def setUp(self):
in_size, out_size = 10, 8
self.link = links.StatefulZoneoutLSTM(in_size, out_size)
self.c = chainer.Variable(
numpy.random.uniform(-1, 1, (1, out_size)).astype(numpy.float32))
self.h = chainer.Variable(
numpy.random.uniform(-1, 1, (1, out_size)).astype(numpy.float32))
def __init__(self, n_in, n_hid, n_out):
links = []
links.append(
L.StatefulZoneoutLSTM(n_in, n_hid, c_ratio=.05, h_ratio=.05))
links.append(L.Linear(None, n_out))
self.n_out = n_out
super(RNN, self).__init__(*links)
def __init__(self, n_units, n_out, layers=2, c_ratio=0.5, h_ratio=0.5):
super(ZoneoutLSTM, self).__init__()
self.layers = layers
with self.init_scope():
for l in range(layers):
setattr(self, "layer_{}".format(l),
L.StatefulZoneoutLSTM(None, n_units, c_ratio, h_ratio))
self.out = L.Linear(None, n_out)
def setUp(self):
self.link = links.StatefulZoneoutLSTM(self.in_size, self.out_size,
c_ratio=self.c_ratio,
h_ratio=self.h_ratio)
upward = self.link.upward.W.data
upward[...] = numpy.random.uniform(-1, 1, upward.shape)
lateral = self.link.lateral.W.data
lateral[...] = numpy.random.uniform(-1, 1, lateral.shape)
c_shape = (4, self.out_size)
h_shape = (4, self.out_size)
x_shape = (4, self.in_size)
gy_shape = (4, self.out_size)
self.c = numpy.zeros(c_shape).astype(numpy.float32)
self.h = numpy.zeros(h_shape).astype(numpy.float32)
self.x = numpy.random.uniform(-1, 1, x_shape).astype(numpy.float32)
self.gy = numpy.random.uniform(-1, 1, gy_shape).astype(numpy.float32)
def setUp(self):
in_size, out_size = 10, 8
self.link = links.StatefulZoneoutLSTM(in_size, out_size)
