code: def __init__(self, hidden_dim=32, n_classes=2):
      super().__init__()
      self.hidden_dim = hidden_dim
      self.n_classes = n_classes
  
      self.fc1 = nn.Linear(2, self.hidden_dim)
      self.fc2 = nn.Linear(self.hidden_dim, self.n_classes)
  
file_path: pytorch/functorch/examples/ensembling/parallel_train.py
imports: import argparse
  import math
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.func import functional_call, grad_and_value, stack_module_state, vmap
label_desc: Use image node_id 1 to create a new MLPClassifier object from inherited base classes: nn with example: obj = MLPClassifier(hidden_dim, n_classes)