diff --git a/MoG.py b/MoG.py
index e7a487a..90a2637 100644
--- a/MoG.py
+++ b/MoG.py
@@ -43,7 +43,7 @@
 
         if i%5000 == 0:
             if method == 'ConsOpt':
-                plot_eigens(i, gen_net, disc_net, params, gamma, path, device)
+                plot_eigens(i, gen_net, disc_net, params, gamma, path, batch_size, z_dim, sigma, criterion, device)
             plot_kde(i,  method, sigma, gen_net, path, device, batch_size, z_dim, real_input=False)
         
             gen_path = join(path, 'Models', 'gen_' + method + "_" + str(i) + '.pt')
diff --git a/utils/plot.py b/utils/plot.py
index 089ed8e..ce759fd 100644
--- a/utils/plot.py
+++ b/utils/plot.py
@@ -6,9 +6,9 @@
 
 
 
-def plot_eigens(iteration, gen, disc, params, gamma, path, device):
-    _, _, fake_d_out_gen, fake_d_out_disc, fake_d_out, real_d_out = batch_net_outputs()
-    _, _, gen_loss, disc_loss = net_losses(fake_d_out_gen, fake_d_out_disc, fake_d_out, real_d_out)
+def plot_eigens(iteration, gen, disc, params, gamma, path,  batch_size, z_dim, sigma, criterion, device):
+    _, _, fake_d_out_gen, fake_d_out_disc, fake_d_out, real_d_out = batch_net_outputs(gen, disc, batch_size, z_dim, sigma, device)
+    _, _, gen_loss, disc_loss = net_losses(criterion, fake_d_out_gen, fake_d_out_disc, fake_d_out, real_d_out)
     p_count = torch.cat([x.flatten() for x in params]).shape[0]
 
     gen.zero_grad()