Formatting.

lensless/recon/multi_wiener.py

@@ -96,7 +96,7 @@ def __init__(
         skip_pre=False,
     ):
         """
-        Constructor for Multi-Wiener Deconvolution Network (MWDN) as proposed in: 
+        Constructor for Multi-Wiener Deconvolution Network (MWDN) as proposed in:
         https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-23-39088&id=541387
 
         Parameters
@@ -169,7 +169,7 @@ def __init__(
     def _prepare_process_block(self, process):
         """
         Method for preparing the pre or post process block.
-        
+
         Parameters
         ----------
         process : :py:class:`function` or :py:class:`~torch.nn.Module`, optional
@@ -283,6 +283,7 @@ def reconstruction_error(self, prediction, lensless):
         convolver = self._convolver
         if not convolver.pad:
             prediction = convolver._pad(prediction)
+
         Fx = convolver.convolve(prediction)
         Fy = lensless
 

lensless/recon/trainable_inversion.py

@@ -9,8 +9,6 @@
 
 
 class TrainableInversion(TrainableReconstructionAlgorithm):
-    """ """
-
     def __init__(self, psf, dtype=None, K=1e-4, **kwargs):
         """
         Constructor for trainable inversion component as proposed in

lensless/recon/trainable_recon.py

@@ -92,6 +92,7 @@ def __init__(
         compensation_residual : bool, optional
             Whether to use residual connection in compensation layer.
         """
+
         assert isinstance(psf, torch.Tensor), "PSF must be a torch.Tensor"
         super(TrainableReconstructionAlgorithm, self).__init__(
             psf, dtype=dtype, n_iter=n_iter, **kwargs