class_docstr: From: https://github.com/facebookresearch/barlowtwins/blob/main/main.py#L218
  
  Main differences:
      - we add a `exclude_bias_and_norm` parameter to filter out biases from the LARS adaptive LR
      - we remove the filter on weight decay as it is not needed in VISSL. See `get_optimizer_param_groups`
code: def _exclude_bias_and_norm(p):
      return p.ndim == 1
  
file_path: vissl/vissl/optimizers/lars.py
imports: from typing import Any, Dict
  import torch
  from classy_vision.optim import ClassyOptimizer, register_optimizer
  from torch import optim
label_desc: Use image node_id 2 for calling the _LARS obj's underlying member method code with example usage: obj._exclude_bias_and_norm(p) and returns: unknown