Fix compatibility with TM 10

CHANGELOG.md

@@ -22,6 +22,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Fixed
 
+- Fixed compatibility with `torchmetrics==1.10.0` ([#1469](https://github.com/Lightning-AI/lightning-flash/pull/1469))
+
 
 ## [0.8.0] - 2022-09-02
 

flash/core/utilities/imports.py

@@ -90,6 +90,7 @@ class Image:
     _PANDAS_GREATER_EQUAL_1_3_0 = compare_version("pandas", operator.ge, "1.3.0")
     _ICEVISION_GREATER_EQUAL_0_11_0 = compare_version("icevision", operator.ge, "0.11.0")
     _TM_GREATER_EQUAL_0_7_0 = compare_version("torchmetrics", operator.ge, "0.7.0")
+    _TM_GREATER_EQUAL_0_10_0 = compare_version("torchmetrics", operator.ge, "0.10.0")
     _BAAL_GREATER_EQUAL_1_5_2 = compare_version("baal", operator.ge, "1.5.2")
 
 _TEXT_AVAILABLE = all(

flash/image/segmentation/model.py

@@ -25,6 +25,7 @@
 from flash.core.serve import Composition
 from flash.core.utilities.imports import (
     _TM_GREATER_EQUAL_0_7_0,
+    _TM_GREATER_EQUAL_0_10_0,
     _TORCHVISION_AVAILABLE,
     _TORCHVISION_GREATER_EQUAL_0_9,
     requires,
@@ -55,7 +56,9 @@ class InterpolationMode:
             NEAREST = "nearest"
 
 
-if _TM_GREATER_EQUAL_0_7_0:
+if _TM_GREATER_EQUAL_0_10_0:
+    from torchmetrics.classification import MulticlassJaccardIndex as JaccardIndex
+elif _TM_GREATER_EQUAL_0_7_0:
     from torchmetrics import JaccardIndex
 else:
     from torchmetrics import IoU as JaccardIndex

flash/pointcloud/segmentation/model.py

@@ -24,7 +24,7 @@
 from flash.core.data.io.input_transform import InputTransform
 from flash.core.data.utilities.collate import wrap_collate
 from flash.core.registry import FlashRegistry
-from flash.core.utilities.imports import _POINTCLOUD_AVAILABLE, _TM_GREATER_EQUAL_0_7_0
+from flash.core.utilities.imports import _POINTCLOUD_AVAILABLE, _TM_GREATER_EQUAL_0_7_0, _TM_GREATER_EQUAL_0_10_0
 from flash.core.utilities.stability import beta
 from flash.core.utilities.types import LOSS_FN_TYPE, LR_SCHEDULER_TYPE, METRICS_TYPE, OPTIMIZER_TYPE
 from flash.pointcloud.segmentation.backbones import POINTCLOUD_SEGMENTATION_BACKBONES
@@ -33,7 +33,9 @@
     from open3d._ml3d.torch.modules.losses.semseg_loss import filter_valid_label
     from open3d.ml.torch.dataloaders import TorchDataloader
 
-if _TM_GREATER_EQUAL_0_7_0:
+if _TM_GREATER_EQUAL_0_10_0:
+    from torchmetrics.classification import MulticlassJaccardIndex as JaccardIndex
+elif _TM_GREATER_EQUAL_0_7_0:
     from torchmetrics import JaccardIndex
 else:
     from torchmetrics import IoU as JaccardIndex

flash_examples/serve/semantic_segmentation/inference_server.py

@@ -15,7 +15,7 @@
 from flash.image.segmentation.output import SegmentationLabelsOutput
 
 model = SemanticSegmentation.load_from_checkpoint(
-    "https://flash-weights.s3.amazonaws.com/0.8.0/semantic_segmentation_model.pt"
+    "https://flash-weights.s3.amazonaws.com/0.9.0/semantic_segmentation_model.pt"
 )
 model.output = SegmentationLabelsOutput(visualize=False)
 model.serve()

tests/core/test_model.py

@@ -220,7 +220,7 @@ def test_classification_task_trainer_predict(tmpdir):
         ),
         pytest.param(
             SemanticSegmentation,
-            "0.8.0/semantic_segmentation_model.pt",
+            "0.9.0/semantic_segmentation_model.pt",
             marks=pytest.mark.skipif(
                 not _IMAGE_TESTING,
                 reason="image packages aren't installed",