class_docstr: Test class for `CLIPScore` metric.
class_docstr_tok: ["Test","class","for","`","CLIPScore","`","metric","."]
docstr: Test the plot method of CLIPScore separately in this file due to the skipping conditions.
docstr_tok: ["Test","the","plot","method","of","CLIPScore","separately","in","this","file","due","to","the","skipping","conditions","."]
code: def test_plot_method(self, inputs, model_name_or_path):
      """Test the plot method of CLIPScore separately in this file due to the skipping conditions."""
      metric = CLIPScore(model_name_or_path=model_name_or_path)
      preds, target = inputs
      metric.update(preds[0], target[0])
      fig, ax = metric.plot()
      assert isinstance(fig, plt.Figure)
      assert isinstance(ax, matplotlib.axes.Axes)
  
imports: from functools import partial
  from typing import List, NamedTuple
  import matplotlib
  import matplotlib.pyplot
  import pytest
  import torch
  from torch import Tensor
  from torchmetrics.functional.multimodal.clip_score import clip_score
  from torchmetrics.multimodal.clip_score import CLIPScore
  from torchmetrics.utilities.imports import _TRANSFORMERS_GREATER_EQUAL_4_10
  from transformers import CLIPModel
  from transformers import CLIPProcessor
  from unittests.helpers import seed_all
  from unittests.helpers.testers import MetricTester
  from unittests.text.helpers import skip_on_connection_issues
label_desc: Use image node_id 6 for calling the TestCLIPScore obj's underlying member method code with example usage: obj.test_plot_method(inputs, model_name_or_path) without return types