn_types.h"
  #include "vsi_nn_platform.h"
  #include "vsi_nn_log.h"
  #include "vsi_nn_graph.h"
  #include "vsi_nn_node.h"
  #include "vsi_nn_prv.h"
  #include "utils/vsi_nn_math.h"
  #include "vsi_nn_ops.h"
  #include "vsi_nn_tensor.h"
  #include "vsi_nn_tensor_util.h"
  #include "client/vsi_nn_vxkernel.h"
  #include "utils/vsi_nn_util.h"
  
  #define _ARG_NUM            (2)
  #define _INPUT_NUM          (3)
  #define _OUTPUT_NUM         (1)
  #define _IO_NUM             (_INPUT_NUM + _OUTPUT_NUM)
  #define _PARAM_NUM          (_ARG_NUM + _IO_NUM)
  
  static vsi_status op_compute
      (
      vsi_nn_node_t * self,
      vsi_nn_tensor_t ** inputs,
      vsi_nn_tensor_t ** outputs
      )
  {
      vsi_status status = VSI_FAILURE;
      uint32_t axis;
      vsi_nn_fcl_param * p;
      uint32_t i = 0;
      uint32_t num_fc = 1, num_no_fc = 1;
      uint32_t num_of_dims[4] = {0};
      int32_t input_size[VSI_NN_MAX_DIM_NUM] = {0};
      int32_t output_size[VSI_NN_MAX_DIM_NUM] = {0};
      int32_t weights_size[VSI_NN_MAX_DIM_NUM] = {0};
      int32_t bias_size[VSI_NN_MAX_DIM_NUM] = {0};
      uint32_t ofm = 0;
      uint32_t dims = 0;
      vx_tensor input = NULL;
      vx_tensor output = NULL;
      vx_tensor weight = NULL;
      vx_tensor bias = NULL;
  
      p = (vsi_nn_fcl_param *)&(self->nn_param.fcl);
      axis = p->axis;
  
      memcpy(input_size, inputs[0]->attr.size, sizeof(uint32_t) * VSI_NN_MAX_DIM_NUM);
      num_of_dims[0] = inputs[0]->attr.dim_num;
      memcpy(output_size, outputs[0]->attr.size, sizeof(uint32_t) * VSI_NN_MAX_DIM_NUM);
      num_of_dims[1] = outputs[0]->attr.dim_num;
      memcpy(weights_size, inputs[1]->attr.size, sizeof(uint32_t) * VSI_NN_MAX_DIM_NUM);
      num_of_dims[2] = inputs[1]->attr.dim_num;
      if( inputs[2] != NULL )
      {
          memcpy(bias_size, inputs[2]->attr.size, sizeof(uint32_t) * VSI_NN_MAX_DIM_NUM);
          num_of_dims[3] = inputs[2]->attr.dim_num;
      }
  
      ofm = weights_size[num_of_dims[2] - 1];
  
      for(i = 0; i <= (uint32_t)axis; ++i)
      {
          num_fc *= input_size[i];
      }
      for(i = axis + 1; i < num_of_dims[0]; ++i)
      {
          num_no_fc *= input_size[i];
      }
  
      input_size[0] = num_fc;
      input_size[1] = num_no_fc;
      dims= 2;
      input = vxReshapeTensor(inputs[0]->t, input_size, dims);
  
      weights_size[0] = num_fc;
      weights_size[1] = ofm;
      dims= 2;
      weight = vxReshapeTensor(inputs[1]->t, weights_size, dims);
  
      if( inputs[2] != NULL )
      {
          bias_size[0] = ofm;
          bias_size[1] = 1;
          dims= 2;
          bias = vxReshapeTensor(inputs[2]->t, bias_size, dims);
      }
  
      output_size[0] = ofm;
      output_size[1] = num_no_fc;
      dims= 2;
      output = vxReshapeTensor(outputs[0]->t, output_size, dims);
  
      self->n = vxFullyConnectedLayer(
          self->graph->g,
          input,
          weight,
          bias,
          self->vx_param.overflow_policy,
          self->vx_param.rounding_policy,
          output
          );
      if( NULL != self->n )
      {
          status = VSI_SUCCESS;
      }
  
      if (input)  vxReleaseTensor(&input);
      if (weight) vxReleaseTensor(&weight);
      if (bias)   vxReleaseTensor(&bias);
      if (output) vxReleaseTensor(&output);
  
      return status;
  } /* op_compute() */
  
  static vsi_bool op_check
      (
      vsi_nn_node_t * self,
      vsi_nn_tensor_t ** inputs,
      vsi_nn_tensor_t ** outputs
      )
  {
      vsi_bool ret = FALSE;
  
      ret = vsi_nn_OpCheck(VSI_NN_OP_FCL, self, inputs, outputs);
  
      return ret;
  } /* op_check() */
  
  static vsi_bool op_setup
      (
      vsi_nn_node_t * self,
      vsi_nn_tensor_t ** inputs,
      vsi_nn_tensor_t ** outputs
      )
  {
      vsi_nn_fcl_param * p;
      uint32_t i, j;
      uint32_t num_in_fmp = 1;
  
  #ifdef VX_CONVERT_POLICY_WRAP_ENABLE
      if ( vsi_nn_compareVersion(self->graph, 1, 1, 21) == -1 )
      {
          self->vx_param.overflow_policy = VX_CONVERT_POLICY_SATURATE;
      }
  #endif
  
      if( VSI_NN_DIM_AUTO == outputs[0]->attr.dim_num )
      {
          p = (vsi_nn_fcl_param *)&(self->nn_param.fcl);
          if (inputs[1]->attr.is_const == TRUE)
          {
              outputs[0]->attr.dim_num = inputs[0]->attr.dim_num - p->axis;
              for(i = p->axis + 1, j = 1; i < inputs[0]->attr.dim_num && j < outputs[0]->attr.dim_num; ++i, ++j)
              {
                  outputs[0]->attr.size[j] = inputs[0]->attr.size[i];
              }
          }
          else
          {
              /* For fullconnect_op, weight not const tensor */
              outputs[0]->attr.dim_num = 2;
              for (i = p->axis + 1; i < inputs[0]->attr.dim_num; i++)
              {
                  num_in_fmp *= inputs[0]->attr.size[i];
              }
              outputs[0]->attr.size[1] = num_in_fmp;
          }
          outputs[0]->attr.size[0] = p->weights;
      }
      return TRUE;
  } /* op_setup() */
  
  #ifdef __cplusplus
  extern "C" {
  #endif
  /* Registrar */
  DEF_OP_REG
      (
      /* op_name    */ FCL2,
      /* init       */ NULL,
      /* compute    */ op_compute,
      /* deinit     */ vsi_nn_op_common_deinit,
      /* check      */ op_check,
      /* setup      */ op_setup,
      /* optimize   */ NULL,
      /* input_num  */ _INPUT_NUM,
      /* output_num */ _OUTPUT_NUM
      );
  #ifdef __cplusplus
  }
  #endif
  
  