class_docstr: An NER visualizer that renders NER prediction as a string of HTML
  inline to any Python class Jupyter notebooks.
class_docstr_tok: ["An","NER","visualizer","that","renders","NER","prediction","as","a","string","of","HTML","inline","to","any","Python","class","Jupyter","notebooks","."]
code: def __init__(self, pred, sent, seed):
      self.pred = pred
      self.sent = sent
      self.colors = {}
      self.spans = merge_spans(sent, pred, for_visualizer=True)
      self.spans = collections.OrderedDict(sorted(self.spans.items()))
      self.rng = np.random.RandomState(seed)
  
imports: import collections
  import colorsys
  import logging
  import re
  from enum import Enum, unique
  from typing import List
  import matplotlib
  import matplotlib.colors
  import matplotlib.figure
  import matplotlib.pyplot
  import numpy
  import pandas
  from matplotlib.backends.backend_agg import FigureCanvasAgg
  from PIL import Image
  from .colormap import random_color
  from .misc import merge_spans
label_desc: Use image node_id 1 to create a new NERVisualizer object  with example: obj = NERVisualizer(pred, sent, seed)