code: def main(argv: Sequence[str]) -> Optional[dev_server.LitServerType]:
      if len(argv) > 1:
          raise app.UsageError("Too many command-line arguments.")
  
      datasets = {"imagenette": imagenette.ImagenetteDataset()}
      # Truncate datasets if --max_examples is set.
      if _MAX_EXAMPLES.value is not None:
          for name in datasets:
              logging.info(
                  "Dataset: '%s' with %d examples",
                  name,
                  len(datasets[name]),
              )
              datasets[name] = datasets[name].slice[
                  : _MAX_EXAMPLES.value
              ]
              logging.info(
                  "  truncated to %d examples", len(datasets[name])
              )
  
      models = {"mobilenet": mobilenet.MobileNet()}
      interpreters = {
          "classification": classification_results.ClassificationInterpreter(),
      } | image_gradient_maps.all_interpreters()
  
      lit_demo = dev_server.Server(
          models,
          datasets,
          interpreters=interpreters,
          generators={},
          layouts={"default": DEMO_LAYOUT},
          **server_flags.get_flags(),
      )
      return lit_demo.serve()
  
file_path: lit/lit_nlp/examples/image_demo.py
imports: from collections.abc import Sequence
  import sys
  from typing import Optional
  from absl import app
  from absl import flags
  from absl import logging
  from lit_nlp import dev_server
  from lit_nlp import server_flags
  from lit_nlp.api import layout
  from lit_nlp.components import classification_results
  from lit_nlp.components import image_gradient_maps
  from lit_nlp.examples.datasets import imagenette
  from lit_nlp.examples.models import mobilenet
label_desc: Use image node_id 2 for calling a global function with example usage: main(argv) and returns: lit_demo