def _add_word_level_context_encoder(self):
# en_es
self.en_es_word_level_encoder = bilstm_layer(
inputs=self.en_es_word_embedded,
inputs_length=self.en_es_word_length_input,
hidden_dim=self.config.context_hidden_dim,
keep_prob=self.keep_prob,
layers=self.config.word_layers,
name_scope='en_es_word_level_bi_lstm')
# es_en
self.es_en_word_level_encoder = bilstm_layer(
inputs=self.es_en_word_embedded,
inputs_length=self.es_en_word_length_input,
hidden_dim=self.config.context_hidden_dim,
keep_prob=self.keep_prob,
layers=self.config.word_layers,
name_scope='es_en_word_level_bi_lstm')
# fr_en
self.fr_en_word_level_encoder = bilstm_layer(
inputs=self.fr_en_word_embedded,
inputs_length=self.fr_en_word_length_input,
hidden_dim=self.config.context_hidden_dim,
keep_prob=self.keep_prob,
layers=self.config.word_layers,
name_scope='fr_en_word_level_bi_lstm')
def _add_word_level_context_encoder(self):
# word embedding
self.word_level_encoder = bilstm_layer(
inputs=self.word_embedded,
inputs_length=self.word_length_input,
hidden_dim=self.config.context_hidden_dim,
keep_prob=self.keep_prob,
layers=self.config.word_layers,
name_scope='word_level_bi_lstm'
)
def _add_char_level_cnn_context_encoder(self):
# en_es
en_es_char_cnn_encoder = self.cnn(name_scope='en_es_char_cnn',
char_embedded=tf.nn.embedding_lookup(
self.en_es_char_embedding,
self.en_es_chars))
self.en_es_char_cnn_context_encoder = bilstm_layer(
inputs=en_es_char_cnn_encoder,
inputs_length=self.en_es_word_length_input,
hidden_dim=self.config.context_hidden_dim,
keep_prob=self.keep_prob,
layers=self.config.char_cnn_bilstm_layers,
name_scope='en_es_char_level_cnn_bi_lstm')
# es_en
es_en_char_cnn_encoder = self.cnn(name_scope='es_en_char_cnn',
char_embedded=tf.nn.embedding_lookup(
self.es_en_char_embedding,
self.es_en_chars))
self.es_en_char_cnn_context_encoder = bilstm_layer(
inputs=es_en_char_cnn_encoder,
inputs_length=self.es_en_word_length_input,
hidden_dim=self.config.context_hidden_dim,
keep_prob=self.keep_prob,
layers=self.config.char_cnn_bilstm_layers,
name_scope='es_en_char_level_cnn_bi_lstm')
# fr_en
fr_en_char_cnn_encoder = self.cnn(name_scope='fr_en_char_cnn',
char_embedded=tf.nn.embedding_lookup(
self.fr_en_char_embedding,
self.fr_en_chars))
self.fr_en_char_cnn_context_encoder = bilstm_layer(
inputs=fr_en_char_cnn_encoder,
inputs_length=self.fr_en_word_length_input,
hidden_dim=self.config.context_hidden_dim,
keep_prob=self.keep_prob,
layers=self.config.char_cnn_bilstm_layers,
name_scope='fr_en_char_level_cnn_bi_lstm')
def _add_char_level_lstm_context_encoder(self):
self.chars = tf.reshape(self.char_input, [-1, self.config.char_max_len])
char_len = tf.reshape(self.char_length_input, [-1, ])
self.char_embedding = tf.get_variable(name='char_embedding',
shape=[self.config.char_size_dic[self.config.data_set],
self.config.char_embedding_dim],
initializer=tf.contrib.layers.xavier_initializer())
char_lstm_encoder = self.char_lstm(name_scope='char_lstm',
char_embedded=tf.nn.embedding_lookup(self.char_embedding,
self.chars),
char_len=char_len
)
self.char_lstm_context_encoder = bilstm_layer(
inputs=char_lstm_encoder,
inputs_length=self.word_length_input,
hidden_dim=self.config.context_hidden_dim,
keep_prob=self.keep_prob,
layers=self.config.char_lstm_bilstm_layers,
name_scope='char_level_lstm_bi_lstm'
)
def _add_char_level_lstm_context_encoder(self):
# en_es
self.en_es_chars = tf.reshape(self.en_es_char_input,
[-1, self.config.char_max_len])
en_es_char_len = tf.reshape(self.en_es_char_length_input, [
-1,
])
self.en_es_char_embedding = tf.get_variable(
name='en_es_char_embedding',
shape=[
self.config.char_size_dic['en_es'],
self.config.char_embedding_dim
],
initializer=tf.contrib.layers.xavier_initializer())
en_es_char_lstm_encoder = self.char_lstm(
name_scope='en_es_char_lstm',
char_embedded=tf.nn.embedding_lookup(self.en_es_char_embedding,
self.en_es_chars),
char_len=en_es_char_len)
self.en_es_char_lstm_context_encoder = bilstm_layer(
inputs=en_es_char_lstm_encoder,
inputs_length=self.en_es_word_length_input,
hidden_dim=self.config.context_hidden_dim,
keep_prob=self.keep_prob,
layers=self.config.char_lstm_bilstm_layers,
name_scope='en_es_char_level_lstm_bi_lstm')
# es_en
self.es_en_chars = tf.reshape(self.es_en_char_input,
[-1, self.config.char_max_len])
es_en_char_len = tf.reshape(self.es_en_char_length_input, [
-1,
])
self.es_en_char_embedding = tf.get_variable(
name='es_en_char_embedding',
shape=[
self.config.char_size_dic['es_en'],
self.config.char_embedding_dim
],
initializer=tf.contrib.layers.xavier_initializer())
es_en_char_lstm_encoder = self.char_lstm(
name_scope='es_en_char_lstm',
char_embedded=tf.nn.embedding_lookup(self.es_en_char_embedding,
self.es_en_chars),
char_len=es_en_char_len)
self.es_en_char_lstm_context_encoder = bilstm_layer(
inputs=es_en_char_lstm_encoder,
inputs_length=self.es_en_word_length_input,
hidden_dim=self.config.context_hidden_dim,
keep_prob=self.keep_prob,
layers=self.config.char_lstm_bilstm_layers,
name_scope='es_en_char_level_lstm_bi_lstm')
# fr_en
self.fr_en_chars = tf.reshape(self.fr_en_char_input,
[-1, self.config.char_max_len])
fr_en_char_len = tf.reshape(self.fr_en_char_length_input, [
-1,
])
self.fr_en_char_embedding = tf.get_variable(
name='fr_en_char_embedding',
shape=[
self.config.char_size_dic['fr_en'],
self.config.char_embedding_dim
],
initializer=tf.contrib.layers.xavier_initializer())
fr_en_char_lstm_encoder = self.char_lstm(
name_scope='fr_en_char_lstm',
char_embedded=tf.nn.embedding_lookup(self.fr_en_char_embedding,
self.fr_en_chars),
char_len=fr_en_char_len)
self.fr_en_char_lstm_context_encoder = bilstm_layer(
inputs=fr_en_char_lstm_encoder,
inputs_length=self.fr_en_word_length_input,
hidden_dim=self.config.context_hidden_dim,
keep_prob=self.keep_prob,
layers=self.config.char_lstm_bilstm_layers,
name_scope='fr_en_char_level_lstm_bi_lstm')