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pasqal-io / pyqtorch

PyTorch-based state vector simulator
https://pasqal-io.github.io/pyqtorch/
Apache License 2.0
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[Refactoring, Hamevo] Optimize block_to_tensor calls for repeated execution of HamEvo #176

Closed jpmoutinho closed 4 months ago

jpmoutinho commented 5 months ago

Original text from @dominikandreasseitz :

_Right now, we call block_to_tensor in every forward pass to get the hamiltonian, which is then exponentiated in native pyq. lets find a way to not have to call block_totensor but rather "fill in" parameter values in a smarter way.

Actually doing that for parametric Hamiltonians will be hard. However, we should avoid doing it for non-parametric Hamiltonians. Those should only be tensorized once and then cached for repeated evaluations.

Related to https://github.com/pasqal-io/qadence/issues/134

jpmoutinho commented 4 months ago

Closing as one possible solution has been merged in #205. There are possibly other avenues to explore, but nothing with a concrete plan, so we can open new issues for that in the future if needed.