It depends on what you want to do obviously. pytorch historically hasn't really focused on forward mode auto differentiation: https://github.com/pytorch/pytorc

It depends on what you want to do obviously. pytorch historically hasn't really focused on forward mode auto differentiation: https://github.com/pytorch/pytorch/issues/10223 https://github.com/pytorch/pytorch/issues/10223 this definitely limits its generality relative to jax, which makes it less than ideal for anything other than 'typical' deep neural networks this is especially true when the research in question is related to things like physics or combining physical models and machine learning, which imho is very interesting. those are use cases that pytorch just isn't good at.