code: def train_loop(args, model, optimizer, step, num_steps):
      for i in range(num_steps):
          input_batch = torch.randn(
              [args.batch_size, args.input_features]
          ).cuda()
          target_batch = torch.randn(
              [args.batch_size, args.output_features]
          ).cuda()
          step = train_step(
              args, model, optimizer, input_batch, target_batch, step
          )
      return step
  
file_path: apex/apex/contrib/sparsity/test/checkpointing_test_reference.py
imports: from collections import OrderedDict
  import torch
  from apex.optimizers import FusedAdam
  from apex.contrib.sparsity import ASP
label_desc: Use image node_id 3 for calling a global function with example usage: train_loop(args, model, optimizer, step, num_steps) and returns: step