add doctest for same modality

src/torchmetrics/functional/multimodal/clip_score.py

@@ -264,6 +264,29 @@ def clip_score(
         >>> score.detach()
         tensor(24.4255)
 
+    Example:
+        >>> import torch
+        >>> from torchmetrics.functional.multimodal import clip_score
+        >>> torch.manual_seed(42)
+        >>> torch.cuda.manual_seed_all(42)
+        >>> score = clip_score(
+        ...     torch.randint(255, (3, 224, 224)),
+        ...     torch.randint(255, (3, 224, 224)),
+        ...     "openai/clip-vit-base-patch16"
+        ... )
+        >>> score.detach()
+        tensor(99.3556)
+
+    Example:
+        >>> from torchmetrics.functional.multimodal import clip_score
+        >>> score = clip_score(
+        ...     "28-year-old chef found dead in San Francisco mall",
+        ...     "A 28-year-old chef who recently moved to San Francisco was found dead.",
+        ...     "openai/clip-vit-base-patch16"
+        ... )
+        >>> score.detach()
+        tensor(91.3950)
+
     """
     model, processor = _get_clip_model_and_processor(model_name_or_path)
     score, _ = _clip_score_update(source, target, model, processor)

src/torchmetrics/multimodal/clip_score.py

@@ -108,6 +108,24 @@ class CLIPScore(Metric):
         >>> score.detach().round()
         tensor(25.)
 
+    Example:
+        >>> import torch
+        >>> from torchmetrics.multimodal.clip_score import CLIPScore
+        >>> torch.manual_seed(42)
+        >>> torch.cuda.manual_seed_all(42)
+        >>> metric = CLIPScore(model_name_or_path="openai/clip-vit-base-patch16")
+        >>> score = metric(torch.randint(255, (3, 224, 224)),torch.randint(255, (3, 224, 224)))
+        >>> score.detach().round()
+        tensor(100.)
+
+    Example:
+        >>> from torchmetrics.multimodal.clip_score import CLIPScore
+        >>> metric = CLIPScore(model_name_or_path="openai/clip-vit-base-patch16")
+        >>> score = metric("28-year-old chef found dead in San Francisco mall",
+        ...               "A 28-year-old chef who recently moved to San Francisco was found dead.")
+        >>> score.detach().round()
+        tensor(91.)
+
     """
 
     is_differentiable: bool = False