580fc161b180d6f0d80721524f7f4ce3d815a9ae,examples/wrap_pytorch_rnn.py,,,#,36

Before Change

        // Calculate dY and dX using get_dX callback

if __name__ == "__main__":
    plac.call(main)

After Change

        else:
            return autograd.Variable(weight.new(num_layers, batch_size, hidden_size).zero_())

if __name__ == "__main__":
    for rnn in ["RNN", "GRU", "LSTM"]:
        for bi in [False, True]:
            test_title = "Using {bidirectional}{rnn_type}".format(
                rnn_type=rnn, 
                bidirectional="Bi-" if bi else "")
            print(test_title)
            test_rnn(rnn_type=rnn, bidirectional=bi)

Instances