code: def _get_learning_rate(self):
      learning_rates = {"constant": 1, "pegasos": 2, "invscaling": 3}
      return learning_rates[self.learning_rate]
  
imports: import warnings
  import numpy
  from sklearn.utils import check_random_state
  from sklearn.utils.extmath import safe_sparse_dot
  from sklearn.utils.validation import assert_all_finite
  from .base import BaseClassifier
  from .base import BaseRegressor
  from .dataset_fast import get_dataset
  from .sgd_fast import _binary_sgd
  from .sgd_fast import _multiclass_sgd
  from .sgd_fast import ModifiedHuber
  from .sgd_fast import Hinge
  from .sgd_fast import SquaredHinge
  from .sgd_fast import Log
  from .sgd_fast import SquaredLoss
  from .sgd_fast import Huber
  from .sgd_fast import EpsilonInsensitive
  from .sgd_fast import MulticlassLog
  from .sgd_fast import MulticlassHinge
  from .sgd_fast import MulticlassSquaredHinge
label_desc: Use image node_id 2 for calling the _BaseSGD obj's underlying member method code with example usage: obj._get_learning_rate() and returns: learning_rates