<|start_filename|>torchvision/csrc/ROIAlign.h<|end_filename|>
#pragma once

#include "cpu/vision_cpu.h"

#ifdef WITH_CUDA
#include "cuda/vision_cuda.h"
#endif

// Interface for Python
at::Tensor ROIAlign_forward(
    const at::Tensor& input, // Input feature map.
    const at::Tensor& rois, // List of ROIs to pool over.
    const float spatial_scale, // The scale of the image features. ROIs will be
    // scaled to this.
    const int pooled_height, // The height of the pooled feature map.
    const int pooled_width, // The width of the pooled feature
    const int sampling_ratio) // The number of points to sample in each bin
// along each axis.
{
  if (input.type().is_cuda()) {
#ifdef WITH_CUDA
    return ROIAlign_forward_cuda(
        input,
        rois,
        spatial_scale,
        pooled_height,
        pooled_width,
        sampling_ratio);
#else
    AT_ERROR("Not compiled with GPU support");
#endif
  }
  return ROIAlign_forward_cpu(
      input, rois, spatial_scale, pooled_height, pooled_width, sampling_ratio);
}

at::Tensor ROIAlign_backward(
    const at::Tensor& grad,
    const at::Tensor& rois,
    const float spatial_scale,
    const int pooled_height,
    const int pooled_width,
    const int batch_size,
    const int channels,
    const int height,
    const int width,
    const int sampling_ratio) {
  if (grad.type().is_cuda()) {
#ifdef WITH_CUDA
    return ROIAlign_backward_cuda(
        grad,
        rois,
        spatial_scale,
        pooled_height,
        pooled_width,
        batch_size,
        channels,
        height,
        width,
        sampling_ratio);
#else
    AT_ERROR("Not compiled with GPU support");
#endif
  }
  return ROIAlign_backward_cpu(
      grad,
      rois,
      spatial_scale,
      pooled_height,
      pooled_width,
      batch_size,
      channels,
      height,
      width,
      sampling_ratio);
}
