code: def __init__(
      self,
      loss,
      penalty,
      alpha,
      fit_intercept,
      tol,
      learning_rate,
      l1_ratio=0.15,
      epsilon=0.1,
      eta0=0.01,
      power_t=0.5,
      average=False,
      random_state=None,
  ):
      self.max_iter = self.get_max_iter()
      self.loss = loss
      self.penalty = penalty
      self.alpha = alpha
      self.fit_intercept = fit_intercept
      self.tol = tol
      self.learning_rate = learning_rate
      self.l1_ratio = l1_ratio
      self.epsilon = epsilon
      self.eta0 = eta0
      self.power_t = power_t
      self.random_state = random_state
      self.average = average
  
      self.estimator = None
      self.scaler = None
  
file_path: auto-sklearn/autosklearn/pipeline/components/regression/sgd.py
imports: from typing import Optional
  from ConfigSpace.conditions import EqualsCondition, InCondition
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.hyperparameters import CategoricalHyperparameter, UniformFloatHyperparameter, UnParametrizedHyperparameter
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from autosklearn.pipeline.components.base import AutoSklearnRegressionAlgorithm, IterativeComponent
  from autosklearn.pipeline.constants import DENSE, PREDICTIONS, SPARSE, UNSIGNED_DATA
  from autosklearn.util.common import check_for_bool
label_desc: Use image node_id 1 to create a new SGD object from inherited base classes: IterativeComponent, AutoSklearnRegressionAlgorithm with example: obj = SGD(loss, penalty, alpha, fit_intercept, tol, learning_rate, l1_ratio, epsilon, eta0, power_t, average, random_state)