if __name__ == "__main__":
args = docopt(__doc__)
# load test data
with open("data/snli/test.pkl", "rb") as fin:
test = pickle.load(fin)
input_embeddings = np.load("data/snli/input_embeddings.npy")
model = dy.Model()
parsed = False
if args["cyk"]:
net = networks.CYK(
model,
input_embeddings,
update_embeddings=False,
hidden_dim=100,
)
if args["--inv-temp"] is not None:
net.inv_temp = float(args["--inv-temp"])
print("Inverse temperature set to " + str(net.inv_temp))
elif args["ltr-cyk"]:
net = networks.CYK(
model,
input_embeddings,
update_embeddings=False,
hidden_dim=100,
order=1,
)
elif args["rtl-cyk"]:
net = networks.CYK(
return np.median(ranks), accuracy10, accuracy100
if __name__ == "__main__":
args = docopt(__doc__)
model = dy.Model()
update_embeddings = bool(args["--update-embeddings"])
input_embeddings = np.load("data/dicteval/input_embeddings.reduced.npy")
hidden_dim = 256
parsed = False
if args["cyk"]:
net = networks.CYK(
model,
input_embeddings,
update_embeddings = update_embeddings,
hidden_dim = hidden_dim,
)
elif args["ltr-cyk"]:
net = networks.CYK(
model,
input_embeddings,
update_embeddings = update_embeddings,
hidden_dim = hidden_dim,
order = 1,
)
elif args["rtl-cyk"]:
net = networks.CYK(
model,
input_embeddings,
update_embeddings = update_embeddings,
args = docopt(__doc__)
# load the embeddings and vocab
embeddings = np.load("data/snli2/input_embeddings.npy")
vocab = []
with open("data/snli2/input_vocab.txt") as fin:
for line in fin:
vocab.append(line.strip().split("\t")[0])
bacov = {n: i for i, n in enumerate(vocab)}
dim = embeddings.shape[1]
# initialise and restore the model
model = dy.Model()
net = networks.CYK(
model,
embeddings,
update_embeddings = False,
hidden_dim = 100,
)
model.load(args["<model-file>"])
net.inv_temp = float(args["--inv-temp"])
while True:
try:
words = list(map(lambda x: cleanup(x), input("Sentence: ").split(" ")))
indices = [bacov[w] for w in words if w in bacov]
n = len(indices)
_, weights = net(np.reshape(indices, (n, 1)), )
tree = build_subtree(weights, words)
tree.render("/home/jm864/public_html/graphviz.gv", view = False)
except (EOFError, ValueError):
break