text: // Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
  //
  // Licensed under the Apache License, Version 2.0 (the "License");
  // you may not use this file except in compliance with the License.
  // You may obtain a copy of the License at
  //
  //     http://www.apache.org/licenses/LICENSE-2.0
  //
  // Unless required by applicable law or agreed to in writing, software
  // distributed under the License is distributed on an "AS IS" BASIS,
  // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  // See the License for the specific language governing permissions and
  // limitations under the License.
  
  #include "lite/core/subgraph_bridge_registry.h"
  #include "lite/kernels/rknpu/bridges/graph.h"
  #include "lite/kernels/rknpu/bridges/utility.h"
  
  namespace paddle {
  namespace lite {
  namespace subgraph {
  namespace rknpu {
  
  int ConcatConverter(void* ctx, OpLite* op, KernelBase* kernel) {
    CHECK(ctx != nullptr);
    CHECK(op != nullptr);
    auto graph = static_cast<Graph*>(ctx);
    auto op_info = op->op_info();
    auto op_type = op_info->Type();
    auto scope = op->scope();
    VLOG(3) << "[RKNPU] Converting " << op_type << " ... ";
  
    // Get input and output vars and op attributes
    auto x_names = op_info->Input("X");
    auto out_name = op_info->Output("Out").front();
    auto output = scope->FindMutableTensor(out_name);
    auto out_scale_name = "Out0_scale";
    auto output_dims = output->dims();
    auto output_dims_count = output_dims.size();
  
    auto axis = op_info->GetAttr<int>("axis");
    if (axis == -1) {
      axis = output_dims_count - 1;
    }
    auto num = x_names.size();
  
    // for quantization
    bool enable_int8 = false;
    float input_scale = 1.0;
    float output_scale = 1.0;
    int bit_length = 8;
    DataLayoutType layout = DATALAYOUT(kNCHW);
    PrecisionType precision = PRECISION(kFloat);
  
    if (op_info->HasOutputScale(out_scale_name, true)) {
      enable_int8 = true;
      bit_length = op_info->GetAttr<int>("bit_length");
      output_scale = op_info->GetOutputScale(out_scale_name, true)[0];
      precision = PRECISION(kInt8);
    } else {
      enable_int8 = false;
      LOG(WARNING) << "[RK-NPU] the op is float-type " << op_type;
      precision = PRECISION(kFloat);
    }
    // Traverse all of input nodes which are added into the new created concat
    // node
    std::vector<std::shared_ptr<rk::nn::Tensor>> inputs;
    std::vector<std::shared_ptr<rk::nn::Tensor>> outputs;
  
    for (int i = 0; i < num; i++) {
      auto x_name = x_names[i];
      auto x_scale_name = "X" + paddle::lite::to_string(i) + "_scale";
      auto x = scope->FindMutableTensor(x_name);
      auto x_dims = x->dims();
      std::shared_ptr<Node> x_node = nullptr;
      if (graph->Has(x_name)) {
        x_node = graph->Get(x_name);
      } else {
        x_node = graph->Add(x_name, *x);
        QuantizationInfo qnt;
        qnt.enable_int8 = enable_int8;
  
        if (enable_int8) {
          CHECK(op_info->HasInputScale(x_scale_name, true));
          input_scale = op_info->GetInputScale(x_scale_name, true)[0];
          qnt.quant_bits = bit_length;
          qnt.scale.push_back(input_scale);
          x->mutable_data<int8_t>();
        }
        x_node = graph->Add(x_name, *x, precision, layout, qnt);
      }
  
      inputs.push_back(x_node->data());
    }
  
    std::shared_ptr<Node> output_node = nullptr;
    QuantizationInfo output_qnt;
  
    output_qnt.enable_int8 = enable_int8;
  
    if (enable_int8) {
      output_qnt.quant_bits = bit_length;
      output_qnt.scale.push_back(output_scale);
      output->mutable_data<int8_t>();
    }
  
    output_node = graph->Add(out_name, *output, precision, layout, output_qnt);
    outputs.push_back(output_node->data());
  
    rk::nn::ConcatAttr attrs;
    attrs.axis = axis;
  
    auto rGraph = graph->GetHandle();
    auto concat = rGraph->AddOperator(
        rk::nn::OperatorType::CONCAT, inputs, outputs, &attrs);
  
    return SUCCESS;
  }
  
  }  // namespace rknpu
  }  // namespace subgraph
  }  // namespace lite
  }  // namespace paddle
  
  REGISTER_SUBGRAPH_BRIDGE(concat,
                           kRKNPU,
                           paddle::lite::subgraph::rknpu::ConcatConverter);
  