def encode(self, x, seq_len_x, z):
x_embed = self.src_embed(x)
if "init_encoder" in self.feed_z_method:
hidden = tile_rnn_hidden(self.encoder_init_layer(z),
self.encoder.rnn)
else:
hidden = None
return self.encoder(x_embed, seq_len_x, hidden=hidden)
def run_language_model(self, x, z):
"""
Runs the language_model.
:param x: unembedded source sentence
:param z: a sample of the latent variable
"""
hidden = tile_rnn_hidden(self.lm_init_layer(z),
self.language_model.rnn)
return self.language_model(x, hidden=hidden)
def encode(self, x, seq_len_x, z):
x_embed = self.src_embed(x)
hidden = tile_rnn_hidden(self.encoder_init_layer(z), self.encoder.rnn)
return self.encoder(x_embed, seq_len_x, hidden=hidden)
def init(self, z):
hidden = tile_rnn_hidden(self.init_layer(z), self.rnn)
return hidden