code: def __init__(
      self,
      projector_dim: int = 8196,
      lambda_param: float = 5e-3,
      gather_distributed: bool = False,
  ):
      super(BarlowTwinsLossReference, self).__init__()
      # normalization layer for the representations z1 and z2
      self.bn = nn.BatchNorm1d(projector_dim, affine=False)
      self.lambda_param = lambda_param
      self.gather_distributed = gather_distributed
  
file_path: lightly/tests/loss/test_barlow_twins_loss.py
imports: import pytest
  import torch
  import torch.nn
  from pytest_mock import MockerFixture
  from torch import distributed
  from lightly.loss.barlow_twins_loss import BarlowTwinsLoss
label_desc: Use image node_id 1 to create a new BarlowTwinsLossReference object from inherited base classes: torch.nn with example: obj = BarlowTwinsLossReference(projector_dim, lambda_param, gather_distributed)