class_docstr: Multilayer Perceptron, implemented in PyTorch, for use with TPOT.
      
class_docstr_tok: ["Multilayer","Perceptron",",","implemented","in","PyTorch",",","for","use","with","TPOT","."]
code: def __init__(
      self,
      num_epochs=10,
      batch_size=8,
      learning_rate=0.01,
      weight_decay=0,
      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 PytorchMLPClassifier object from inherited base classes: PytorchClassifier with example: obj = PytorchMLPClassifier(num_epochs, batch_size, learning_rate, weight_decay, verbose)