text: import torch.nn as nn
  import torch.nn.functional as F
  
  class Net(nn.Module):
      def __init__(self):
          super(Net,self).__init__()
  
          self.conv1 = nn.Conv2d(3,3,3)
          self.maxpool1 = nn.MaxPool2d(kernel_size=2)
          self.relu1 = nn.ReLU(inplace=True)
  
          self.conv2 = nn.Conv2d(3,6,3)
          self.maxpool2 = nn.MaxPool2d(kernel_size=2)
          self.relu2 = nn.ReLU(inplace=True)
  
          self.fc1 = nn.Linear(6 * 123 * 123, 150)
  
          self.fc2_classes = nn.Linear(150,2)
          self.fc2_species = nn.Linear(150,3)
  
          self.relu3 = nn.ReLU(inplace=True)
  
          self.softmax = nn.Softmax(dim=1)
  
  
      def forward(self,x):
          x = self.conv1(x)
          x = self.maxpool1(x)
          x = self.relu1(x)
  
          x = self.conv2(x)
          x = self.maxpool2(x)
          x = self.relu2(x)
  
          x = x.view(-1, 6 * 123 * 123)
          x = self.fc1(x)
          x = self.relu3(x)
          x = F.dropout(x, training=self.training)
          
          x_classes = self.fc2_classes(x) 
  #        x_classes = self.softmax(x_classes)
  
          x_species = self.fc2_species(x)
  #        x_species = self.softmax(x_species)
  
          return x_classes,x_species
  