def __init__(self, input_size, hidden_size):
super(GRU, self).__init__()
self.input_size = input_size
self.hidden_size = hidden_size
self.weight_i, self.weight_h, self.bias_i, self.bias_h = gru_default_state(
self.input_size, self.hidden_size)
self.rnn = P.DynamicGRUV2()
self.cast = P.Cast()
def __init__(self, config, is_training=True):
super(GRU, self).__init__()
if is_training:
self.batch_size = config.batch_size
else:
self.batch_size = config.eval_batch_size
self.hidden_size = config.hidden_size
self.weight_i, self.weight_h, self.bias_i, self.bias_h = \
gru_default_state(self.batch_size, self.hidden_size, self.hidden_size)
self.rnn = P.DynamicGRUV2()
self.cast = P.Cast()
def __init__(self):
super(DynamicGRUV2, self).__init__()
self.dynamic_gru = P.DynamicGRUV2()