Reduce function building overhead in wrappedCircuit#332
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k-vijayaraghavan wants to merge 16 commits into
Open
Reduce function building overhead in wrappedCircuit#332k-vijayaraghavan wants to merge 16 commits into
k-vijayaraghavan wants to merge 16 commits into
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In models/circuits/fittings.py, buildCircuit no longer substitutes parameters; rather it returns a string that can be used to construct a lambda function. Subsequently wrapCircuit returns a lambda function that only needs to be generated once. This offers ~80% improvement.
We can pass optimizations={"algorithm":algo,...} to circuit_fit.
Here algo can be 'pygad' or 'scipy_minimize' or a callable. We can also pass optimizations=[optimizations1,optimizations2], where optimizations1={"algorithm":algo,...} ... to perform sequential optimization.
To improve scaling, we can pass scale=[..] with the expected relative magnitude of the different parameters.
Modified elements for robust tanh
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In models/circuits/fittings.py, it is rather inefficient to create/evaluate a new function for each call (i.e. currently, each call involves string conversions and exec). The proposed buildCircuit no longer substitutes parameters; rather it returns a string with variable-names that can be used to construct a lambda function. Subsequently wrapCircuit returns a lambda function that only needs to be generated once. This offers ~80% improvement. (tests/test_fitting.py::test_buildCircuit() has been correspondingly modified for compatibility)
PS: A new file tests/compare_newfitting.py was created (and subsequently deleted) to compare new buildCircuit with original buildCircuit. The file showed significant speed-up
R0-p(R1-Wo1,CPE1) : 82.97% faster
R0-p(C1,R1,R2) : 79.30% faster
R0-p(p(R1, C1)-R2, C2) : 82.17% faster
p(C1,R1)-p(C2,R2) : 81.10% faster
R1 : 85.55% faster