try to fix file exists error

Author: voorhs

tests/modules/decision/test_threshold.py

@@ -3,7 +3,6 @@
 
 from autointent.exceptions import MismatchNumClassesError
 from autointent.modules import ThresholdDecision
-from tests.conftest import setup_environment
 
 
 @pytest.mark.parametrize(
@@ -43,17 +42,16 @@ def test_fails_on_wrong_n_classes_fit(multiclass_fit_data):
 
 
 @pytest.mark.parametrize("fit_fixture", ["multiclass_fit_data", "multilabel_fit_data"])
-def test_dump_load(fit_fixture, request):
+def test_dump_load(fit_fixture, request, tmp_path):
     fit_data = request.getfixturevalue(fit_fixture)
     predictor = ThresholdDecision(thresh=0.3)
     predictor.fit(*fit_data)
     predictions = predictor.predict(fit_data[0])
 
-    path = setup_environment() / "threshold_module"
-    predictor.dump(path)
+    predictor.dump(tmp_path)
     del predictor
 
-    predictor = ThresholdDecision.load(path)
+    predictor = ThresholdDecision.load(tmp_path)
 
     assert hasattr(predictor, "thresh")
     assert predictor.thresh is not None

tests/modules/decision/test_tunable.py

@@ -3,7 +3,6 @@
 
 from autointent.exceptions import MismatchNumClassesError
 from autointent.modules import TunableDecision
-from tests.conftest import setup_environment
 
 
 @pytest.mark.parametrize(
@@ -41,17 +40,16 @@ def test_fails_on_wrong_n_classes_predict(multiclass_fit_data):
 
 
 @pytest.mark.parametrize("fit_fixture", ["multiclass_fit_data", "multilabel_fit_data"])
-def test_dump_load(fit_fixture, request):
+def test_dump_load(fit_fixture, request, tmp_path):
     fit_data = request.getfixturevalue(fit_fixture)
     predictor = TunableDecision()
     predictor.fit(*fit_data)
     predictions = predictor.predict(fit_data[0])
 
-    path = setup_environment() / "tunable_module"
-    predictor.dump(path)
+    predictor.dump(tmp_path)
     del predictor
 
-    predictor = TunableDecision.load(path)
+    predictor = TunableDecision.load(tmp_path)
     assert hasattr(predictor, "thresh")
     assert predictor.thresh is not None
     assert isinstance(predictor.thresh, np.ndarray)

tests/modules/embedding/test_retrieval.py

@@ -1,7 +1,6 @@
-import shutil
+from pathlib import Path
 
 from autointent.modules.embedding import RetrievalAimedEmbedding
-from tests.conftest import setup_environment
 
 
 def test_get_assets_returns_correct_artifact():
@@ -10,20 +9,17 @@ def test_get_assets_returns_correct_artifact():
     assert artifact.config.model_name == "sergeyzh/rubert-tiny-turbo"
 
 
-def test_dump_and_load_preserves_model_state():
-    project_dir = setup_environment()
+def test_dump_and_load_preserves_model_state(tmp_path: Path):
     module = RetrievalAimedEmbedding(k=5, embedder_config="sergeyzh/rubert-tiny-turbo")
 
     utterances = ["hello", "goodbye", "hi", "bye", "bye", "hello", "welcome", "hi123", "hiii", "bye-bye", "bye!"]
     labels = [0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1]
     module.fit(utterances, labels)
     predictions = module.predict(utterances)
 
-    module.dump(project_dir)
+    module.dump(tmp_path)
     del module
 
-    loaded_module = RetrievalAimedEmbedding.load(project_dir)
+    loaded_module = RetrievalAimedEmbedding.load(tmp_path)
     predictions_loaded = loaded_module.predict(utterances)
     assert predictions == predictions_loaded
-
-    shutil.rmtree(project_dir)