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)
Preprocess target data for encoding :param target_data: Target Placehoder :param target_vocab_to_int: Dictionary to go from the target words to an id :param batch_size: Batch Size :return: Preprocessed target data """ x = tf.strided_slice(target_data, [0, 0], [batch_size, -1], [1, 1]) y = tf.concat([tf.fill([batch_size, 1], target_vocab_to_int['<GO>']), x], 1) return y """ DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE """ tests.test_process_encoding_input(process_decoder_input) # ### Encoding # Implement `encoding_layer()` to create a Encoder RNN layer: # * Embed the encoder input using [`tf.contrib.layers.embed_sequence`](https://www.tensorflow.org/api_docs/python/tf/contrib/layers/embed_sequence) # * Construct a [stacked](https://github.com/tensorflow/tensorflow/blob/6947f65a374ebf29e74bb71e36fd82760056d82c/tensorflow/docs_src/tutorials/recurrent.md#stacking-multiple-lstms) [`tf.contrib.rnn.LSTMCell`](https://www.tensorflow.org/api_docs/python/tf/contrib/rnn/LSTMCell) wrapped in a [`tf.contrib.rnn.DropoutWrapper`](https://www.tensorflow.org/api_docs/python/tf/contrib/rnn/DropoutWrapper) # * Pass cell and embedded input to [`tf.nn.dynamic_rnn()`](https://www.tensorflow.org/api_docs/python/tf/nn/dynamic_rnn) # In[9]: from imp import reload reload(tests) def encoding_layer(rnn_inputs, rnn_size, num_layers, keep_prob, source_sequence_length, source_vocab_size,