code: def test__transform_bounding_boxes_clamping(self, mocker):
      batch_size = 3
      canvas_size = (10, 10)
  
      mocker.patch(
          "torchvision.prototype.transforms._geometry.FixedSizeCrop._get_params",
          return_value=dict(
              needs_crop=True,
              top=0,
              left=0,
              height=canvas_size[0],
              width=canvas_size[1],
              is_valid=torch.full((batch_size,), fill_value=True),
              needs_pad=False,
          ),
      )
  
      bounding_boxes = make_bounding_boxes(
          format=BoundingBoxFormat.XYXY,
          canvas_size=canvas_size,
          num_boxes=batch_size,
      )
      mock = mocker.patch(
          "torchvision.prototype.transforms._geometry.F.clamp_bounding_boxes",
          wraps=clamp_bounding_boxes,
      )
  
      transform = transforms.FixedSizeCrop((-1, -1))
      mocker.patch(
          "torchvision.prototype.transforms._geometry.has_any",
          return_value=True,
      )
  
      transform(bounding_boxes)
  
      mock.assert_called_once()
  
imports: import collections.abc
  import re
  import PIL.Image
  import pytest
  import torch
  from common_utils import assert_equal, make_bounding_boxes, make_detection_masks, make_image, make_video
  from torchvision.prototype import transforms, tv_tensors
  from torchvision.transforms.v2._utils import check_type, is_pure_tensor
  from torchvision.transforms.v2.functional import clamp_bounding_boxes, InterpolationMode, pil_to_tensor, to_pil_image
  from torchvision.tv_tensors import BoundingBoxes, BoundingBoxFormat, Image, Mask, Video
  import importlib.machinery
  import importlib.util
  from pathlib import Path
label_desc: Use image node_id 3 for calling the TestFixedSizeCrop obj's underlying member method code with example usage: obj.test__transform_bounding_boxes_clamping(mocker) without return types