code: def multiclass_classification_string_target(cls):
      multiclass_classification_integer_target(cls)
      cls.type = str
      cls.dtrain["label"] = cls.dtrain["label"].astype(str)
      cls.dtest["label"] = cls.dtest["label"].astype(str)
      cls.model = tc.boosted_trees_classifier.create(
          cls.dtrain,
          target=cls.target,
          validation_set=cls.dtest,
          **cls.param,
      )
      num_examples_per_class = {
          c: (cls.dtrain[cls.target] == c).sum()
          for c in cls.model.classes
      }
      cls.get_ans["num_examples_per_class"] = (
          lambda x: x == num_examples_per_class
      )
      cls.get_ans["classes"] = lambda x: set(x) == set(
          map(str, [0, 1, 2])
      )
      cls.get_ans["class_weights"] = lambda x: x == {
          "0": 1.0,
          "1": 1.0,
          "2": 1.0,
      }
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import unittest
  import turicreate
  import uuid
  import random
  import copy
  from turicreate.toolkits._main import ToolkitError
  import turicreate.toolkits.evaluation
  import shutil
  from array import array
  import os
label_desc: Use image node_id 6 for calling a global function with example usage: multiclass_classification_string_target(cls) without return types