code: def __init__(self, prefix, epoch, ctx_id=0):
      print("loading", prefix, epoch)
      if ctx_id >= 0:
          ctx = mx.gpu(ctx_id)
      else:
          ctx = mx.cpu()
      sym, arg_params, aux_params = mx.model.load_checkpoint(
          prefix, epoch
      )
      all_layers = sym.get_internals()
      sym = all_layers["heatmap_output"]
      image_size = (128, 128)
      self.image_size = image_size
      model = mx.mod.Module(symbol=sym, context=ctx, label_names=None)
      # model = mx.mod.Module(symbol=sym, context=ctx)
      model.bind(
          for_training=False,
          data_shapes=[("data", (1, 3, image_size[0], image_size[1]))],
      )
      model.set_params(arg_params, aux_params)
      self.model = model
      mtcnn_path = os.path.join(
          os.path.dirname(__file__), "..", "deploy", "mtcnn-model"
      )
      self.det_threshold = [0.6, 0.7, 0.8]
      self.detector = MtcnnDetector(
          model_folder=mtcnn_path,
          ctx=ctx,
          num_worker=1,
          accurate_landmark=True,
          threshold=self.det_threshold,
      )
  
file_path: insightface/alignment/heatmap/test.py
imports: import argparse
  import cv2
  import sys
  import numpy
  import os
  import mxnet
  import datetime
  import img_helper
  from mtcnn_detector import MtcnnDetector
label_desc: Use image node_id 1 to create a new Handler object  with example: obj = Handler(prefix, epoch, ctx_id)