Fix codespell errors

Author: CeliaBenquet

cebra/solver/base.py

@@ -86,7 +86,7 @@ def _check_indices(batch_start_idx: int, batch_end_idx: int,
         raise ValueError(
             f"The batch has length {batch_size_lenght} which "
             f"is smaller or equal than the required offset length {len(offset)}."
-            f"Either choose a model with smaller offset or the batch shoud contain more samples."
+            f"Either choose a model with smaller offset or the batch should contain more samples."
         )
 
 
@@ -511,7 +511,7 @@ def decoding(self, train_loader, valid_loader):
 
     @abc.abstractmethod
     def _check_is_inputs_valid(self, inputs: torch.Tensor, session_id: int):
-        """Check that the inputs can be infered using the selected model.
+        """Check that the inputs can be inferred using the selected model.
         
         Note: This method checks that the number of neurons in the input is
         similar to the input dimension to the selected model.

cebra/solver/multi_session.py

@@ -144,7 +144,7 @@ def _set_fitted_params(self, loader: cebra.data.Loader):
 
     def _check_is_inputs_valid(self, inputs: torch.Tensor,
                                session_id: Optional[int]):
-        """Check that the inputs can be infered using the selected model.
+        """Check that the inputs can be inferred using the selected model.
         
         Note: This method checks that the number of neurons in the input is
         similar to the input dimension to the selected model.

cebra/solver/single_session.py

@@ -67,7 +67,7 @@ def _set_fitted_params(self, loader: cebra.data.Loader):
         self.n_features = loader.dataset.input_dimension
 
     def _check_is_inputs_valid(self, inputs: torch.Tensor, session_id: int):
-        """Check that the inputs can be infered using the selected model.
+        """Check that the inputs can be inferred using the selected model.
         
         Note: This method checks that the number of neurons in the input is
         similar to the input dimension to the selected model.

tests/test_solver.py

@@ -683,7 +683,7 @@ def test_batched_transform_multi_session(data_name, model_name, padding,
     n_samples = dataset._datasets[0].neural.shape[0]
     assert all(
         d.neural.shape[0] == n_samples for d in dataset._datasets
-    ), "for this set all of the sessions need ot have same number of samples."
+    ), # all sessions need to have same number of samples
 
     smallest_batch_length = n_samples - batch_size
     offset_ = model[0].get_offset()