code: def forward(self, inputs, dummy_labels=None):
      targets = torch.zeros(inputs.shape[0], dtype=torch.long).cuda()
      loss = nn.CrossEntropyLoss(reduction=self.reduction).cuda()(
          inputs, targets
      )
      return loss
  
file_path: SlowFast/slowfast/models/losses.py
imports: from functools import partial
  import torch
  import torch.nn
  from pytorchvideo.losses.soft_target_cross_entropy import SoftTargetCrossEntropyLoss
label_desc: Use image node_id 2 for calling the ContrastiveLoss obj's underlying member method code with example usage: obj.forward(inputs, dummy_labels) and returns: loss