correct typos

src/ncopt/functions/main.py

@@ -32,27 +32,27 @@ def __init__(
         Parameters
         ----------
         model : torch.nn.Module
-            The Pytorch module for evaluating the function
+            The Pytorch module for evaluating the function.
         dim : Optional[int], optional
             Input dimension of the function, by default None.
             Needs to be specified for objective functions for the solver.
         dim_out : int, optional
-            Output dimension of the function, by default 1
+            Output dimension of the function, by default 1.
             Needs to be specified for each constraint function for the solver.
         name : Optional[str], optional
             A name for the function, by default None.
             Not needed for solver, only for convenience.
         device : Optional[Union[str, torch.device]], optional
             A device for the forward pass, by default None.
-            You normall don't need to specify this: we automatically use the device
+            You normally don't need to specify this: we automatically use the device
             where the parameters of the model lie on.
             If you specify the device, please make sure, that the parameters of the model
             lie on the correct device.
         dtype : Optional[torch.dtype], optional
             Format to convert when evaluating a tensor that was converted
-            from ``np.ndarray``, by default torch.float32
+            from ``np.ndarray``, by default torch.float32.
         prepare_inputs : Optional[Callable], optional
-            Callable to prepare the model inpt, by default None
+            Callable to prepare the model inpt, by default None.
             Note that the solver always inputs the full optimization variable (as batch).
             If your function only needs a subset of the vector as input, or
             needs reshaping operations etc, then you can do this via this callable.

src/ncopt/sqpgs/main.py

@@ -59,24 +59,24 @@ def __init__(
             Starting point, by default vector of zeros.
         tol : float, optional
             Tolerance for stopping, measured by E_k in [Curtis and Overton, 2012].
-            By default DEFAULT_ARG.tol
+            By default DEFAULT_ARG.tol.
         max_iter : int, optional
-            Maximum number of iterations, by default DEFAULT_ARG.max_iter
+            Maximum number of iterations, by default DEFAULT_ARG.max_iter.
         verbose : bool, optional
-            Whether to print status updates, by default DEFAULT_ARG.verbose
+            Whether to print status updates, by default DEFAULT_ARG.verbose.
         options : dict, optional
             Dictionary with options, by default {}.
             All specified entries will overwrite the default value.
             See ``./defaults.py`` for possible key names and default values.
         assert_tol : float, optional
-            Assertion tolerance used in mathematical checks, by default DEFAULT_ARG.assert_tol
+            Assertion tolerance used in mathematical checks, by default DEFAULT_ARG.assert_tol.
             You can avoid errors raised by assertions by increasing this number.
             Note that in that case, the algorihtm might be not producing correct output.
         store_history : bool, optional
             Whether to store the history of iterates in every iteration, by default False.
             Only use this for small examples, as it might produce memory overflow.
         log_every : int, optional
-            Frequency of status updates (if ``verbose=True``) by default DEFAULT_ARG.log_every
+            Frequency of status updates (if ``verbose=True``) by default DEFAULT_ARG.log_every.
 
         """
         if tol < 0: