slides added

model/model.py

@@ -14,7 +14,7 @@ class Block(nn.Module):
     super().__init__()
     self.time_mlp = nn.Linear(time_emb_dim, out_ch)
     if up:
-      ## up channel - go big big big bigg from smol smol smol with 3x3 kernel
+      ## up channel - gobig big big bigg from smol smol smol with 3x3 kernel
       self.conv1 = nn.Conv2d(2*in_ch, out_ch, 3, padding=1)
       self.transform = nn.ConvTranspose2d(out_ch, out_ch, 4, 2, 1)
     else:

model/precomputes.py

@@ -3,7 +3,7 @@ from torch.nn import functional as F
 
 T = 300 ## according to the paper
 
-### SOO MMANNYY PRECOMPUTEDD VALUESS TO TRACKKKK
+### SOO MMANNYY PRECOMPUTEDD VALUESS TO TRACKKKKSS
 betas = torch.linspace(1e-4, 0.02, T)
 alphas = 1. - betas
 alphas_cumulative_products = torch.cumprod(alphas, axis=0)