2018-10-10-serialization-issue.py

import mxnet as mx

class MyBlock(mx.gluon.HybridBlock):
    def __init__(self):
        super().__init__()
        with self.name_scope():
            self.lstm = mx.gluon.rnn.HybridSequentialRNNCell()
            for layer in range(3):
                self.lstm.add(mx.gluon.rnn.LSTMCell(hidden_size=20))

    def hybrid_forward(self, F, seq):
        outputs, state = self.lstm.unroll(inputs=seq, length=10, layout="NTC", merge_outputs=True)
        return outputs

block = MyBlock()
block.initialize()
block.hybridize()

input = mx.nd.random_normal(shape=(32, 10, 5))
output = block(input)

block.export(path="./model", epoch=0)
symbol = mx.gluon.SymbolBlock.imports(
    symbol_file="./model-symbol.json",
    input_names=[f"data"],
    param_file="./model-0000.params",
    ctx=mx.Context.default_ctx
)