code: def test_shape_assertion(self):
      test_dtype = torch.float32
      image = np.zeros((1, 10, 10, 10))
      boxes = np.array([[7, 8, 9, 10, 12, 13]])
      data = {"image": image, "boxes": boxes, "labels": np.array((1,))}
      data = CastToTyped(keys=["image", "boxes"], dtype=test_dtype)(
          data
      )
      transform_to_mask = BoxToMaskd(
          box_keys="boxes",
          box_mask_keys="box_mask",
          box_ref_image_keys="image",
          label_keys="labels",
          min_fg_label=0,
          ellipse_mask=False,
      )
      with self.assertRaises(ValueError) as context:
          transform_to_mask(data)
      self.assertTrue(
          "Some boxes are larger than the image."
          in str(context.exception)
      )
  
file_path: MONAI/tests/test_box_transform.py
imports: from __future__ import annotations
  import unittest
  from copy import deepcopy
  import numpy
  import torch
  from parameterized import parameterized
  from monai.apps.detection.transforms.box_ops import convert_mask_to_box
  from monai.apps.detection.transforms.dictionary import AffineBoxToImageCoordinated, AffineBoxToWorldCoordinated, BoxToMaskd, ClipBoxToImaged, ConvertBoxModed, FlipBoxd, MaskToBoxd, RandCropBoxByPosNegLabeld, RandFlipBoxd, RandRotateBox90d, RandZoomBoxd, RotateBox90d, ZoomBoxd
  from monai.data.meta_tensor import MetaTensor
  from monai.transforms import CastToTyped, Invertd
  from tests.utils import TEST_NDARRAYS, assert_allclose
label_desc: Use image node_id 4 for calling the TestBoxTransform obj's underlying member method code with example usage: obj.test_shape_assertion() without return types