class_docstr: Anchor generator for SSD.
  
  Args:
      strides (list[int]  | list[tuple[int, int]]): Strides of anchors
          in multiple feature levels.
      ratios (list[float]): The list of ratios between the height and width
          of anchors in a single level.
      basesize_ratio_range (tuple(float)): Ratio range of anchors.
      input_size (int): Size of feature map, 300 for SSD300,
          512 for SSD512.
      scale_major (bool): Whether to multiply scales first when generating
          base anchors. If true, the anchors in the same row will have the
          same scales. It is always set to be False in SSD.
docstr: str: a string that describes the module
code: def __repr__(self):
      """str: a string that describes the module"""
      indent_str = "    "
      repr_str = self.__class__.__name__ + "(\n"
      repr_str += f"{indent_str}strides={self.strides},\n"
      repr_str += f"{indent_str}scales={self.scales},\n"
      repr_str += f"{indent_str}scale_major={self.scale_major},\n"
      repr_str += f"{indent_str}input_size={self.input_size},\n"
      repr_str += f"{indent_str}scales={self.scales},\n"
      repr_str += f"{indent_str}ratios={self.ratios},\n"
      repr_str += f"{indent_str}num_levels={self.num_levels},\n"
      repr_str += f"{indent_str}base_sizes={self.base_sizes},\n"
      repr_str += f"{indent_str}basesize_ratio_range="
      repr_str += f"{self.basesize_ratio_range})"
      return repr_str
  
imports: import mmcv
  import numpy
  import torch
  from torch.nn.modules.utils import _pair
  from .builder import ANCHOR_GENERATORS
label_desc: Use image node_id 3 for calling the SSDAnchorGenerator obj's underlying member method code with example usage: obj.__repr__() and returns: repr_str