class_docstr: Logistic Regression classifier, implemented in PyTorch, for use with
  TPOT.
  
  For examples on standalone use (i.e., non-TPOT) refer to:
  https://github.com/trang1618/tpot-nn/blob/master/tpot_nn/estimator_sandbox.py
class_docstr_tok: ["Logistic","Regression","classifier",",","implemented","in","PyTorch",",","for","use","with","TPOT",".","For","examples","on","standalone","use","(","i.e.",",","non-TPOT",")","refer","to",":","https",":","\/\/github.com\/trang1618\/tpot-nn\/blob\/master\/tpot_nn\/estimator_sandbox.py"]
code: def __init__(
      self,
      num_epochs=10,
      batch_size=16,
      learning_rate=0.02,
      weight_decay=1e-4,
      verbose=False,
  ):
      self.num_epochs = num_epochs
      self.batch_size = batch_size
      self.learning_rate = learning_rate
      self.weight_decay = weight_decay
      self.verbose = verbose
  
      self.input_size = None
      self.num_classes = None
      self.network = None
      self.loss_function = None
      self.optimizer = None
      self.data_loader = None
      self.train_dset_len = None
      self.device = None
  
imports: from abc import abstractmethod
  import numpy
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.utils.validation import check_X_y, assert_all_finite, check_array, check_is_fitted
  from sklearn.utils.multiclass import type_of_target
label_desc: Use image node_id 1 to create a new PytorchLRClassifier object from inherited base classes: PytorchClassifier with example: obj = PytorchLRClassifier(num_epochs, batch_size, learning_rate, weight_decay, verbose)