Fix automatic CUDA graphing not working when requiring backwards (#120)

* Pass posTensor as input argument to energyTensor.backwards.
This instructs torch to compute gradients only with respect to positions.

* Add comments

platforms/cuda/src/CudaTorchKernels.cpp

@@ -188,7 +188,11 @@ static void executeGraph(bool outputsForces, bool includeForces, torch::jit::scr
  energyTensor = module.forward(inputs).toTensor();
  // Compute force by backpropagating the PyTorch model
  if (includeForces) {
- energyTensor.backward();
+ // CUDA graph capture sometimes fails if backwards is not explicitly requested w.r.t positions
+ // See https://github.com/openmm/openmm-torch/pull/120/
+ auto none = torch::Tensor();
+ energyTensor.backward(none, false, false, posTensor);
+ // This is minus the forces, we change the sign later on
  forceTensor = posTensor.grad().clone();
  // Zero the gradient to avoid accumulating it
  posTensor.grad().zero_();