Fix device and dtype for LPIPS functional metric

CHANGELOG.md

@@ -57,6 +57,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Fixed numerical stability issue in `UniversalImageQualityIndex` metric ([#2222](https://github.com/Lightning-AI/torchmetrics/pull/2222))
 
 
+-  Fix device and dtype for `LearnedPerceptualImagePatchSimilarity` functional metric ([#2234](https://github.com/Lightning-AI/torchmetrics/pull/2234))
+
+
 ## [1.2.0] - 2023-09-22
 
 ### Added

src/torchmetrics/functional/image/lpips.py

@@ -426,6 +426,6 @@ def learned_perceptual_image_patch_similarity(
         tensor(0.1008, grad_fn=<DivBackward0>)
 
     """
-    net = _NoTrainLpips(net=net_type)
+    net = _NoTrainLpips(net=net_type).to(device=img1.device, dtype=img1.dtype)
     loss, total = _lpips_update(img1, img2, net, normalize)
     return _lpips_compute(loss.sum(), total, reduction)

tests/unittests/image/test_lpips.py

@@ -18,6 +18,7 @@
 import torch
 from lpips import LPIPS as LPIPS_reference  # noqa: N811
 from torch import Tensor
+from torchmetrics.functional.image.lpips import learned_perceptual_image_patch_similarity
 from torchmetrics.image.lpip import LearnedPerceptualImagePatchSimilarity
 from torchmetrics.utilities.imports import _LPIPS_AVAILABLE
 
@@ -68,6 +69,16 @@ def test_lpips(self, net_type, ddp):
             metric_args={"net_type": net_type},
         )
 
+    def test_lpips_functional(self):
+        """Test functional implementation of metric."""
+        self.run_functional_metric_test(
+            preds=_inputs.img1,
+            target=_inputs.img2,
+            metric_functional=learned_perceptual_image_patch_similarity,
+            reference_metric=partial(_compare_fn, net_type="alex"),
+            metric_args={"net_type": "alex"},
+        )
+
     def test_lpips_differentiability(self):
         """Test the differentiability of the metric, according to its `is_differentiable` attribute."""
         self.run_differentiability_test(