class_docstr: Compute rotated anchors used by Rotated RPN (RRPN), described in
  "Arbitrary-Oriented Scene Text Detection via Rotation Proposals".
docstr: Args:
      features (list[Tensor]): list of backbone feature maps on which to generate anchors.
  
  Returns:
      list[RotatedBoxes]: a list of Boxes containing all the anchors for each feature map
          (i.e. the cell anchors repeated over all locations in the feature map).
          The number of anchors of each feature map is Hi x Wi x num_cell_anchors,
          where Hi, Wi are resolution of the feature map divided by anchor stride.
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code: def forward(self, features):
      """
      Args:
          features (list[Tensor]): list of backbone feature maps on which to generate anchors.
  
      Returns:
          list[RotatedBoxes]: a list of Boxes containing all the anchors for each feature map
              (i.e. the cell anchors repeated over all locations in the feature map).
              The number of anchors of each feature map is Hi x Wi x num_cell_anchors,
              where Hi, Wi are resolution of the feature map divided by anchor stride.
      """
      grid_sizes = [feature_map.shape[-2:] for feature_map in features]
      anchors_over_all_feature_maps = self._grid_anchors(grid_sizes)
      return [RotatedBoxes(x) for x in anchors_over_all_feature_maps]
  
imports: import collections
  import math
  from typing import List
  import torch
  from torch import nn
  from detectron2.config import configurable
  from detectron2.layers import ShapeSpec, move_device_like
  from detectron2.structures import Boxes, RotatedBoxes
  from detectron2.utils.registry import Registry
label_desc: Use image node_id 8 for calling the RotatedAnchorGenerator obj's underlying member method code with example usage: obj.forward(features) and returns: unknown