class_docstr: Test clip iqa metric.
class_docstr_tok: ["Test","clip","iqa","metric","."]
docstr: Test class implementation of metric.
docstr_tok: ["Test","class","implementation","of","metric","."]
code: def test_clip_iqa(self, ddp):
      """Test class implementation of metric."""
      self.run_class_metric_test(
          ddp=ddp,
          preds=torch.rand(2, 1, 3, 128, 128),
          target=torch.rand(2, 1, 3, 128, 128),
          metric_class=CLIPTesterClass,
          reference_metric=partial(_reference, reduce=True),
          check_scriptable=False,
          check_state_dict=False,
      )
  
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 1 for calling the TestCLIPIQA obj's underlying member method code with example usage: obj.test_clip_iqa(ddp) without return types