From e553093d3b2a44a1b6d0c8739a973598af6aa535 Mon Sep 17 00:00:00 2001
From: Soumith Chintala <soumith@fb.com>
Date: Mon, 27 Feb 2017 13:54:22 -0500
Subject: [PATCH] dont reuse variables

---
 main.py | 21 +++++++++++----------
 1 file changed, 11 insertions(+), 10 deletions(-)

diff --git a/main.py b/main.py
index 8b35bb2..02f707f 100644
--- a/main.py
+++ b/main.py
@@ -182,17 +182,18 @@ for epoch in range(opt.niter):
             real_cpu, _ = data
             netD.zero_grad()
             batch_size = real_cpu.size(0)
-            input.data.resize_(real_cpu.size()).copy_(real_cpu)
+            
+            inputv = Variable(input)
 
-            errD_real = netD(input)
+            errD_real = netD(inputv)
             errD_real.backward(one)
 
             # train with fake
-            noise.data.resize_(batch_size, nz, 1, 1)
-            noise.data.normal_(0, 1)
-            fake = netG(noise)
-            input.data.copy_(fake.data)
-            errD_fake = netD(input)
+            noise.resize_(opt.batchSize, nz, 1, 1).normal_(0, 1)
+            noisev = Variable(noise)
+            fake = netG(noisev)
+            inputv.data.copy_(fake.data)
+            errD_fake = netD(inputv)
             errD_fake.backward(mone)
             errD = errD_real - errD_fake
             optimizerD.step()
@@ -205,9 +206,9 @@ for epoch in range(opt.niter):
         netG.zero_grad()
         # in case our last batch was the tail batch of the dataloader,
         # make sure we feed a full batch of noise
-        noise.data.resize_(opt.batchSize, nz, 1, 1)
-        noise.data.normal_(0, 1)
-        fake = netG(noise)
+        noise.resize_(opt.batchSize, nz, 1, 1).normal_(0, 1)
+        noisev = Variable(noise)
+        fake = netG(noisev)
         errG = netD(fake)
         errG.backward(one)
         optimizerG.step()