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,
