make tests runnable even without sentence-transformers dependency

Author: voorhs

tests/_transformers/test_nli_transformer.py

@@ -5,6 +5,8 @@
 from autointent import Dataset, Ranker
 from autointent.context.data_handler import DataHandler
 
+pytest.importorskip("sentence-transformers")
+
 
 @pytest.fixture
 def data_handler():

tests/embedder/conftest.py

@@ -8,6 +8,8 @@
 # Check if OpenAI API key is available for testing
 openai_available = os.getenv("OPENAI_API_KEY") is not None
 
+pytest.importorskip("sentence-transformers")
+
 
 @pytest.fixture
 def on_windows() -> bool:

tests/modules/scoring/test_bert.py

@@ -8,6 +8,8 @@
 from autointent.context.data_handler import DataHandler
 from autointent.modules import BertScorer
 
+pytest.importorskip("transformers")
+
 
 def test_bert_scorer_dump_load(dataset):
     """Test that BertScorer can be saved and loaded while preserving predictions."""

tests/modules/scoring/test_description_bi.py

@@ -6,6 +6,8 @@
 from autointent.context.data_handler import DataHandler
 from autointent.modules import BiEncoderDescriptionScorer
 
+pytest.importorskip("sentence-transformers")
+
 
 @pytest.mark.parametrize(
     ("expected_prediction", "multilabel"),

tests/modules/scoring/test_description_cross.py

@@ -6,6 +6,8 @@
 from autointent.context.data_handler import DataHandler
 from autointent.modules import CrossEncoderDescriptionScorer
 
+pytest.importorskip("sentence-transformers")
+
 
 @pytest.mark.parametrize(
     ("expected_prediction", "multilabel"),

tests/modules/scoring/test_dnnc.py

@@ -6,6 +6,8 @@
 from autointent.context.data_handler import DataHandler
 from autointent.modules import DNNCScorer
 
+pytest.importorskip("sentence-transformers")
+
 
 @pytest.mark.parametrize(("train_head", "pred_score"), [(True, 1)])
 def test_base_dnnc(dataset, train_head, pred_score):

tests/modules/scoring/test_rerank_scorer.py

@@ -1,10 +1,13 @@
 import tempfile
 
 import numpy as np
+import pytest
 
 from autointent.context.data_handler import DataHandler
 from autointent.modules import RerankScorer
 
+pytest.importorskip("sentence-transformers")
+
 
 def test_base_rerank_scorer(dataset):
     data_handler = DataHandler(dataset)

tests/modules/test_dumper.py

@@ -5,7 +5,6 @@
 import pytest
 import torch
 from sklearn.linear_model import LogisticRegression
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
 
 from autointent import Embedder, Ranker, VectorIndex
 from autointent._dump_tools import Dumper
@@ -39,6 +38,8 @@ def check_attributes(self):
 
 class TestTransformers:
     def init_attributes(self):
+        from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
         self.tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
         self._tokenizer_predictions = np.array(self.tokenizer(["hello", "world"]).input_ids)
         self.transformer = AutoModelForSequenceClassification.from_pretrained("bert-base-uncased")
@@ -143,16 +144,55 @@ def check_attributes(self):
         assert not self.pydantic_model.tokenizer_config.truncation
 
 
+def _st_is_installed() -> bool:
+    try:
+        import sentence_transformers  # noqa: F401
+    except ImportError:
+        return False
+    else:
+        return True
+
+
+def _transformers_is_installed() -> bool:
+    try:
+        import transformers  # noqa: F401
+    except ImportError:
+        return False
+    else:
+        return True
+
+
 @pytest.mark.parametrize(
     "test_class",
     [
         TestSimpleAttributes,
         TestTags,
-        TestTransformers,
+        pytest.param(
+            TestTransformers,
+            marks=pytest.mark.skipif(
+                not _transformers_is_installed(),
+                reason="need transformers dependency",
+            ),
+            id="transformer",
+        ),
         TestVectorIndex,
-        TestEmbedder,
+        pytest.param(
+            TestEmbedder,
+            marks=pytest.mark.skipif(
+                not _st_is_installed(),
+                reason="need sentence-transformers dependency",
+            ),
+            id="embedder",
+        ),
         TestSklearnEstimator,
-        TestRanker,
+        pytest.param(
+            TestRanker,
+            marks=pytest.mark.skipif(
+                not _st_is_installed(),
+                reason="need sentence-transformers dependency",
+            ),
+            id="ranker",
+        ),
         TestCrossEncoderConfig,
     ],
 )