docstr: Avoids the log(0) problem
  
  Args:
      x (torch.tensor): input tensor
      eps (float, optional): lower bound. Defaults to 1e-04.
  
  Returns:
      torch.tensor: :math:`log(x)`
docstr_tok: ["Avoids","the","log","(","0",")","problem","Args",":","x","(","torch.tensor",")",":","input","tensor","eps","(","float",",","optional",")",":","lower","bound",".","Defaults","to","1e-04",".","Returns",":","torch.tensor",":",":","math",":","`","log","(","x",")","`"]
code: def log_clamped(x, eps=1e-04):
      """
      Avoids the log(0) problem
  
      Args:
          x (torch.tensor): input tensor
          eps (float, optional): lower bound. Defaults to 1e-04.
  
      Returns:
          torch.tensor: :math:`log(x)`
      """
      clamped_x = torch.clamp(x, min=eps)
      return torch.log(clamped_x)
  
imports: from typing import List, Tuple
  import torch
  import torch.nn.functional
  from torch import nn
  from tqdm.auto import tqdm
  from TTS.tts.layers.tacotron.common_layers import Linear
  from TTS.tts.layers.tacotron.tacotron2 import ConvBNBlock
label_desc: Use image node_id 3 for calling the OverflowUtils obj's underlying member method code with example usage: obj.log_clamped(x, eps) and returns: torch