I'm a researcher who used Theano for 3 years to train convnets. A couple of months ago I realized that Theano is getting too much pain to work with (main reasons being the lack of implementations for latest models, and difficulty of using multiple GPUs), so I decided to switch to a more popular framework. I looked at TF, and almost started porting my code to it, then someone suggested I look at PyTorch. After 30 minutes playing with it, I was sold. Much more intuitive. Major architectures from the last 12 months have been implemented. Dynamic graphs are probably something I will need in the future. Community is very active and helpful. The downside is that the software is not as mature as TF, and the community is smaller, but that's changing fast.
p.s. What you wrote about Torch is correct though, but we are talking about PyTorch, not Torch.
I'm a researcher who used Theano for 3 years to train convnets. A couple of months ago I realized that Theano is getting too much pain to work with (main reasons being the lack of implementations for latest models, and difficulty of using multiple GPUs), so I decided to switch to a more popular framework. I looked at TF, and almost started porting my code to it, then someone suggested I look at PyTorch. After 30 minutes playing with it, I was sold. Much more intuitive. Major architectures from the last 12 months have been implemented. Dynamic graphs are probably something I will need in the future. Community is very active and helpful. The downside is that the software is not as mature as TF, and the community is smaller, but that's changing fast.
p.s. What you wrote about Torch is correct though, but we are talking about PyTorch, not Torch.