diff --git a/torchflows/bijections/base.py b/torchflows/bijections/base.py
index 02e7b57..57c0ca6 100644
--- a/torchflows/bijections/base.py
+++ b/torchflows/bijections/base.py
@@ -11,6 +11,7 @@
 class Bijection(nn.Module):
     """Bijection class.
     """
+
     def __init__(self,
                  event_shape: Union[torch.Size, Tuple[int, ...]],
                  context_shape: Union[torch.Size, Tuple[int, ...]] = None,
@@ -50,9 +51,17 @@ def inverse(self, z: torch.Tensor, context: torch.Tensor = None) -> Tuple[torch.
         """
         raise NotImplementedError
 
-    @staticmethod
-    def batch_apply(fn, batch_size, *args):
-        dataset = TensorDataset(*args)
+    def batch_apply(self, fn, batch_size, x, context=None):
+        batch_shape = x.shape[:-len(self.event_shape)]
+
+        if context is None:
+            x_flat = torch.flatten(x, start_dim=0, end_dim=len(batch_shape) - 1)
+            dataset = TensorDataset(x_flat)
+        else:
+            x_flat = torch.flatten(x, start_dim=0, end_dim=len(batch_shape) - 1)
+            context_flat = torch.flatten(context, start_dim=0, end_dim=len(batch_shape) - 1)
+            dataset = TensorDataset(x_flat, context_flat)
+
         data_loader = DataLoader(dataset, batch_size=batch_size, shuffle=False)
         outputs = []
         log_dets = []
@@ -60,8 +69,8 @@ def batch_apply(fn, batch_size, *args):
             batch_out, batch_log_det = fn(*batch)
             outputs.append(batch_out)
             log_dets.append(batch_log_det)
-        outputs = torch.cat(outputs, dim=0)
-        log_dets = torch.cat(log_dets, dim=0)
+        outputs = torch.cat(outputs, dim=0).view_as(x)
+        log_dets = torch.cat(log_dets, dim=0).view(*batch_shape)
         return outputs, log_dets
 
     def batch_forward(self, x: torch.Tensor, batch_size: int, context: torch.Tensor = None):
@@ -89,6 +98,7 @@ def batch_inverse(self, x: torch.Tensor, batch_size: int, context: torch.Tensor
     def regularization(self):
         return 0.0
 
+
 def invert(bijection: Bijection) -> Bijection:
     """Swap the forward and inverse methods of the input bijection.
 
@@ -104,6 +114,7 @@ class BijectiveComposition(Bijection):
     """
     Composition of bijections. Inherits from Bijection.
     """
+
     def __init__(self,
                  event_shape: Union[torch.Size, Tuple[int, ...]],
                  layers: List[Bijection],