ezyang/pytorch-unattached

Adapt torch.jit.Traceable to RNN-cell like usage

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Right now it assumes that it encapsulates the whole model, or that it's a unique subgraph in the model. If a cell is used multiple times, we'll record the first forward run and compile a one-stage closure when it's reused. This means that the closure isn't differentiable even once.