format

netam/common.py

@@ -369,14 +369,12 @@ def linear_bump_lr(epoch, warmup_epochs, total_epochs, max_lr, min_lr):
         )
     return lr
 
+
 def encode_sequences(sequences, encoder):
     encoded_parents, wt_base_modifiers = zip(
         *[encoder.encode_sequence(sequence) for sequence in sequences]
     )
-    masks = [
-        nt_mask_tensor_of(sequence, encoder.site_count)
-        for sequence in sequences
-    ]
+    masks = [nt_mask_tensor_of(sequence, encoder.site_count) for sequence in sequences]
     return (
         torch.stack(encoded_parents),
         torch.stack(masks),

netam/framework.py

@@ -252,7 +252,9 @@ def __init__(self, encoder, model, training_hyperparameters={}):
         self.training_hyperparameters = training_hyperparameters
 
     def __call__(self, sequences):
-        return self.model.selection_factors_of_sequences(sequences, encoder=self.encoder)
+        return self.model.selection_factors_of_sequences(
+            sequences, encoder=self.encoder
+        )
 
     @property
     def device(self):

netam/models.py

@@ -73,7 +73,6 @@ def selection_factors_of_sequences(self, sequences, encoder=None):
             return tuple(t.detach().cpu() for t in outputs)
 
 
-
 class KmerModel(ModelBase):
     def __init__(self, kmer_length):
         super().__init__()