class_docstr: Implementation of a leanable sigmoid.
  
  Arguments
  ---------
  in_features : int
      Input dimensionality
class_docstr_tok: ["Implementation","of","a","leanable","sigmoid",".","Arguments","--","--","--","--","-","in_features",":","int","Input","dimensionality"]
docstr: Processes the input tensor x and returns an output tensor.
docstr_tok: ["Processes","the","input","tensor","x","and","returns","an","output","tensor","."]
code: def forward(self, x):
      """Processes the input tensor x and returns an output tensor."""
      return 1.2 * torch.sigmoid(self.slope * x)
  
file_path: speechbrain/speechbrain/lobes/models/MetricGAN.py
imports: import torch
  import speechbrain
  from torch import nn
  from torch.nn.utils import spectral_norm
label_desc: Use image node_id 2 for calling the Learnable_sigmoid obj's underlying member method code with example usage: obj.forward(x) and returns: unknown