timesteps

app.py

@@ -222,7 +222,7 @@ def sample_ddpm(n_sample, context, save_rate=20):
     return samples, intermediate
 
 @torch.no_grad()
-def sample_ddpm_context(n_sample, context, save_rate=20):
+def sample_ddpm_context(n_sample,timesteps, context, save_rate=20):
     # x_T ~ N(0, 1), sample initial noise
     samples = torch.randn(n_sample, 3, height, height).to(device)
 
@@ -257,7 +257,7 @@ def greet(input):
 	ctx = torch.from_numpy(mtx_2d).to(device=device).float()
 
 	#samples, intermediate = sample_ddim_context(32, ctx, n=steps)
-	samples, intermediate = sample_ddpm_context(32, ctx, steps)
+	samples, intermediate = sample_ddpm_context(32, steps, ctx)
 
 	#samples, intermediate = sample_ddim(32, n=steps)
 	#ctx = F.one_hot(torch.randint(0, 5, (32,)), 5).to(device=device).float()