text: // Copyright (c) 2021 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 "operation/adaptive_pool2d.h"
  #include "driver/cambricon_mlu/converter.h"
  #include "utility/debug.h"
  #include "utility/logging.h"
  #include "utility/utility.h"
  
  namespace nnadapter {
  namespace cambricon_mlu {
  
  int ConvertAdaptivePool2D(Converter* converter, core::Operation* operation) {
    ADAPTIVE_POOL_2D_OPERATION_EXTRACT_INPUTS_OUTPUTS
  
    auto input_tensor = converter->GetMappedTensor(input_operand);
    if (!input_tensor) {
      input_tensor = converter->ConvertOperand(input_operand);
    }
    if (operation->type == NNADAPTER_ADAPTIVE_MAX_POOL_2D) {
      NNADAPTER_LOG(FATAL) << "Not support max pool2d.";
      return NNADAPTER_DEVICE_INTERNAL_ERROR;
    } else {
      auto pool2d_node =
          converter->network()->AddIAdaptiveAvgPool2DNode(input_tensor);
      NNADAPTER_CHECK(pool2d_node) << "Failed to add adaptive_avg_pool2d node.";
      pool2d_node->SetOutputSize(static_cast<int64_t>(output_height),
                                 static_cast<int64_t>(output_width));
      magicmind::Layout input_layout =
          ConvertToMagicMindDataLayout(input_operand->type.layout);
      pool2d_node->SetLayout(input_layout, input_layout);
      auto output_tensor = pool2d_node->GetOutput(0);
      converter->UpdateTensorMap(output_operand, output_tensor);
    }
    return NNADAPTER_NO_ERROR;
  }
  
  }  // namespace cambricon_mlu
  }  // namespace nnadapter
  