Skip to content

Instantly share code, notes, and snippets.

@eileen-code4fun
Created January 21, 2022 05:59
Show Gist options
  • Save eileen-code4fun/6ab41caf94af4f30090c7da2c5519a47 to your computer and use it in GitHub Desktop.
Save eileen-code4fun/6ab41caf94af4f30090c7da2c5519a47 to your computer and use it in GitHub Desktop.
Translation Init
class Spa2EngTranslator(tf.keras.Model):
def __init__(self, eng_text_processor, spa_text_processor, unit=512):
super().__init__()
# Spanish
self.spa_text_processor = spa_text_processor
self.spa_voba_size = len(spa_text_processor.get_vocabulary())
self.spa_embedding = tf.keras.layers.Embedding(
self.spa_voba_size,
output_dim=unit,
mask_zero=True)
self.spa_rnn = tf.keras.layers.Bidirectional(layer=tf.keras.layers.LSTM(int(unit/2), return_sequences=True, return_state=True))
# Attention
self.attention = tf.keras.layers.Attention()
# English
self.eng_text_processor = eng_text_processor
self.eng_voba_size = len(eng_text_processor.get_vocabulary())
self.eng_embedding = tf.keras.layers.Embedding(
self.eng_voba_size,
output_dim=unit,
mask_zero=True)
self.eng_rnn = tf.keras.layers.LSTM(unit, return_sequences=True, return_state=True)
# Output
self.out = tf.keras.layers.Dense(self.eng_voba_size)
def call(self, eng_text, spa_text):
pass
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment