class_docstr: Main class which validates the passed estimator and
  coordinates the kind of estimator to a concrete subclass.
code: def template(self, name: Union[str, enum.Template]):
      template = enum.Template.convert(name)
      if can(self.estimator, self.language, template):
          self._template = template
      else:
          name = self._estimator.estimator_name
          language = enum.Language.convert(self.language)
          msg = (
              "The passed template `{}` is not "
              "supported for the estimator `{}` "
              "and language `{}`."
          )
          msg = msg.format(template.value, name, language.value.KEY)
          raise exception.NotSupportedYetError(msg)
  
imports: import urllib.request
  from abc import ABCMeta
  from collections import OrderedDict
  from functools import partial
  from json import JSONDecodeError, loads
  from multiprocessing import Pool, cpu_count
  from os import environ, remove
  from pathlib import Path
  from shutil import which
  from subprocess import STDOUT, CalledProcessError, check_output
  from sys import platform, stdout, version_info
  from tempfile import mktemp
  from textwrap import dedent
  from time import sleep
  from typing import Callable, Dict, List, Optional, Tuple, Union
  import numpy
  from loguru import logger
  from tabulate import tabulate
  from sklearn import __version__
  from sklearn.base import BaseEstimator, ClassifierMixin, RegressorMixin
  from sklearn.ensemble import BaseEnsemble
  from sklearn.metrics import accuracy_score
  from sklearn_porter import decorators
  from sklearn_porter import enums
  from sklearn_porter import exceptions
  from sklearn_porter import meta
  from sklearn_porter.utils import options
label_desc: Use image node_id 7 for calling the Estimator obj's underlying member method code with example usage: obj.template(name) without return types