code: def reset_all_weights(model: nn.Module) -> None:
      """Resets all parameters in a network.
  
      Args:
          model: The model to reset the parameters of.
  
      refs:
          - https://discuss.pytorch.org/t/how-to-re-set-alll-parameters-in-a-network/20819/6
          - https://stackoverflow.com/questions/63627997/reset-parameters-of-a-neural-network-in-pytorch
          - https://pytorch.org/docs/stable/generated/torch.nn.Module.html
      """
  
      @torch.no_grad()
      def weight_reset(m: nn.Module):
          # - check if the current module has reset_parameters & if it's callabed called it on m
          reset_parameters = getattr(m, "reset_parameters", None)
          if callable(reset_parameters):
              m.reset_parameters()
  
      # Applies fn recursively to every submodule see: https://pytorch.org/docs/stable/generated/torch.nn.Module.html
      model.apply(fn=weight_reset)
  
file_path: pytorch_tabular/src/pytorch_tabular/utils/nn_utils.py
imports: import torch
  import torch.nn
  from .logger import get_logger
label_desc: Use image node_id 3 for calling a global function with example usage: reset_all_weights(model) without return types