code: def __init__(self, model, num_classes, transitions_blob=None):
      self.model = model
      self.num_classes = num_classes
      self.num_classes_padded = (
          num_classes + 2
      )  # After adding BOS and EOS
      if not transitions_blob:
          transitions_blob = self.model.param_init_net.UniformFill(
              [],
              [core.ScopedBlobReference("crf_transitions")],
              shape=[self.num_classes_padded, self.num_classes_padded],
              min=-1.0,
              max=1.0,
          )
      self.transitions = transitions_blob
      self.model.params.append(self.transitions)
  
file_path: pytorch/caffe2/python/crf.py
imports: import numpy
  from caffe2.python import brew, core, model_helper, recurrent
label_desc: Use image node_id 1 to create a new CRFWithLoss object  with example: obj = CRFWithLoss(model, num_classes, transitions_blob)