code: def __init__(self, dropout, fc1_size, fc2_size):
      super().__init__()
      self.fc1 = nn.Linear(50, fc1_size)
      self.relu1 = nn.ReLU()
      self.dout = nn.Dropout(dropout)
      self.fc2 = nn.Linear(fc1_size, fc2_size)
      self.prelu = nn.PReLU(1)
      self.out = nn.Linear(fc2_size, 1)
      self.out_act = nn.Sigmoid()
  
imports: import os
  from unittest import TestCase
  import numpy
  import pytest
  import torch
  import torch.nn
  from torch.utils.data import Dataset, DataLoader
  from zoo.orca.automl.auto_estimator import AutoEstimator
  from zoo.orca.automl.pytorch_utils import LR_NAME
  from zoo.orca.automl import hp
label_desc: Use image node_id 1 to create a new Net object from inherited base classes: nn with example: obj = Net(dropout, fc1_size, fc2_size)