That man has an infective enthusiasm. I remember the DCGAN paper inspired me to try getting the (Lua) Torch code to work, and I tried it on the Oxford flowers dataset early on. It worked surprisingly well, and Soumith Chintala even shared it around in social media, surprised at how well it worked on such a small dataset. Of course back then we didn't really appreciate the problem of mode collapse.
Pytorch and old Lua Torch were a pleasure to work with compared to the contemporary Tensorflow. Lots of S.C's code was copied around liberally, it had its quirks (I remember the DCGAN code had a pretty odd way of doing parameter passing) but it was also really easy to understand and made random people like me feel like we had suddenly stumbled onto something crazy powerful (which we had!). It was wonderfully hackable.
Pytorch and old Lua Torch were a pleasure to work with compared to the contemporary Tensorflow. Lots of S.C's code was copied around liberally, it had its quirks (I remember the DCGAN code had a pretty odd way of doing parameter passing) but it was also really easy to understand and made random people like me feel like we had suddenly stumbled onto something crazy powerful (which we had!). It was wonderfully hackable.