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 "core/operation/conv2d.h"
  #include "core/hal/types.h"
  #include "utility/debug.h"
  #include "utility/logging.h"
  #include "utility/micros.h"
  #include "utility/modeling.h"
  #include "utility/utility.h"
  
  namespace nnadapter {
  namespace operation {
  
  NNADAPTER_EXPORT void UpdateConv2DPadAndDilation(
      int32_t input_size,
      int32_t filter_height_or_width,
      NNAdapterAutoPadCode auto_pad,
      int32_t* pad_top_or_left,
      int32_t* pad_bottom_or_right,
      int32_t stride_height_or_width,
      int32_t* dilation_height_or_width) {
    NNADAPTER_CHECK_NE(input_size, NNADAPTER_UNKNOWN);
    if (auto_pad == NNADAPTER_AUTO_PAD_SAME) {
      auto output_size =
          (input_size + stride_height_or_width - 1) / stride_height_or_width;
      auto pad_size = (output_size - 1) * stride_height_or_width +
                      filter_height_or_width - input_size;
      pad_size = pad_size < 0 ? 0 : pad_size;
      *pad_top_or_left = pad_size / 2;
      *pad_bottom_or_right = pad_size - *pad_top_or_left;
      *dilation_height_or_width = 1;
    } else if (auto_pad == NNADAPTER_AUTO_PAD_VALID) {
      *pad_top_or_left = 0;
      *pad_bottom_or_right = 0;
    }
  }
  
  NNADAPTER_EXPORT int32_t
  CalcConv2DOutputSize(int32_t input_size,
                       int32_t filter_height_or_width,
                       NNAdapterAutoPadCode auto_pad,
                       int32_t pad_top_or_left,
                       int32_t pad_bottom_or_right,
                       int32_t stride_height_or_width,
                       int32_t dilation_height_or_width) {
    if (input_size == NNADAPTER_UNKNOWN) {
      return NNADAPTER_UNKNOWN;
    }
    UpdateConv2DPadAndDilation(input_size,
                               filter_height_or_width,
                               auto_pad,
                               &pad_top_or_left,
                               &pad_bottom_or_right,
                               stride_height_or_width,
                               &dilation_height_or_width);
    auto dkernel = dilation_height_or_width * (filter_height_or_width - 1) + 1;
    return (input_size + (pad_top_or_left + pad_bottom_or_right) - dkernel) /
               stride_height_or_width +
           1;
  }
  
  int PrepareConv2D(hal::Operation* operation) {
    CONV_2D_OPERATION_EXTRACT_INPUTS_OUTPUTS
  
    // Infer the shape and type of output operands
    CopyOperandTypeExceptQuantParams(&output_operand->type, input_operand->type);
    auto infer_output_shape = [&](int32_t* input_dimensions,
                                  int32_t* output_dimensions) {
      output_dimensions[0] = input_dimensions[0];
      output_dimensions[1] = output_channel_size;
      output_dimensions[2] = CalcConv2DOutputSize(input_dimensions[2],
                                                  filter_height,
                                                  auto_pad,
                                                  pad_height_top,
                                                  pad_height_bottom,
                                                  stride_height,
                                                  dilation_height);
      output_dimensions[3] = CalcConv2DOutputSize(input_dimensions[3],
                                                  filter_width,
                                                  auto_pad,
                                                  pad_width_left,
                                                  pad_width_right,
                                                  stride_width,
                                                  dilation_width);
    };
    infer_output_shape(input_operand->type.dimensions.data,
                       output_operand->type.dimensions.data);
    for (uint32_t i = 0; i < input_operand->type.dimensions.dynamic_count; i++) {
      infer_output_shape(input_operand->type.dimensions.dynamic_data[i],
                         output_operand->type.dimensions.dynamic_data[i]);
    }
    NNADAPTER_VLOG(5) << "output: " << OperandToString(output_operand);
    return NNADAPTER_NO_ERROR;
  }
  
  }  // namespace operation
  }  // namespace nnadapter
  