# Anyone tried out the PyTorch Mobile demo apps yet? **URL:** \ **Category:** Mobile\ **Created:** [October 16, 2019, 3:40am UTC](https://discuss.pytorch.org/t/anyone-tried-out-the-pytorch-mobile-demo-apps-yet/58336 "2019-10-16T03:40:33Z")\ **Posts on this page:** 1\ **Showing post:** 14
**Author:** ![tom](https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/tom/32/3162_2.png) [@tom](https://discuss.pytorch.org/u/tom)\ **Post date:** [October 30, 2019, 9:09am UTC](https://discuss.pytorch.org/t/anyone-tried-out-the-pytorch-mobile-demo-apps-yet/58336/14 "2019-10-30T09:09:49Z")
So I have played with it some more: - I must say I dislike the hack around reading models (copying from assets to fs). I got burnt by forgetting to overwrite it more than once. My libtorch/JNI adaptation used `torch::jit::load` with string streams. This is less memory efficient, of course, but for development it is much more convenient. If it isn’t controversial, I could see if I file a PR. - One of the first things I needed was a method to get output pictures, I’ll file a PR for adding something like that to torchvision. - I hit a bug with some arm32 ops. Model works fine on Android/x86, colors/scanline widths are off on Android/arm(32). The net uses `aten::_convolution, aten::add, aten::contiguous, aten::instance_norm, aten::reflection_pad2d, aten::relu_, aten::tanh, prim::Constant, prim::GetAttr, prim::ListConstruct` with the most fancy convolutions being with stride=2 and a transposed one with stride=2 and output padding=1 (so no non-default dilations, kernel 1,3,7). I’m still trying to narrow this down. As error looks like it is some “striding”/contiguous problem, I tried inserting lots of `contiguous` but it didn’t immediately help. I know this isn’t narrowed down enough yet, unfortunately. Best regards Thomas --- _[View the full topic](https://discuss.pytorch.org/t/anyone-tried-out-the-pytorch-mobile-demo-apps-yet/58336)._