Function EvalPie

tensorflow/lite/kernels/fully_connected.cc:237–268

}

TfLiteStatus EvalPie(TfLiteContext* context, TfLiteNode* node,
                     TfLiteFullyConnectedParams* params, OpData* data,
                     const TfLiteTensor* input, const TfLiteTensor* filter,
                     const TfLiteTensor* bias, TfLiteTensor* output) {
  int total_input_size = 1;
  for (int i = 0; i < input->dims->size; i++) {
    total_input_size *= input->dims->data[i];
  }

  int input_size = filter->dims->data[1];
  const int batch_size = total_input_size / filter->dims->data[1];
  const int num_units = filter->dims->data[0];

  // Output = bias if bias tensor exists.
  if (bias) {
    tensor_utils::VectorBatchVectorAssign(bias->data.f, num_units, batch_size,
                                          output->data.f);
  } else {
    std::fill_n(output->data.f, batch_size * num_units, 0.0f);
  }

  // Compute output += weight * input
  tensor_utils::MatrixBatchVectorMultiplyAccumulate(
      filter->data.f, num_units, input_size, input->data.f, batch_size,
      output->data.f, /*result_stride=*/1);

  // Apply activation function
  tensor_utils::ApplyActivationToVector(output->data.f, batch_size * num_units,
                                        params->activation, output->data.f);

  return kTfLiteOk;
}

TfLiteStatus EvalHybrid(TfLiteContext* context, TfLiteNode* node,
                        TfLiteFullyConnectedParams* params, OpData* data,