class_docstr: Calculates anaphoricity scores by passing the inputs into a FFNN 
docstr: Calculates anaphoricity scores.
  
  Args:
      x: tensor of shape [batch_size, n_ants, n_features]
  
  Returns:
      tensor of shape [batch_size, n_ants]
docstr_tok: ["Calculates","anaphoricity","scores",".","Args",":","x",":","tensor","of","shape","[","batch_size",",","n_ants",",","n_features","]","Returns",":","tensor","of","shape","[","batch_size",",","n_ants","]"]
code: def _ffnn(self, x: torch.Tensor) -> torch.Tensor:
      """
      Calculates anaphoricity scores.
  
      Args:
          x: tensor of shape [batch_size, n_ants, n_features]
  
      Returns:
          tensor of shape [batch_size, n_ants]
      """
      x = self.out(self.hidden(x))
      return x.squeeze(2)
  
file_path: stanza/stanza/models/coref/anaphoricity_scorer.py
imports: import torch
  from stanza.models.coref import utils
  from stanza.models.coref.config import Config
label_desc: Use image node_id 3 for calling the AnaphoricityScorer obj's underlying member method code with example usage: obj._ffnn(x) and returns: x