Run github actiosns CI tests on Windows, Mac and Linux (#267)

Add CI for windows and mac --------- Co-authored-by: Constantin Pape <[email protected]>
computational-cell-analytics · Nov 18, 2023 · 5546343 · 5546343
1 parent d427e9f
commit 5546343
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Showing 6 changed files with 10 additions and 4 deletions.
diff --git a/.github/workflows/test.yaml b/.github/workflows/test.yaml
@@ -19,7 +19,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        os: [ubuntu-latest]
+        os: [ubuntu-latest, windows-latest, macos-latest]
         python-version: ["3.10"]
 
     steps:

diff --git a/micro_sam/util.py b/micro_sam/util.py
@@ -140,6 +140,10 @@ def _get_checkpoint(model_type, checkpoint_path=None):
 
 
 def _get_default_device():
+    # check that we're in CI and use the CPU if we are
+    # otherwise the tests may run out of memory on MAC if MPS is used.
+    if os.getenv("GITHUB_ACTIONS") == "true":
+        return "cpu"
     # Use cuda enabled gpu if it's available.
     if torch.cuda.is_available():
         device = "cuda"

diff --git a/requirements-dev.txt b/requirements-dev.txt
@@ -1,6 +1,5 @@
 coverage
 line-profiler
-memray
 napari[all]
 pdoc
 pytest

diff --git a/test/test_gui.py b/test/test_gui.py
@@ -1,3 +1,5 @@
+import platform
+
 import numpy as np
 import pytest
 
@@ -20,6 +22,7 @@ def _check_layer_initialization(viewer):
 
 
 @pytest.mark.gui
+@pytest.mark.skipif(platform.system() == "Windows", reason="Gui test is not working on windows.")
 def test_annotator_2d(make_napari_viewer_proxy, tmp_path):
     """Integration test for annotator_2d widget with automatic mask generation.
 

diff --git a/test/test_instance_segmentation.py b/test/test_instance_segmentation.py
@@ -39,7 +39,7 @@ def write_object(center, radius):
 
     @staticmethod
     def _get_model(image, model_type):
-        predictor = util.get_sam_model(model_type=model_type)
+        predictor = util.get_sam_model(model_type=model_type, device=util._get_device(None))
         image_embeddings = util.precompute_image_embeddings(predictor, image)
         return predictor, image_embeddings
 

diff --git a/test/test_prompt_based_segmentation.py b/test/test_prompt_based_segmentation.py
@@ -20,7 +20,7 @@ def _get_input(shape=(256, 256)):
 
     @staticmethod
     def _get_model(image, model_type):
-        predictor = util.get_sam_model(model_type=model_type)
+        predictor = util.get_sam_model(model_type=model_type, device=util._get_device(None))
         image_embeddings = util.precompute_image_embeddings(predictor, image)
         util.set_precomputed(predictor, image_embeddings)
         return predictor