code: def get_all_anchors(*, stride, sizes, ratios, max_size):
      """
      Get all anchors in the largest possible image, shifted, floatbox
      Args:
          stride (int): the stride of anchors.
          sizes (tuple[int]): the sizes (sqrt area) of anchors
          ratios (tuple[int]): the aspect ratios of anchors
          max_size (int): maximum size of input image
  
      Returns:
          anchors: SxSxNUM_ANCHORx4, where S == ceil(MAX_SIZE/STRIDE), floatbox
          The layout in the NUM_ANCHOR dim is NUM_RATIO x NUM_SIZE.
  
      """
      # Generates a NAx4 matrix of anchor boxes in (x1, y1, x2, y2) format. Anchors
      # are centered on 0, have sqrt areas equal to the specified sizes, and aspect ratios as given.
      anchors = []
      for sz in sizes:
          for ratio in ratios:
              w = np.sqrt(sz * sz / ratio)
              h = ratio * w
              anchors.append([-w, -h, w, h])
      cell_anchors = np.asarray(anchors) * 0.5
  
      field_size = int(np.ceil(max_size / stride))
      shifts = (np.arange(0, field_size) * stride).astype("float32")
      shift_x, shift_y = np.meshgrid(shifts, shifts)
      shift_x = shift_x.flatten()
      shift_y = shift_y.flatten()
      shifts = np.vstack(
          (shift_x, shift_y, shift_x, shift_y)
      ).transpose()
      # Kx4, K = field_size * field_size
      K = shifts.shape[0]
  
      A = cell_anchors.shape[0]
      field_of_anchors = cell_anchors.reshape(
          (1, A, 4)
      ) + shifts.reshape((1, K, 4)).transpose((1, 0, 2))
      field_of_anchors = field_of_anchors.reshape(
          (field_size, field_size, A, 4)
      )
      # FSxFSxAx4
      # Many rounding happens inside the anchor code anyway
      # assert np.all(field_of_anchors == field_of_anchors.astype('int32'))
      field_of_anchors = field_of_anchors.astype("float32")
      return field_of_anchors
  
file_path: tensorpack/examples/FasterRCNN/modeling/model_rpn.py
imports: import tensorflow
  import numpy
  from tensorpack import tfv1
  from tensorpack.models import Conv2D, layer_register
  from tensorpack.tfutils.argscope import argscope
  from tensorpack.tfutils.scope_utils import auto_reuse_variable_scope, under_name_scope
  from tensorpack.tfutils.summary import add_moving_summary
  from tensorpack.utils.argtools import memoized
  from config import config
  from .model_box import clip_boxes
label_desc: Use image node_id 4 for calling a global function with example usage: get_all_anchors() and returns: field_of_anchors