Check if DI is installed for tests and CI

.github/workflows/deepinterpolation.yml

@@ -23,15 +23,28 @@ jobs:
       - uses: actions/setup-python@v4
         with:
           python-version: '3.9'
+      - name: Get changed files
+        id: changed-files
+        uses: tj-actions/changed-files@v35
+      - name: Deepinteprolation changes
+        id: modules-changed
+        run: |
+          for file in ${{ steps.changed-files.outputs.all_changed_files }}; do
+            if [[ $file == *"/deepinterpolation/"* ]]; then
+              echo "DeepInterpolation changed"
+              echo "DEEPINTERPOLATION_CHANGED=true" >> $GITHUB_OUTPUT
+            fi
       - name: Install dependencies
+        if: ${{ steps.modules-changed.outputs.DEEPINTERPOLATION_CHANGED == 'true' }}
         run: |
           python -m pip install -U pip  # Official recommended way
           # install deepinteprolation
           pip install tensorflow==2.7.0
           pip install deepinterpolation@git+https://github.com/AllenInstitute/deepinterpolation.git
           pip install protobuf==3.20.*
           pip install -e .[full,test_core]
-      - name: Test core with pytest
+      - name: Test DeepInterpolation with pytest
+        if: ${{ steps.modules-changed.outputs.DEEPINTERPOLATION_CHANGED == 'true' }}
         run: |
           pytest -v src/spikeinterface/preprocessing/deepinterpolation
         shell: bash  # Necessary for pipeline to work on windows

conftest.py

@@ -11,7 +11,7 @@
 mark_names = ["core", "extractors", "preprocessing", "postprocessing",
               "sorters_external", "sorters_internal", "sorters",
               "qualitymetrics", "comparison", "curation",
-              "widgets", "exporters", "sortingcomponents", "deepinterpolation"]
+              "widgets", "exporters", "sortingcomponents"]
 
 
 # define global test folder

pyproject.toml

@@ -176,7 +176,6 @@ markers = [
     "exporters",
     "widgets",
     "sortingcomponents",
-    "deepinterpolation",
     "streaming_extractors: extractors that require streaming such as ross and fsspec",
 ]
 filterwarnings =[

src/spikeinterface/preprocessing/deepinterpolation/tests/test_deepinterpolation.py

@@ -11,6 +11,15 @@
 from spikeinterface.preprocessing.deepinterpolation import train_deepinterpolation, deepinterpolate
 
 
+try:
+    import tensorflow
+    import deepinterpolation
+
+    HAVE_DEEPINTERPOLATION = True
+except ImportError:
+    HAVE_DEEPINTERPOLATION = False
+
+
 if hasattr(pytest, "global_test_folder"):
     cache_folder = pytest.global_test_folder / "deepinterpolation"
 else:
@@ -37,6 +46,7 @@ def recording_and_shape_fixture():
     return recording_and_shape()
 
 
+@pytest.mark.skipif(not HAVE_DEEPINTERPOLATION, reason="requires deepinterpolation")
 def test_deepinterpolation_generator_borders(recording_and_shape_fixture):
     """Test that the generator avoids borders in multi-segment and recording lists cases"""
     from spikeinterface.preprocessing.deepinterpolation.generators import SpikeInterfaceRecordingGenerator
@@ -58,6 +68,7 @@ def test_deepinterpolation_generator_borders(recording_and_shape_fixture):
     assert len(gen_multi_list.exclude_intervals) == 2 * len(recording_multi_list) + 2
 
 
+@pytest.mark.skipif(not HAVE_DEEPINTERPOLATION, reason="requires deepinterpolation")
 def test_deepinterpolation_training(recording_and_shape_fixture):
     recording, desired_shape = recording_and_shape_fixture
 
@@ -82,6 +93,7 @@ def test_deepinterpolation_training(recording_and_shape_fixture):
     print(model_path)
 
 
+@pytest.mark.skipif(not HAVE_DEEPINTERPOLATION, reason="requires deepinterpolation")
 @pytest.mark.dependency(depends=["test_deepinterpolation_training"])
 def test_deepinterpolation_transfer(recording_and_shape_fixture, tmp_path):
     recording, desired_shape = recording_and_shape_fixture
@@ -109,6 +121,7 @@ def test_deepinterpolation_transfer(recording_and_shape_fixture, tmp_path):
     print(model_path)
 
 
+@pytest.mark.skipif(not HAVE_DEEPINTERPOLATION, reason="requires deepinterpolation")
 @pytest.mark.dependency(depends=["test_deepinterpolation_training"])
 def test_deepinterpolation_inference(recording_and_shape_fixture):
     recording, desired_shape = recording_and_shape_fixture