code: def test__get_params(self, mocker):
      crop_size = (7, 7)
      batch_shape = (10,)
      canvas_size = (11, 5)
  
      transform = transforms.FixedSizeCrop(size=crop_size)
  
      flat_inputs = [
          make_image(size=canvas_size, color_space="RGB"),
          make_bounding_boxes(
              format=BoundingBoxFormat.XYXY,
              canvas_size=canvas_size,
              num_boxes=batch_shape[0],
          ),
      ]
      params = transform._get_params(flat_inputs)
  
      assert params["needs_crop"]
      assert params["height"] <= crop_size[0]
      assert params["width"] <= crop_size[1]
  
      assert (
          isinstance(params["is_valid"], torch.Tensor)
          and params["is_valid"].dtype is torch.bool
          and params["is_valid"].shape == batch_shape
      )
  
      assert params["needs_pad"]
      assert any(pad > 0 for pad in params["padding"])
  
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 1 for calling the TestFixedSizeCrop obj's underlying member method code with example usage: obj.test__get_params(mocker) without return types