pyFDN.trainable_from_preset

pyFDN.trainable_from_preset(preset, *, trainable=None, matrix='orthogonal', trainable_hooks=(), nfft=16384, alias_decay_db=0.0, device=None, dtype=None)

Build a FLAMO model while recovering designed filter parameters.

The baked build is always the source of truth. A hook is recreated as a AttenuationFilter or OutputEQ only when its design record contains a target and the recreated SOS bank matches the baked one. Otherwise the baked coefficients remain a frozen filter, exactly as in trainable_from_build().

trainable_hooks selects which recovered design targets require gradients. It does not make raw baked SOS coefficients trainable.

Return type:

Any