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.
      
class_docstr_tok: ["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","."]
code: def _create_grid_offsets(self, size, stride, offset):
      grid_height, grid_width = size[0], size[1]
      shifts_x = paddle.arange(
          offset * stride,
          grid_width * stride,
          step=stride,
          dtype="float32",
      )
      shifts_y = paddle.arange(
          offset * stride,
          grid_height * stride,
          step=stride,
          dtype="float32",
      )
      shift_y, shift_x = paddle.meshgrid(shifts_y, shifts_x)
      shift_x = paddle.reshape(shift_x, [-1])
      shift_y = paddle.reshape(shift_y, [-1])
      return shift_x, shift_y
  
imports: import math
  import paddle
  import paddle.nn
  import numpy
  from ppdet.core.workspace import register
label_desc: Use image node_id 5 for calling the AnchorGenerator obj's underlying member method code with example usage: obj._create_grid_offsets(size, stride, offset) and returns: shift_x,  shift_y