class_docstr: Dataset class for the MS COCO Object Detection using Single Shot Object Detector (SSD).
  
  Args:
      opts: Command-line arguments
docstr: Given the height and width of the input to the SSD model, generate anchors
  
  Args:
      height: Height of the input image to the SSD model
      width: Width of the input image to the SSD model
  
  Returns:
      Tensor containing anchor locations
docstr_tok: ["Given","the","height","and","width","of","the","input","to","the","SSD","model",",","generate","anchors","Args",":","height",":","Height","of","the","input","image","to","the","SSD","model","width",":","Width","of","the","input","image","to","the","SSD","model","Returns",":","Tensor","containing","anchor","locations"]
code: def generate_anchors(self, height: int, width: int) -> Tensor:
      """Given the height and width of the input to the SSD model, generate anchors
  
      Args:
          height: Height of the input image to the SSD model
          width: Width of the input image to the SSD model
  
      Returns:
          Tensor containing anchor locations
      """
      anchors = []
      for output_stride in self.output_strides:
          if output_stride == -1:
              fm_width = fm_height = 1
          else:
              fm_width = int(math.ceil(width / output_stride))
              fm_height = int(math.ceil(height / output_stride))
          fm_anchor = self.anchor_box_generator(
              fm_height=fm_height,
              fm_width=fm_width,
              fm_output_stride=output_stride,
          )
          anchors.append(fm_anchor)
      anchors = torch.cat(anchors, dim=0)
      return anchors
  
imports: import argparse
  import math
  from typing import List, Mapping, Tuple, Union
  import torch
  from torch import Tensor
  from cvnets.anchor_generator import build_anchor_generator
  from cvnets.matcher_det import build_matcher
  from data.collate_fns import COLLATE_FN_REGISTRY
  from data.datasets import DATASET_REGISTRY
  from data.datasets.detection.coco_base import COCODetection
  from data.transforms import image_pil
  from data.transforms.common import Compose
  from utils import logger
label_desc: Use image node_id 4 for calling the COCODetectionSSD obj's underlying member method code with example usage: obj.generate_anchors(height, width) and returns: anchors