remove_parametrizations() stores weight as a plain __dict__ tensor (not
nn.Parameter), making it invisible to _parameters iteration. Also, buffers
(Activation1d anti-aliasing filters) are inference tensors that break the
backward graph mid-network. Fix all three categories:
1. _parameters: clone().detach(), wrap as Parameter
2. plain __dict__ tensors: clone(), register_parameter (also makes trainable)
3. _buffers: clone() to strip inference flag without parametrizing
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Ethanfel
5df2abd6dd