# hidden_size = 100 num_layer = 3 layer = mx.gluon.rnn.GRU(100, 3) layer.initialize() # seq_len = 5 batch_size = 3 input_size = 10 input = mx.nd.random.uniform(shape=(5, 3, 10)) # by default zeros are used as begin state output = layer(input) # manually specify begin state. # num_layers = 6 batch_size = 3 num_hidden = 128 h0 = mx.nd.random.uniform(shape=(3, 3, 100)) output, hn = layer(input, h0)