class_docstr: Outputs object detection proposals by applying estimated bounding-box
  transformations to a set of regular boxes (called "anchors").
class_docstr_tok: ["Outputs","object","detection","proposals","by","applying","estimated","bounding-box","transformations","to","a","set","of","regular","boxes","(","called","``","anchors","''",")","."]
code: def deserialize(inputs, name, state):
      return ProposalLayer(
          inputs[0],
          inputs[1],
          inputs[2],
          layer_config=state["layer_config"],
          name=name,
      )
  
file_path: CNTK/Examples/Image/Detection/utils/rpn/proposal_layer.py
imports: from cntk import output_variable, FreeDimension
  from cntk.ops.functions import UserFunction
  import numpy
  import yaml
  from utils.rpn.generate_anchors import generate_anchors
  from utils.rpn.bbox_transform import bbox_transform_inv, clip_boxes
  from utils.nms_wrapper import nms
label_desc: Use image node_id 7 for calling the ProposalLayer obj's underlying member method code with example usage: obj.deserialize(inputs, name, state) and returns: ProposalLayer