Created
January 21, 2022 05:59
-
-
Save eileen-code4fun/6ab41caf94af4f30090c7da2c5519a47 to your computer and use it in GitHub Desktop.
Translation Init
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
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