Merge branch 'main' into pyproject

_requirements/default.txt

@@ -1,6 +1,6 @@
-setuptools==65.*
+setuptools==67.4.0
 matplotlib>=3.0.0, <3.4.0
-ipython[notebook]>=8.0.0, <8.9.0
+ipython[notebook]>=8.0.0, <8.12.0
 torch>=1.8.1, <1.14.0
 pytorch-lightning>=1.4, <2.0.0
 torchmetrics>=0.7, <0.12

course_UvA-DL/09-normalizing-flows/NF_image_modeling.py

@@ -799,13 +799,13 @@ def forward(self, x):
 
 
 class LayerNormChannels(nn.Module):
-    def __init__(self, c_in):
-        """This module applies layer norm across channels in an image.
-
-        Has been shown to work well with ResNet connections.
+    def __init__(self, c_in, eps=1e-5):
+        """
+        This module applies layer norm across channels in an image.
 
         Args:
             c_in: Number of channels of the input
+            eps: Small constant to stabilize std
         """
         super().__init__()
         self.gamma = nn.Parameter(torch.ones(1, c_in, 1, 1))
@@ -1252,7 +1252,8 @@ def print_num_params(model):
 # %%
 @torch.no_grad()
 def interpolate(model, img1, img2, num_steps=8):
-    """
+    """Interpolate.
+
     Args:
         model: object of ImageFlow class that represents the (trained) flow model
         img1, img2: Image tensors of shape [1, 28, 28]. Images between which should be interpolated.