class_docstr: NCE for MM joint space, on softmax text2video matrix.
      
class_docstr_tok: ["NCE","for","MM","joint","space",",","on","softmax","text2video","matrix","."]
code: def __call__(self, pooled_video, pooled_text, **kargs):
      batch_size = pooled_video.size(0)
      logits = torch.mm(pooled_text, pooled_video.transpose(1, 0))
      targets = torch.arange(
          batch_size, dtype=torch.long, device=pooled_video.device
      )
      return self.loss(logits, targets)
  
imports: import torch
  from torch import nn
  from .loss import Loss
label_desc: Use image node_id 2 for calling the T2VContraLoss obj's underlying member method code with example usage: obj.__call__(pooled_video, pooled_text) and returns: self