code: def forward(self, x, x_mask, reverse=False, **kwargs):
      if not reverse:
          y = torch.log(torch.clamp_min(x, 1e-5)) * x_mask
          logdet = torch.sum(-y, [1, 2])
          return y, logdet
      else:
          x = torch.exp(x) * x_mask
          return x
  
imports: import torch
  from torch import nn
  from torch.nn import Conv1d
  from torch.nn import functional
  from torch.nn.utils.parametrizations import weight_norm
  from torch.nn.utils.parametrize import remove_parametrizations
  import TTS.vc.modules.freevc.commons
  from TTS.vc.modules.freevc.commons import get_padding, init_weights
label_desc: Use image node_id 1 for calling the Log obj's underlying member method code with example usage: obj.forward(x, x_mask, reverse) and returns: y,  logdet, x