Built-in autograd and RNN modules convinced me.
Anecdotally, a fairly complex seq2seq+attention model took me about a week to build in Torch. The majority of that was figuring out backpropagation. The same model took 3 weeks (and counting, I gave up) in TensorFlow. In PyTorch it took about an hour.