Fix incompatibility errors raises()

Different in hydra >= 1.1.2

tests/integration/pipelines/test_rank_and_validate.py

@@ -3,11 +3,6 @@
 import numpy as np
 import pandas as pd
 import pytest
-from hydra.core.config_store import ConfigStore
-from hydra.utils import instantiate
-from omegaconf import DictConfig, open_dict
-from sklearn.base import BaseEstimator
-
 from fseval.config import (
     CrossValidatorConfig,
     DatasetConfig,
@@ -16,8 +11,13 @@
     ResampleConfig,
 )
 from fseval.pipeline.dataset import Dataset, DatasetLoader
-from fseval.types import AbstractAdapter, IncompatibilityError, Task
+from fseval.types import AbstractAdapter, Task
 from fseval.utils.hydra_utils import get_config
+from hydra.core.config_store import ConfigStore
+from hydra.errors import InstantiationException
+from hydra.utils import instantiate
+from omegaconf import DictConfig, open_dict
+from sklearn.base import BaseEstimator
 
 cs = ConfigStore.instance()
 
@@ -206,7 +206,7 @@ def test_with_ranker_gt_no_importances_substitution(cfg: PipelineConfig):
 
 
 def test_validator_incompatibility_check(cfg: PipelineConfig):
-    with pytest.raises(IncompatibilityError):
+    with pytest.raises(InstantiationException):
         cfg.dataset.n = 5
         cfg.dataset.p = 5
         cfg.dataset.multioutput = False
@@ -215,7 +215,7 @@ def test_validator_incompatibility_check(cfg: PipelineConfig):
 
 
 def test_ranker_incompatibility_check(cfg: PipelineConfig):
-    with pytest.raises(IncompatibilityError):
+    with pytest.raises(InstantiationException):
         cfg.dataset.n = 5
         cfg.dataset.p = 5
         cfg.dataset.multioutput = False

tests/integration/test_main.py

@@ -7,6 +7,7 @@
 from fseval.types import IncompatibilityError
 from fseval.utils.hydra_utils import get_config
 from hydra.conf import ConfigStore
+from hydra.errors import InstantiationException
 
 
 @pytest.fixture
@@ -66,7 +67,7 @@ def test_pipeline_incompatibility(incompatible_cfg: PipelineConfig):
     """Pipeline should throw IncompatibilityError when trying to run a classification
     method on a regression dataset."""
 
-    with pytest.raises(IncompatibilityError):
+    with pytest.raises(InstantiationException):
         run_pipeline(incompatible_cfg, raise_incompatibility_errors=True)
 
 

tests/unit/pipeline/test_estimator.py

@@ -3,13 +3,14 @@
 
 import pytest
 from hydra.utils import instantiate
+from hydra.errors import InstantiationException
 from omegaconf import OmegaConf
 from sklearn.base import BaseEstimator
 
 from fseval.config import EstimatorConfig
 from fseval.pipeline.estimator import Estimator
 from fseval.storage.local import LocalStorage
-from fseval.types import CacheUsage, IncompatibilityError, Task
+from fseval.types import CacheUsage, Task
 
 
 @pytest.fixture
@@ -79,23 +80,23 @@ def test_incompatibility(estimator_cfg: EstimatorConfig):
     # classification estimator, but regression task
     estimator_cfg._estimator_type = "classifier"
     estimator_cfg.task = Task.regression
-    with pytest.raises(IncompatibilityError):
+    with pytest.raises(InstantiationException):
         instantiate(estimator_cfg)
 
     # multioutput, but estimator does not support it (`multioutput=False`)
     estimator_cfg._estimator_type = "classifier"
     estimator_cfg.task = Task.classification
     estimator_cfg.multioutput = False
     estimator_cfg.is_multioutput_dataset = True
-    with pytest.raises(IncompatibilityError):
+    with pytest.raises(InstantiationException):
         instantiate(estimator_cfg)
 
     # multioutput only, but
     estimator_cfg._estimator_type = "classifier"
     estimator_cfg.task = Task.classification
     estimator_cfg.multioutput_only = True
     estimator_cfg.is_multioutput_dataset = False
-    with pytest.raises(IncompatibilityError):
+    with pytest.raises(InstantiationException):
         instantiate(estimator_cfg)