class_docstr: Test loss functions.
class_docstr_tok: ["Test","loss","functions","."]
code: def test_NTXentMultiplePositives_loss(self):
      from deepchem.models.losses import NTXentMultiplePositives
  
      z1 = torch.randn(4, 8)
      z2 = torch.randn(4 * 3, 8)
  
      ntxent_loss = NTXentMultiplePositives(norm=True, tau=0.5)
  
      loss_fn = ntxent_loss._create_pytorch_loss()
      loss = loss_fn(z1, z2)
  
      # Check if the loss is a scalar and non-negative
      assert loss.dim() == 0
      assert loss.item() >= 0
  
imports: import unittest
  import numpy
  import pytest
  import deepchem
  import deepchem.models.losses
label_desc: Use image node_id 37 for calling the TestLosses obj's underlying member method code with example usage: obj.test_NTXentMultiplePositives_loss() without return types