code: def test_annotate_not_all(backend_config, setup):
      # check that we can load partially annotated data
      label_type = "classification"
      dataset, anno_key, label_field, labels = setup
      label_field += f"-{label_type}"
      dataset.annotate(
          anno_key,
          label_field=label_field,
          project_name=f"labelstudio_{label_type}_tests",
          label_type=label_type,
          classes=labels if label_type != "scalar" else None,
          backend="labelstudio",
          **backend_config,
      )
  
      # create dummy prediction and convert to annotations
      dummy_predictions = _generate_dummy_predictions(
          label_type, labels, len(dataset) - 1
      )
      _add_dummy_annotations(
          dataset, anno_key, dummy_predictions, backend_config
      )
  
      dataset.load_annotations(
          anno_key, cleanup=False, **backend_config
      )
  
      labelled = dataset.exists(label_field)
      assert len(labelled) == len(dummy_predictions)
      assert len(labelled) == len(dataset) - 1
  
imports: import os
  import random
  import numpy
  import pytest
  import fiftyone
  import fiftyone.zoo
  import fiftyone.utils.labelstudio
  import fiftyone.core.labels
label_desc: Use image node_id 9 for calling a global function with example usage: test_annotate_not_all(backend_config, setup) without return types