class_docstr: A Layer that adds learnable Noise to some previous layer's outputs.
  
  Consists of:
  - a common dense layer: y = w^{T}x + b
  - a noisy layer: y = (w + \epsilon_w*\sigma_w)^{T}x +
      (b+\epsilon_b*\sigma_b)
  , where \epsilon are random variables sampled from factorized normal
  distributions and \sigma are trainable variables which are expected to
  vanish along the training procedure.
code: def _f_epsilon(self, x: TensorType) -> TensorType:
      return torch.sign(x) * torch.pow(torch.abs(x), 0.5)
  
file_path: ray/python/ray/rllib/models/torch/modules/noisy_layer.py
imports: import numpy
  from ray.rllib.models.utils import get_activation_fn
  from ray.rllib.utils.framework import try_import_torch, TensorType
label_desc: Use image node_id 3 for calling the NoisyLayer obj's underlying member method code with example usage: obj._f_epsilon(x) and returns: unknown