class_docstr: Layer to calibrate the model outputs.
  
  The class implements the heuristics described in :cite:`calibration`,
  using Platt scaling :cite:`platt1999probabilistic`.
  
  See the docs of :meth:`~ampligraph.latent_features.models.ScoringBasedEmbeddingModel.calibrate()` for more details.
docstr: Build method.
docstr_tok: ["Build","method","."]
code: def build(self, input_shape):
      """
      Build method.
      """
      self.calib_w = self.add_weight(
          "calib_w",
          shape=(),
          initializer=self.w_init,
          dtype=tf.float32,
          trainable=True,
      )
  
      self.calib_b = self.add_weight(
          "calib_b",
          shape=(),
          initializer=self.b_init,
          dtype=tf.float32,
          trainable=True,
      )
      self.built = True
  
imports: import tensorflow
label_desc: Use image node_id 3 for calling the CalibrationLayer obj's underlying member method code with example usage: obj.build(input_shape) without return types