Potential Memory Leak

[halochou]

First, thanks for the great work.
I found there's possible memory leak in the code.
To reproduce the problem, change the test.py as below:

import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
from torch.autograd import gradcheck
from torch.nn.modules.utils import _single, _pair

from modules import ConvOffset2d

num_deformable_group = 1

N, inC, inH, inW = 1, 3, 512, 512
outC, outH, outW = 4, 512, 512
kH, kW = 3, 3

conv = nn.Conv2d(inC, num_deformable_group * 2 * kH * kW, kernel_size=(kH, kW), stride=(1,1), padding=(1,1), bias=False).cuda()
conv_offset2d = ConvOffset2d(inC, outC, (kH, kW), stride=1, padding=1).cuda()

for epoch in range(500):
    inputs = Variable(torch.randn(N, inC, inH, inW).cuda())
    offset = conv(inputs)
    output = conv_offset2d(inputs, offset)
    output.backward(output.data)
    print(output.size())

Code will crash for OOM while doing the backward()

[1zb]

Thanks for the feedback. New version pushed.

[halochou]

It works. Thanks!