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 __init__(
      self,
      params,
      lr: float = 0.1,
      momentum: float = 0.9,
      weight_decay: float = 0,
      eta: float = 0.001,
      exclude_bias_and_norm: bool = False,
  ):
      defaults = {
          "lr": lr,
          "weight_decay": weight_decay,
          "momentum": momentum,
          "eta": eta,
          "exclude": exclude_bias_and_norm,
      }
      super().__init__(params, defaults)
  
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 1 to create a new _LARS object from inherited base classes: optim with example: obj = _LARS(params, lr, momentum, weight_decay, eta, exclude_bias_and_norm)