class_docstr: make use of the pre-trained frequency prior
class_docstr_tok: ["make","use","of","the","pre-trained","frequency","prior"]
code: def __init__(self, prior_pkl):
      super(EdgeFreqPrior, self).__init__()
      with open(prior_pkl, "rb") as f:
          freq_prior = pickle.load(f)
      self.freq_prior = freq_prior
  
imports: import pickle
  import dgl
  import gluoncv
  import mxnet
  import numpy
  from dgl.nn.mxnet import GraphConv
  from dgl.utils import toindex
  from mxnet import nd
  from mxnet.gluon import nn
label_desc: Use image node_id 1 to create a new EdgeFreqPrior object from inherited base classes: nn with example: obj = EdgeFreqPrior(prior_pkl)