segment fault on libleveldb.so when load data

[ivysoftware]

Hi Junyuan,
Basic, I downloaded two datasets: mnist and reuters by mnist(reuters)/get_data.sh then pyhton make_mnist(reuters)_data.py.
However, things is not so easy as I thought.
1. Parameter initialization Problem: Claimed " You can use dec/pretrain.py to train your own autoencoder. " on the https://github.com/piiswrong/dec
but in my practice, python pretrain.py came out of "segment fault on libleveldb.so when load data", which data is default on DB=mnist, and download by mnist/get_data.sh then pyhton make_mnist_data.py
2. Two(mnist/reuters10k) datasets are segmented fault on training using dec.py.
3. Since reutersidf is ok on training, I am looking forward to seeing the amazing result, but the acc is only about 0.35 not a impressive promance of 0.7, during the experiment procedure I assumed the reutersidf data is pretrained well.
Could you double check on if datesets is pretrained well ? Although, the loss is very low.
4. I have a confuse on the training process: during diff iteration, diff training data is loaded by seek operator, after the current iteration training(each has a 20 times caffe iterations), init weight and init.model are updated, then a fine-tuning of next iteration diff data is processed, is it right?

[ankitrbansal]

@ivysoftware Hi, I am facing the same issues when I try it with mnist dataset. I get a Segmentation Fault on "Opening leveldb mnist_total". Have you found a way to make it work with mnist? Thanks!