o 8wÖiã@sdZdd„ZdS)z_Implements functions to avoid optimizing certain parameters Authors * Titouan Parcollet 2023 cCsXg}g}| ¡D]\}}|jsqt|jƒdkr| |¡q| |¡q|ddœd|igS)a‰Put vectors in a parameter group without weight decay Takes in a list of modules and separates their parameters into two parameter groups, which can be passed to a PyTorch Optimizer class. Vector parameters get weight_decay overridden to zero. This is particularly useful for biases and norms, which we expect to deviate from zero. Other vectors as parameters are also likely not meant to be pushed toward zero. Arguments --------- modules : torch.ModuleList, torch.Module Torch modules to operate on Returns ------- list The parameter groups in the Pytorch Optimizer specification format. ég)ÚparamsÚ weight_decayr)Únamed_parametersÚ requires_gradÚlenÚshapeÚappend)ÚmodulesÚdecayÚno_decayÚ_Úparam©rúY/home/ubuntu/sommelier/.venv/lib/python3.10/site-packages/speechbrain/utils/optimizers.pyÚrm_vector_weight_decays  þrN)Ú__doc__rrrrrÚs