Fix incorrect CLIP-IQA type hints

src/torchmetrics/functional/multimodal/clip_iqa.py

@@ -89,7 +89,9 @@ def _get_clip_iqa_model_and_processor(
     return _get_clip_model_and_processor(model_name_or_path)
 
 
-def _clip_iqa_format_prompts(prompts: tuple[Union[str, tuple[str, str]]] = ("quality",)) -> tuple[list[str], list[str]]:
+def _clip_iqa_format_prompts(
+    prompts: tuple[Union[str, tuple[str, str]], ...] = ("quality",),
+) -> tuple[list[str], list[str]]:
     """Converts the provided keywords into a list of prompts for the model to calculate the anchor vectors.
 
     Args:
@@ -225,7 +227,7 @@ def clip_image_quality_assessment(
         "openai/clip-vit-large-patch14",
     ] = "clip_iqa",
     data_range: float = 1.0,
-    prompts: tuple[Union[str, tuple[str, str]]] = ("quality",),
+    prompts: tuple[Union[str, tuple[str, str]], ...] = ("quality",),
 ) -> Union[Tensor, dict[str, Tensor]]:
     """Calculates `CLIP-IQA`_, that can be used to measure the visual content of images.
 
@@ -329,3 +331,20 @@ def clip_image_quality_assessment(
         anchors = _clip_iqa_get_anchor_vectors(model_name_or_path, model, processor, prompts_list, device)
         img_features = _clip_iqa_update(model_name_or_path, images, model, processor, data_range, device)
         return _clip_iqa_compute(img_features, anchors, prompts_names)
+
+
+if TYPE_CHECKING:
+    from functools import partial
+    from typing import Any, cast
+
+    images = cast(Any, None)
+
+    f = partial(clip_image_quality_assessment, images=images)
+    f(prompts=("colorfullness",))
+    f(
+        prompts=("quality", "brightness", "noisiness"),
+    )
+    f(
+        prompts=("quality", "brightness", "noisiness", "colorfullness"),
+    )
+    f(prompts=(("Photo of a cat", "Photo of a dog"), "quality", ("Colorful photo", "Black and white photo")))

src/torchmetrics/multimodal/clip_iqa.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 from collections.abc import Sequence
-from typing import Any, List, Literal, Optional, Union
+from typing import TYPE_CHECKING, Any, List, Literal, Optional, Union
 
 import torch
 from torch import Tensor
@@ -179,7 +179,7 @@ def __init__(
             "openai/clip-vit-large-patch14",
         ] = "clip_iqa",
         data_range: float = 1.0,
-        prompts: tuple[Union[str, tuple[str, str]]] = ("quality",),
+        prompts: tuple[Union[str, tuple[str, str]], ...] = ("quality",),
         **kwargs: Any,
     ) -> None:
         super().__init__(**kwargs)
@@ -259,3 +259,15 @@ def plot(self, val: Union[Tensor, Sequence[Tensor], None] = None, ax: Optional[_
 
         """
         return self._plot(val, ax)
+
+
+if TYPE_CHECKING:
+    f = CLIPImageQualityAssessment
+    f(prompts=("colorfullness",))
+    f(
+        prompts=("quality", "brightness", "noisiness"),
+    )
+    f(
+        prompts=("quality", "brightness", "noisiness", "colorfullness"),
+    )
+    f(prompts=(("Photo of a cat", "Photo of a dog"), "quality", ("Colorful photo", "Black and white photo")))