Run isort, ruff, yapf

Author: CeliaBenquet

cebra/data/single_session.py

@@ -370,7 +370,7 @@ 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`` "

cebra/integrations/sklearn/cebra.py

@@ -51,6 +51,7 @@
     np.dtypes.Float64DType, np.dtypes.Int64DType
 ]
 
+
 def check_version(estimator):
     # NOTE(stes): required as a check for the old way of specifying tags
     # https://github.com/scikit-learn/scikit-learn/pull/29677#issuecomment-2334229165
@@ -76,8 +77,6 @@ def _safe_torch_load(filename, weights_only, **kwargs):
     return checkpoint
 
 
-
-
 def _init_loader(
     is_cont: bool,
     is_disc: bool,

cebra/solver/base.py

@@ -33,7 +33,7 @@
 import abc
 import os
 import warnings
-from typing import Callable, Dict, Iterable, List, Literal, Optional, Tuple, Union
+from typing import Callable, Dict, List, Literal, Optional, Tuple, Union
 
 import literate_dataclasses as dataclasses
 import numpy.typing as npt

tests/test_solver.py

@@ -59,15 +59,14 @@
      cebra.data.ContinuousMultiSessionDataLoader, "offset1-model"),
     ("demo-continuous-multisession",
      cebra.data.ContinuousMultiSessionDataLoader, "offset10-model"),
-    ("demo-discrete-multisession",
-              cebra.data.DiscreteMultiSessionDataLoader, "offset1-model"),
-    ("demo-discrete-multisession",
-     cebra.data.DiscreteMultiSessionDataLoader, "offset10-model"),
+    ("demo-discrete-multisession", cebra.data.DiscreteMultiSessionDataLoader,
+     "offset1-model"),
+    ("demo-discrete-multisession", cebra.data.DiscreteMultiSessionDataLoader,
+     "offset10-model"),
 ]:
     multi_session_tests.append((*args, cebra.solver.MultiSessionSolver))
 
 
-
 def _get_loader(data, loader_initfunc):
     kwargs = dict(num_steps=5, batch_size=32)
     loader = loader_initfunc(data, **kwargs)
@@ -168,7 +167,7 @@ def test_single_session(data_name, loader_initfunc, model_architecture,
 
     assert solver.num_sessions is None
     assert solver.n_features == X.shape[1]
-    
+
     embedding = solver.transform(X)
     assert isinstance(embedding, torch.Tensor)
     assert embedding.shape == (X.shape[0], OUTPUT_DIMENSION)
@@ -498,7 +497,7 @@ def test_multi_session_2(data_name, loader_initfunc, solver_initfunc):
     assert isinstance(log, dict)
 
     solver.fit(loader)
-    
+
 
 def create_model(model_name, input_dimension):
     return cebra.models.init(model_name,