code: def test_segmentation_data_bad_batch_to_label_implementation():
      # Arrange
      coco_segmentation = segmentation_coco.load_dataset(
          object_type="DataLoader"
      )
      loader_empty_batch = replace_collate_fn_dataloader(
          coco_segmentation, lambda x: {"labels": []}
      )
      loader_classification_shape = replace_collate_fn_dataloader(
          coco_segmentation, lambda x: {"labels": [8]}
      )
      loader_good_shape = replace_collate_fn_dataloader(
          coco_segmentation, lambda x: {"labels": [np.ones((3, 3))]}
      )
  
      # Assert
      assert_that(
          calling(VisionData).with_args(
              loader_empty_batch, TaskType.SEMANTIC_SEGMENTATION.value
          ),
          raises(
              ValidationError,
              "The batch labels must be a non empty iterable.",
          ),
      )
      assert_that(
          calling(VisionData).with_args(
              loader_classification_shape,
              TaskType.SEMANTIC_SEGMENTATION.value,
          ),
          raises(
              ValidationError,
              "label for semantic_segmentation per image must be a multi dimensional array.",
          ),
      )
      VisionData(
          loader_good_shape, TaskType.SEMANTIC_SEGMENTATION.value
      )
  
imports: import numpy
  import pytest
  import torch
  from hamcrest import assert_that, calling, equal_to, has_length, is_not, raises
  from torch.utils.data import DataLoader
  from deepchecks.core.errors import DatasetValidationError, ValidationError
  from deepchecks.vision.datasets.classification.mnist_torch import IterableTorchMnistDataset, collate_without_model
  from deepchecks.vision.datasets.detection import coco_torch
  from deepchecks.vision.datasets.segmentation import segmentation_coco
  from deepchecks.vision.utils.test_utils import replace_collate_fn_dataloader
  from deepchecks.vision.vision_data import TaskType, VisionData
  from deepchecks.vision.vision_data.utils import validate_vision_data_compatibility
  from tests.vision.conftest import run_update_loop
label_desc: Use image node_id 13 for calling a global function with example usage: test_segmentation_data_bad_batch_to_label_implementation() without return types