diff --git a/cca_zoo/deep/_generative/_dccae.py b/cca_zoo/deep/_generative/_dccae.py
index 4c69b480..30bc19bc 100644
--- a/cca_zoo/deep/_generative/_dccae.py
+++ b/cca_zoo/deep/_generative/_dccae.py
@@ -70,13 +70,13 @@ def _decode(self, z, **kwargs):
         return recon
 
     def loss(self, batch, **kwargs):
-        z = self(batch['views'])
+        z = self(batch["views"])
         recons = self._decode(z)
         loss = dict()
         loss["reconstruction"] = torch.stack(
             [
                 self.recon_loss(x, recon, loss_type=self.recon_loss_type)
-                for x, recon in zip(batch['views'], recons)
+                for x, recon in zip(batch["views"], recons)
             ]
         ).sum()
         loss["correlation"] = self.objective.loss(z)
diff --git a/cca_zoo/deep/_generative/_dvcca.py b/cca_zoo/deep/_generative/_dvcca.py
index ded05e8c..591ff241 100644
--- a/cca_zoo/deep/_generative/_dvcca.py
+++ b/cca_zoo/deep/_generative/_dvcca.py
@@ -114,22 +114,22 @@ def _decode(self, z, uncertainty=False, **kwargs):
         return x
 
     def loss(self, batch, **kwargs):
-        z = self(batch['views'], mle=False)
+        z = self(batch["views"], mle=False)
         recons = self._decode(z)
         loss = dict()
         loss["reconstruction"] = torch.stack(
             [
                 self.recon_loss(x, recon, loss_type=self.recon_loss_type)
-                for x, recon in zip(batch['views'], recons)
+                for x, recon in zip(batch["views"], recons)
             ]
         ).sum()
         loss["kl shared"] = (
-            self.kl_loss(z["mu_shared"], z["logvar_shared"]) / batch['views'][0].numel()
+            self.kl_loss(z["mu_shared"], z["logvar_shared"]) / batch["views"][0].numel()
         )
         if "private" in z:
             loss["kl private"] = torch.stack(
                 [
-                    self.kl_loss(mu_, logvar_) / batch['views'][0].numel()
+                    self.kl_loss(mu_, logvar_) / batch["views"][0].numel()
                     for mu_, logvar_ in zip(z["mu_private"], z["logvar_private"])
                 ]
             ).sum()
diff --git a/cca_zoo/deep/_generative/_splitae.py b/cca_zoo/deep/_generative/_splitae.py
index 330ed2dd..d8d81d36 100644
--- a/cca_zoo/deep/_generative/_splitae.py
+++ b/cca_zoo/deep/_generative/_splitae.py
@@ -62,13 +62,13 @@ def _decode(self, z, **kwargs):
         return recon
 
     def loss(self, batch, **kwargs):
-        z = self(batch['views'])
+        z = self(batch["views"])
         recons = self._decode(z)
         loss = dict()
         loss["reconstruction"] = torch.stack(
             [
                 self.recon_loss(x, recon, loss_type=self.recon_loss_type)
-                for x, recon in zip(batch['views'], recons)
+                for x, recon in zip(batch["views"], recons)
             ]
         ).sum()
         loss["objective"] = loss["reconstruction"]