code: def test_prompt(prompts):
      """Test that the function works with other prompts, and that output is as expected."""
      img = Image.open(_SAMPLE_IMAGE)
      img = PILToTensor()(img)
      img = img.float()[None]
  
      result = clip_image_quality_assessment(
          img, data_range=255, prompts=prompts
      )
      if len(prompts) == 1:
          assert isinstance(result, Tensor)
          assert 0 < result < 1
      else:
          assert isinstance(result, dict)
          for i, (k, v) in enumerate(result.items()):
              assert isinstance(k, str)
              assert (
                  k == prompts[i]
                  if isinstance(prompts[i], str)
                  else "user_defined_" in k
              )
              assert isinstance(v, Tensor)
              assert 0 < v < 1
  
imports: import os
  from functools import partial
  import matplotlib
  import matplotlib.pyplot
  import piq
  import pytest
  import torch
  from PIL import Image
  from torch import Tensor
  from torchmetrics.functional.multimodal.clip_iqa import clip_image_quality_assessment
  from torchmetrics.multimodal.clip_iqa import CLIPImageQualityAssessment
  from torchmetrics.utilities.imports import _PIQ_GREATER_EQUAL_0_8, _TRANSFORMERS_GREATER_EQUAL_4_10
  from torchvision.transforms import PILToTensor
  from unittests.helpers.testers import MetricTester
  from unittests.image import _SAMPLE_IMAGE
  from unittests.text.helpers import skip_on_connection_issues
label_desc: Use image node_id 6 for calling a global function with example usage: test_prompt(prompts) without return types