code: def main():
      # Argument parser
      parser = argparse.ArgumentParser()
  
      parser.add_argument(
          "--flash",
          action="store_true",
          help="whether to use Flash Attention",
      )
  
      opt = parser.parse_args()
  
      # Device
      device = torch.device("cuda:0")
      # Load layers
      layers = list(
          LayerGenerator(
              is_clone_layers=True,
              filter_layers=None,
              dtype=torch.float16,
              device=device,
              is_flash_attention=opt.flash,
          ).load()
      )
  
      # Create `nn.Sequential` model
      model = nn.Sequential(*layers)
  
      # Run [evaluation harness](index.html)
      print(
          run_eval_harness(model, "half_precision", ["lambada"], device)
      )
  
imports: import argparse
  import torch
  from torch import nn
  from labml_nn.neox.evaluation import run_eval_harness
  from labml_nn.neox.model import LayerGenerator
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types