# value definition
tree_matrix = np.asarray([
[3, 1, 2],
[4, 0, 3],
], dtype=np.int32)
phrase_number = tree_matrix.shape[0]
labels = np.asarray([2, 4, 2, 4, 4], dtype=np.int32)
x = T.imatrix('x')
y = T.ivector('y')
classifier = RNTN(
x,
y,
vocab_size=5,
embed_dim=3,
label_n=5,
)
x_input = np.asarray([[1, -1, -1], [2, -1, -1], [3, 1, 2]], dtype=np.int32)
y_input = labels[1:4]
original_embedding = classifier.embedding.get_value()
classifier.update_embedding(x_input)
new_embedding = classifier.embedding.get_value()
assert_matrix_neq(original_embedding, new_embedding, "update_embeding")
