def run_tests(): import problem_unittests as t t.test_decoding_layer(decoding_layer) t.test_decoding_layer_infer(decoding_layer_infer) t.test_decoding_layer_train(decoding_layer_train) t.test_encoding_layer(encoding_layer) t.test_model_inputs(model_inputs) t.test_process_encoding_input(process_decoder_input) t.test_sentence_to_seq(sentence_to_seq) t.test_seq2seq_model(seq2seq_model) t.test_text_to_ids(text_to_ids)
def run_all_tests(): tests.test_text_to_ids(text_to_ids) check_tensorflow_gpu() tests.test_model_inputs(model_inputs) tests.test_process_encoding_input(process_decoder_input) from imp import reload reload(tests) tests.test_encoding_layer(encoding_layer) tests.test_decoding_layer_train(decoding_layer_train) tests.test_decoding_layer_infer(decoding_layer_infer) tests.test_decoding_layer(decoding_layer) tests.test_seq2seq_model(seq2seq_model) tests.test_sentence_to_seq(sentence_to_seq)
dec_input = process_decoding_input(target_data, target_vocab_to_int, batch_size) dec_embeddings = tf.Variable( tf.random_uniform([target_vocab_size, dec_embedding_size])) dec_embed_input = tf.nn.embedding_lookup(dec_embeddings, dec_input) training_logits, inference_logits = decoding_layer( dec_embed_input, dec_embeddings, encoding_state, target_vocab_size, sequence_length, rnn_size, num_layers, target_vocab_to_int, keep_prob) return training_logits, inference_logits """ DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE """ tests.test_seq2seq_model(seq2seq_model) # ## 训练神经网络 # # ### 超参数 # # 调试以下参数: # # - 将 `epochs` 设为 epoch 次数。 # - 将 `batch_size` 设为批次大小。 # - 将 `rnn_size` 设为 RNN 的大小。 # - 将 `num_layers` 设为层级数量。 # - 将 `encoding_embedding_size` 设为编码器嵌入大小。 # - 将 `decoding_embedding_size` 设为解码器嵌入大小 # - 将 `learning_rate` 设为训练速率。 # - 将 `keep_probability` 设为丢弃保留率(Dropout keep probability)。