// 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/reshape.h"

#include "driver/huawei_ascend_npu/converter/converter.h"
#include "utility/debug.h"
#include "utility/hints.h"
#include "utility/logging.h"
#include "utility/modeling.h"

namespace nnadapter {
namespace huawei_ascend_npu {

std::vector<int32_t> GetShape(core::Operand* input_operand,
                              core::Operand* output_operand,
                              uint32_t shape_count) {
  int size_in = 1;
  auto input_dimensions_data = input_operand->type.dimensions.data;
  auto output_dimensions_data = output_operand->type.dimensions.data;
  for (uint32_t i = 0; i < input_operand->type.dimensions.count; i++) {
    if (input_dimensions_data[i] == NNADAPTER_UNKNOWN ||
        input_dimensions_data[i] == -1) {
      continue;
    } else {
      size_in *= static_cast<int64_t>(input_dimensions_data[i]);
    }
  }
  int size_out = 1;
  for (uint32_t i = 0; i < shape_count; i++) {
    if (output_dimensions_data[i] == NNADAPTER_UNKNOWN ||
        output_dimensions_data[i] == -1) {
      continue;
    } else {
      size_out *= static_cast<int64_t>(output_dimensions_data[i]);
    }
  }
  for (uint32_t i = 0; i < shape_count; i++) {
    if (output_dimensions_data[i] == -1) {
      output_dimensions_data[i] = size_in / size_out;
    }
  }

  std::vector<int32_t> shape = std::vector<int32_t>(
      output_dimensions_data,
      output_dimensions_data + output_operand->type.dimensions.count);
  for (auto& value : shape) {
    if (value == NNADAPTER_UNKNOWN) {
      value = -1;
    }
  }
  return shape;
}

int ConvertReshape(Converter* converter, core::Operation* operation) {
  RESHAPE_OPERATION_EXTRACT_INPUTS_OUTPUTS

  // Convert to GE operators
  auto input_operator = converter->GetMappedOperator(input_operand);
  if (!input_operator) {
    input_operator = converter->ConvertOperand(input_operand);
  }
  std::shared_ptr<Operator> shape_operator = nullptr;
  if (IsTemporaryShapeOperand(shape_operand)) {
    if (IsOperandWithDynamicShape(shape_operand)) {
      shape_operator = converter->GetMappedOperator(shape_operand);
      if (!shape_operator) {
        shape_operator = converter->ConvertOperand(shape_operand);
      }
    } else {
      auto& temporary_shape = *(GetTemporaryShape(shape_operand));
      auto shape_count = temporary_shape.count;
      auto shape = GetShape(input_operand, output_operand, shape_count);
      shape_operator = converter->AddInt32ConstantOperator(shape);
    }
  } else if (IsConstantOperand(shape_operand)) {
    auto shape_count = shape_operand->length / sizeof(int32_t);
    auto shape = GetShape(input_operand, output_operand, shape_count);
    shape_operator = converter->AddInt32ConstantOperator(shape);
  } else {
    shape_operator = converter->GetMappedOperator(shape_operand);
    if (!shape_operator) {
      shape_operator = converter->ConvertOperand(shape_operand);
    }
  }
  auto reshape_op = converter->AddOperator<ge::op::Reshape>(output_operand);
  SET_INPUT(reshape_op, x, input_operator);
  SET_INPUT(reshape_op, shape, shape_operator);
  MAP_OUTPUT(reshape_op, y, output_operand);
  return NNADAPTER_NO_ERROR;
}

}  // namespace huawei_ascend_npu
}  // namespace nnadapter
