devnag

import torch
import torch.nn as nn
from torch.autograd import Variable
import torch.optim as optim

a = torch.ones(1,2)
b = torch.nn.Linear(2,1)
b.zero_grad()

c = b(Variable(a))

devnag

diff --git a/gan_pytorch.py b/gan_pytorch.py
index 0bff38c..802d6cb 100755
--- a/gan_pytorch.py
+++ b/gan_pytorch.py
@@ -31,7 +31,7 @@ g_steps = 1
 
 # ### Uncomment only one of these
 #(name, preprocess, d_input_func) = ("Raw data", lambda data: data, lambda x: x)
-(name, preprocess, d_input_func) = ("Data and variances", lambda data: decorate_with_diffs(data, 2.0), lambda x: x * 2)
+(name, preprocess, d_input_func) = ("Data and variances", lambda data: decorate_with_diffs(data, 2.0), lambda x: x)