apply ruff auto-fixes

Author: stes

cebra/data/single_session.py

@@ -370,6 +370,11 @@ def __post_init__(self):
 
         self._init_behavior_distribution()
         self._init_time_distribution()
+        
+        if self.conditional != "time_delta":
+            raise NotImplementedError(
+                "Hybrid training is currently only implemented using the ``time_delta`` "
+                "continual distribution.")
 
     def _init_behavior_distribution(self):
         if self.conditional == "time":

cebra/datasets/gaussian_mixture.py

@@ -27,7 +27,6 @@
 
 import cebra.data
 import cebra.io
-from cebra.datasets import get_datapath
 from cebra.datasets import parametrize
 from cebra.datasets import register
 

cebra/solver/base.py

@@ -33,15 +33,14 @@
 import abc
 import os
 import warnings
-from typing import Callable, Dict, Iterable, List, Literal, Optional, Union
+from typing import Callable, Dict, Iterable, List, Literal, Optional, Tuple, Union
 
 import literate_dataclasses as dataclasses
 import numpy.typing as npt
 import numpy as np
 import numpy.typing as npt
 import torch
 import torch.nn.functional as F
-import tqdm
 from torch.utils.data import DataLoader
 from torch.utils.data import Dataset
 

tests/test_solver.py

@@ -20,7 +20,6 @@
 # limitations under the License.
 #
 import copy
-import itertools
 import tempfile
 
 import numpy as np
@@ -715,8 +714,8 @@ def create_model(model_name, input_dimension):
 
 @pytest.mark.parametrize(
     "data_name, model_name ,session_id, loader_initfunc, solver_initfunc",
-    single_session_tests_select_model +
-    single_session_hybrid_tests_select_model)
+    single_session_tests_select_model + single_session_hybrid_tests_select_model
+)
 def test_select_model_single_session(data_name, model_name, session_id,
                                      loader_initfunc, solver_initfunc):
     dataset = cebra.datasets.init(data_name)