Есть ли прямая замена для tf.contrib.layers.embed_sequence в TF 2.0 - PullRequest
0 голосов
/ 06 мая 2020

Я пытаюсь вручную перенести свой python код с 1.0 на 2.0 в некоторых частях. И я не могу найти способ обновить эту часть моего кода:

def seq2seq_model(inputs, targets, keep_prob, batch_size, sequence_length, answers_num_words, questions_num_words, encoder_embedding_size, decoder_embedding_size, rnn_size, num_layers, questionswords2int):
encoder_embedded_input = tf.contrib.layers.embed_sequence(inputs,
                                                          answers_num_words + 1,
                                                          encoder_embedding_size,
                                                          initializer = tf.random_uniform_initializer(0, 1))
encoder_state = encoder_rnn(encoder_embedded_input, rnn_size, num_layers, keep_prob, sequence_length)
preprocessed_targets = preprocess_targets(targets, questionswords2int, batch_size)
decoder_embeddings_matrix = tf.Variable(tf.random_uniform([questions_num_words + 1, decoder_embedding_size], 0, 1))
decoder_embedded_input = tf.nn.embedding_lookup(decoder_embeddings_matrix, preprocessed_targets)
training_predictions, test_predictions = decoder_rnn(decoder_embedded_input,
                                                     decoder_embeddings_matrix,
                                                     encoder_state,
                                                     questions_num_words,
                                                     sequence_length,
                                                     rnn_size,
                                                     num_layers,
                                                     questionswords2int,
                                                     keep_prob,
                                                     batch_size)
return training_predictions, test_predictions
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