Function Eval

tensorflow/lite/kernels/depthwise_conv.cc:300–333

template <KernelType kernel_type>
TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
  auto* params =
      reinterpret_cast<TfLiteDepthwiseConvParams*>(node->builtin_data);
  OpData* data = reinterpret_cast<OpData*>(node->user_data);

  TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
  const TfLiteTensor* input = GetInput(context, node, kInputTensor);
  const TfLiteTensor* filter = GetInput(context, node, kFilterTensor);
  const TfLiteTensor* bias =
      (NumInputs(node) == 3) ? GetInput(context, node, kBiasTensor) : nullptr;

  // TODO(aselle): Consider whether float conv and quantized conv should be
  // separate ops to avoid dispatch overhead here.
  switch (input->type) {  // Already know in/out types are same.
    case kTfLiteFloat32:
      EvalFloat<kernel_type>(context, node, params, data, input, filter, bias,
                             output);
      break;
    case kTfLiteUInt8:
      EvalQuantized<kernel_type>(context, node, params, data, input, filter,
                                 bias, output);
      break;
    case kTfLiteInt8: {
      EvalQuantizedPerChannel<kernel_type>(context, node, params, data, input,
                                           filter, bias, output);
      break;
    }
    default:
      context->ReportError(context, "Type %d not currently supported.",
                           input->type);
      return kTfLiteError;
  }
  return kTfLiteOk;
}

}  // namespace depthwise_conv