class_docstr: This network takes current state and previous observed values as input
  and returns its parameters, mean, standard deviation and probability
  of transition to the next state
class_docstr_tok: ["This","network","takes","current","state","and","previous","observed","values","as","input","and","returns","its","parameters",",","mean",",","standard","deviation","and","probability","of","transition","to","the","next","state"]
docstr: It clamps the standard deviation to not to go below some level
  This removes the problem when the model tries to cheat for higher likelihoods by converting
  one of the gaussians to a point mass.
  
  Args:
      std (float Tensor): tensor containing the standard deviation to be
docstr_tok: ["It","clamps","the","standard","deviation","to","not","to","go","below","some","level","This","removes","the","problem","when","the","model","tries","to","cheat","for","higher","likelihoods","by","converting","one","of","the","gaussians","to","a","point","mass",".","Args",":","std","(","float","Tensor",")",":","tensor","containing","the","standard","deviation","to","be"]
code: def _floor_std(self, std):
      r"""
      It clamps the standard deviation to not to go below some level
      This removes the problem when the model tries to cheat for higher likelihoods by converting
      one of the gaussians to a point mass.
  
      Args:
          std (float Tensor): tensor containing the standard deviation to be
      """
      original_tensor = std.clone().detach()
      std = torch.clamp(std, min=self.std_floor)
      if torch.any(original_tensor != std):
          print(
              "[*] Standard deviation was floored! The model is preventing overfitting, nothing serious to worry about"
          )
      return std
  
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 Outputnet obj's underlying member method code with example usage: obj._floor_std(std) and returns: std