def test_seq_length(self):
tokens = '<unk> a b c'.split()
unk = '<unk>'
vocab = VocabExample(tokens, unk)
sequences = [
'a b a b c'.split(), # more than length 4
'a b'.split(),
['b'],
['c'],
]
indices = np.array([
[2, 1, 2, 3],
[0, 0, 1, 2],
[0, 0, 0, 2],
[0, 0, 0, 3],
], dtype=np.int32)
mask = np.array([
[1, 1, 1, 1],
[0, 0, 1, 1],
[0, 0, 0, 1],
[0, 0, 0, 1],
], dtype=np.float32)
with clean_session():
model = FeedSequenceBatch(align='right', seq_length=4)
test_feed = model.inputs_to_feed_dict(sequences, vocab)
correct = {model.values: indices, model.mask: mask}
assert_array_collections_equal(correct, test_feed)
indices = tf.identity(model.values)
mask = tf.identity(model.mask)
assert indices.get_shape().as_list() == [None, 4]
assert mask.get_shape().as_list() == [None, 4]
def test_right_align(self, inputs):
indices = np.array([
[1, 1, 2, 2, 3],
[0, 0, 0, 1, 2],
[0, 0, 0, 0, 2],
[0, 0, 0, 0, 3],
], dtype=np.int32)
mask = np.array([
[1, 1, 1, 1, 1],
[0, 0, 0, 1, 1],
[0, 0, 0, 0, 1],
[0, 0, 0, 0, 1],
], dtype=np.float32)
with clean_session():
model = FeedSequenceBatch(align='right')
correct = {model.values: indices, model.mask: mask}
args, kwargs = inputs
test = model.inputs_to_feed_dict(*args, **kwargs)
assert_array_collections_equal(correct, test)