code: def test_equal_losses(y_pred, embedded_x, obf_vars):
      numpy_loss = UnsupervisedLossNumpy(
          y_pred=y_pred, embedded_x=embedded_x, obf_vars=obf_vars
      )
  
      torch_loss = UnsupervisedLoss(
          y_pred=torch.tensor(y_pred, dtype=torch.float64),
          embedded_x=torch.tensor(embedded_x, dtype=torch.float64),
          obf_vars=torch.tensor(obf_vars, dtype=torch.float64),
      )
  
      assert np.isclose(numpy_loss, torch_loss.detach().numpy())
  
imports: import numpy
  import torch
  import pytest
  from pytorch_tabnet.metrics import UnsupervisedLoss, UnsupervisedLossNumpy
label_desc: Use image node_id 1 for calling a global function with example usage: test_equal_losses(y_pred, embedded_x, obf_vars) without return types