code: def forward(self, x):
      # Added the view for reshaping score requests
      x = x.view(-1, 1, 28, 28)
      x = F.relu(self.conv1(x))
      x = F.max_pool2d(x, 2, 2)
      x = F.relu(self.conv2(x))
      x = F.max_pool2d(x, 2, 2)
      x = x.view(-1, 4 * 4 * 50)
      x = F.relu(self.fc1(x))
      x = self.fc2(x)
      return F.log_softmax(x, dim=1)
  
file_path: MachineLearningNotebooks/how-to-use-azureml/ml-frameworks/using-mlflow/train-and-deploy-pytorch/scripts/train.py
imports: import mlflow
  import mlflow.pytorch
  from mlflow.utils.environment import _mlflow_conda_env
  import warnings
  import cloudpickle
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  import torchvision
  from torchvision import datasets, transforms
label_desc: Use image node_id 2 for calling the Net obj's underlying member method code with example usage: obj.forward(x) and returns: F