code: def main(current_gpu_index, num_gpu):
      # setup the process groups
      setup(current_gpu_index, num_gpu)
  
      #################################################################
      ######## Writing a torch training loop for a Keras model ########
      #################################################################
  
      dataset = get_data()
      model = get_model()
  
      # prepare the dataloader
      dataloader = prepare(
          dataset, current_gpu_index, num_gpu, batch_size
      )
  
      # Instantiate the torch optimizer
      optimizer = optim.Adam(model.parameters(), lr=learning_rate)
  
      # Instantiate the torch loss function
      loss_fn = nn.CrossEntropyLoss()
  
      # Put model on device
      model = model.to(current_gpu_index)
      ddp_model = DDP(
          model,
          device_ids=[current_gpu_index],
          output_device=current_gpu_index,
      )
  
      train(ddp_model, dataloader, num_epochs, optimizer, loss_fn)
  
      ################################################################
      ######## Using a Keras model or layer in a torch Module ########
      ################################################################
  
      torch_module = MyModel().to(current_gpu_index)
      ddp_torch_module = DDP(
          torch_module,
          device_ids=[current_gpu_index],
          output_device=current_gpu_index,
      )
  
      # Instantiate the torch optimizer
      optimizer = optim.Adam(
          torch_module.parameters(), lr=learning_rate
      )
  
      # Instantiate the torch loss function
      loss_fn = nn.CrossEntropyLoss()
  
      train(
          ddp_torch_module, dataloader, num_epochs, optimizer, loss_fn
      )
  
      cleanup()
  
imports: import os
  import torch
  import torch.nn
  import torch.optim
  from keras import layers
  import keras
  import numpy
  import torch.multiprocessing
  import torch.distributed
  from torch.nn.parallel import DistributedDataParallel
  from torch.utils.data import DataLoader, Dataset
  from torch.utils.data.distributed import DistributedSampler
label_desc: Use image node_id 7 for calling a global function with example usage: main(current_gpu_index, num_gpu) without return types