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torch.autograd.forward_ad.unpack_dual

torch.autograd.forward_ad.unpack_dual(tensor, *, level=None)[source]

Unpacks a “dual tensor” to get both its Tensor value and its forward AD gradient. The result is a namedtuple (primal, tangent) where primal is a view of tensor’s primal and tangent is tensor’s tangent as-is. Neither of these tensors can be dual tensor of level level.

This function is backward differentiable.

Example:

>>> with dual_level():
...     inp = make_dual(x, x_t)
...     out = f(inp)
...     y, jvp = unpack_dual(out)
...     jvp = unpack_dual(out).tangent

Please see the forward-mode AD tutorial for detailed steps on how to use this API.

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