Arhitectura encoder-decoder

Traducere automată cu Keras

Thushan Ganegedara

Data Scientist and Author

Model encoder-decoder

Model de traducere automată

Encoder și decoder

Analogie encoder

Analogie decoder

Text inversat cu encoder-decoder

def words2onehot(word_list, word2index):
  word_ids = [word2index[w] for w in word_list]
  onehot = to_categorical(word_ids, 3)
  return onehot

def encoder(onehot):
  word_ids = np.argmax(onehot, axis=1)
  return word_ids

onehot = words2onehot(["I", "like", "cats"], word2index)
context = encoder(onehot)
print(context)

[0, 1, 2]

def decoder(context_vector):
  word_ids_rev = context_vector[::-1]
  onehot_rev = to_categorical(word_ids_rev, 3)
  return onehot_rev

def onehot2words(onehot, index2word):
  ids = np.argmax(onehot, axis=1)
  return [index2word[id] for id in ids]

onehot_rev = decoder(context)
reversed_words = onehot2words(onehot_rev, index2word)

print(reversed_words)

['cats', 'like', 'I']

Traducere automată cu Keras