code: def inference(self, user_id):
      user_vec = self.user_latent_factor(user_id)
      logit = tf.squeeze(
          self.mlp(
              tf.expand_dims(user_vec, 1)
              * self.item_latent_factor.variables[0]
          ),
          axis=-1,
      ) + tf.reshape(self.item_bias.variables[0], [-1])
      return logit
  
file_path: openrec/openrec/tf2/recommenders/gmf.py
imports: import tensorflow
  from tensorflow.keras import Model
  from openrec.tf2.modules import LatentFactor, MLP
label_desc: Use image node_id 3 for calling the GMF obj's underlying member method code with example usage: obj.inference(user_id) and returns: logit