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）。
