code: def forward(self, x):
      x = F.relu(F.max_pool2d(self.conv1(x), 2))
      x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2))
      x = x.view(-1, 320)
      x = F.relu(self.fc1(x))
      x = F.dropout(x, training=self.training)
      x = self.fc2(x)
      return F.log_softmax(x)
  
file_path: MachineLearningNotebooks/how-to-use-azureml/ml-frameworks/pytorch/distributed-pytorch-with-horovod/pytorch_horovod_mnist.py
imports: from __future__ import print_function
  import argparse
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from torchvision import datasets, transforms
  import torch.utils.data.distributed
  import horovod.torch
  from azureml.core.run import Run
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