def __init__(self,
size,
tracker_size,
lateral_tracking=True,
tracking_ln=True):
'''Args:
size: input size (parser hidden state) = FLAGS.model_dim
tracker_size: FLAGS.tracking_lstm_hidden_dim
(see FLAGS for the rest)'''
super(Tracker, self).__init__()
# Initialize layers.
if lateral_tracking:
self.buf = Linear()(size, 4 * tracker_size, bias=True)
self.stack1 = Linear()(size, 4 * tracker_size, bias=False)
self.stack2 = Linear()(size, 4 * tracker_size, bias=False)
self.lateral = Linear(initializer=HeKaimingInitializer)(
tracker_size, 4 * tracker_size, bias=False)
self.state_size = tracker_size
else:
self.state_size = size * 3
if tracking_ln:
self.buf_ln = LayerNormalization(size)
self.stack1_ln = LayerNormalization(size)
self.stack2_ln = LayerNormalization(size)
self.lateral_tracking = lateral_tracking
self.tracking_ln = tracking_ln
self.reset_state()
def __init__(self, hidden_dim, composition_ln=False):
super(BinaryTreeLSTMLayer, self).__init__()
self.hidden_dim = hidden_dim
self.comp_linear = Linear(initializer=HeKaimingInitializer)(
in_features=2 * hidden_dim, out_features=5 * hidden_dim)
self.composition_ln = composition_ln
if composition_ln:
self.left_h_ln = LayerNormalization(hidden_dim)
self.right_h_ln = LayerNormalization(hidden_dim)
self.left_c_ln = LayerNormalization(hidden_dim)
self.right_c_ln = LayerNormalization(hidden_dim)