// Copyright (c) 2022 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/arg_min_max.h"
#include "driver/verisilicon_timvx/converter/converter.h"
#include "utility/debug.h"
#include "utility/logging.h"

namespace nnadapter {
namespace verisilicon_timvx {

int ConvertArgMinMax(Converter* converter, core::Operation* operation) {
  ARG_MIN_MAX_OPERATION_EXTRACT_INPUTS_OUTPUTS

  // Convert to tim-vx tensors and operators
  auto input_tensor = converter->GetMappedTensor(input_operand);
  if (!input_tensor) {
    input_tensor = converter->ConvertOperand(input_operand);
  }

  auto output_tensor = converter->ConvertOperand(output_operand);
  auto dimensions = input_operand->type.dimensions;
  switch (operation->type) {
#define CONVERT_ARGMINMAX(type, class_name)                            \
  case NNADAPTER_##type: {                                             \
    auto arg_op =                                                      \
        converter->graph()->CreateOperation<tim::vx::ops::class_name>( \
            ConvertToTimVXAxis(axis, dimensions.count));               \
    arg_op->BindInputs({input_tensor});                                \
    arg_op->BindOutputs({output_tensor});                              \
  } break;
    CONVERT_ARGMINMAX(ARG_MAX, ArgMax);
    CONVERT_ARGMINMAX(ARG_MIN, ArgMin);

#undef CONVERT_ARGMINMAX
    default:
      NNADAPTER_LOG(FATAL) << "Unsupported comparison operation type "
                           << OperationTypeToString(operation->type)
                           << " is found.";
      break;
  }

  if (keepdim) {
    std::vector<uint32_t> size(dimensions.data,
                               dimensions.data + dimensions.count);
    auto reshape_tensor = converter->ConvertOperand(output_operand);
    auto reshape_op =
        converter->graph()->CreateOperation<tim::vx::ops::Reshape>(size);
    reshape_op->BindInputs({output_tensor});
    reshape_op->BindOutputs({reshape_tensor});
  }
  return NNADAPTER_NO_ERROR;
}

}  // namespace verisilicon_timvx
}  // namespace nnadapter
