Question about Synthetic Data Experiment

[geek-ai]

Question about Synthetic Data Experiment

[Yaoming95]

For question 1, we use the same settings in Oracle. We use the same seed to ensure they share the same parameters. As the code denotes:
` self.Wi = tf.Variable(tf.random_normal([self.emb_dim, self.hidden_dim], 0.0, 1000000.0, seed=111))
self.Ui = tf.Variable(tf.random_normal([self.hidden_dim, self.hidden_dim], 0.0, 1000000.0, seed=211))
self.bi = tf.Variable(tf.random_normal([self.hidden_dim, ], 0.0, 1000000.0, seed=311))

    self.Wf = tf.Variable(tf.random_normal([self.emb_dim, self.hidden_dim], 0.0, 1000000.0, seed=114))
    self.Uf = tf.Variable(tf.random_normal([self.hidden_dim, self.hidden_dim], 0.0, 1000000.0, seed=115))
    self.bf = tf.Variable(tf.random_normal([self.hidden_dim, ], 0.0, 1000000.0, seed=116))

    self.Wog = tf.Variable(tf.random_normal([self.emb_dim, self.hidden_dim], 0.0, 1000000.0, seed=997))
    self.Uog = tf.Variable(tf.random_normal([self.hidden_dim, self.hidden_dim], 0.0, 1000000.0, seed=998))
    self.bog = tf.Variable(tf.random_normal([self.hidden_dim, ], 0.0, 1000000.0, seed=999))

    self.Wc = tf.Variable(tf.random_normal([self.emb_dim, self.hidden_dim], 0.0, 1000000.0, seed=110))
    self.Uc = tf.Variable(tf.random_normal([self.hidden_dim, self.hidden_dim], 0.0, 1000000.0, seed=111))
    self.bc = tf.Variable(tf.random_normal([self.hidden_dim, ], 0.0, 1000000.0, seed=112))`

The only difference in every run is that maybe they do not generate exactly the same training data.

For question 2, for some parameters, we use the one provided by the author (for example, SeqGAN). For some hyperparameter which is shared by different models, we use the parameters in the repo, for example, hyperparameter of CNN as the discriminator. This is because we want to provide a fair comparison environment.

[optimass]

Ok this is really helpful thank you!