Merge branch 'main' into random_seed

sede-open · Sep 20, 2024 · af0ffaa · af0ffaa
2 parents 494fbd7 + 43d0d94
commit af0ffaa
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Showing 4 changed files with 10 additions and 6 deletions.
diff --git a/.git-blame-ignore-revs b/.git-blame-ignore-revs
@@ -1,4 +1,6 @@
-# Double quote -> single quote
+# Prettier: double quote -> single quote
+6a5aaf4b93507072d40dcd78114893362c4eaf6e
+# Ruff: double quote -> single quote
 b09122f3e4a9cb422f6747bf33eca02993f67549
 # Prettier
 bd9c75798eede1a4b7d7ecd6203179d3cb5e54dd

diff --git a/.github/workflows/tutorials.yaml b/.github/workflows/tutorials.yaml
@@ -33,7 +33,7 @@ jobs:
       - name: Install pip dependencies
         if: steps.cache.outputs.cache-hit != 'true'
         run: |
-          pip install -r requirements/required.txt -r requirements/docs.txt -r requirements/tests.txt planetary_computer pystac
+          pip install -r requirements/required.txt -r requirements/docs.txt -r requirements/tests.txt planetary_computer pystac .
           pip cache purge
       - name: List pip dependencies
         run: pip list

diff --git a/tests/conf/landcoverai100.yaml b/tests/conf/landcoverai100.yaml
@@ -1,9 +1,9 @@
 model:
   class_path: SemanticSegmentationTask
   init_args:
-    loss: "ce"
-    model: "unet"
-    backbone: "resnet18"
+    loss: 'ce'
+    model: 'unet'
+    backbone: 'resnet18'
     in_channels: 3
     num_classes: 5
     num_filters: 1
@@ -13,4 +13,4 @@ data:
   init_args:
     batch_size: 1
   dict_kwargs:
-    root: "tests/data/landcoverai"
+    root: 'tests/data/landcoverai'
diff --git a/torchgeo/datamodules/geo.py b/torchgeo/datamodules/geo.py
@@ -286,6 +286,7 @@ def _dataloader_factory(self, split: str) -> DataLoader[dict[str, Tensor]]:
             batch_sampler=batch_sampler,
             num_workers=self.num_workers,
             collate_fn=self.collate_fn,
+            persistent_workers=self.num_workers > 0,
         )
 
     def train_dataloader(self) -> DataLoader[dict[str, Tensor]]:
@@ -429,6 +430,7 @@ def _dataloader_factory(self, split: str) -> DataLoader[dict[str, Tensor]]:
             shuffle=split == 'train',
             num_workers=self.num_workers,
             collate_fn=self.collate_fn,
+            persistent_workers=self.num_workers > 0,
         )
 
     def train_dataloader(self) -> DataLoader[dict[str, Tensor]]: