class_docstr: Generate anchors according to the feature maps
  
  Args:
      anchor_sizes (list[float] | list[list[float]]): The anchor sizes at 
          each feature point. list[float] means all feature levels share the 
          same sizes. list[list[float]] means the anchor sizes for 
          each level. The sizes stand for the scale of input size.
      aspect_ratios (list[float] | list[list[float]]): The aspect ratios at
          each feature point. list[float] means all feature levels share the
          same ratios. list[list[float]] means the aspect ratios for
          each level.
      strides (list[float]): The strides of feature maps which generate 
          anchors
      offset (float): The offset of the coordinate of anchors, default 0.
      
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docstr: Returns:
      int: number of anchors at every pixel
          location, on that feature map.
          For example, if at every pixel we use anchors of 3 aspect
          ratios and 5 sizes, the number of anchors is 15.
          For FPN models, `num_anchors` on every feature map is the same.
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code: def num_anchors(self):
      """
      Returns:
          int: number of anchors at every pixel
              location, on that feature map.
              For example, if at every pixel we use anchors of 3 aspect
              ratios and 5 sizes, the number of anchors is 15.
              For FPN models, `num_anchors` on every feature map is the same.
      """
      return len(self.cell_anchors[0])
  
imports: import math
  import paddle
  import paddle.nn
  import numpy
  from ppdet.core.workspace import register
label_desc: Use image node_id 8 for calling the AnchorGenerator obj's underlying member method code with example usage: obj.num_anchors() and returns: len