def _create_network(self, input_view, input_feature, use_conv=True):
        """define computation graph of network

        Parameters
        ----------
        input_view: mx.symbol
        input_feature: mx.symbol
            the input tensor
        """
        kernel_num = [32, 32]
        hidden_size = [256]

        if use_conv:
            input_view = mx.sym.transpose(data=input_view, axes=[0, 3, 1, 2])
            h_conv1 = mx.sym.Convolution(data=input_view, kernel=(3, 3),
                                         num_filter=kernel_num[0], layout="NCHW")
            h_conv1 = mx.sym.Activation(data=h_conv1, act_type="relu")
            h_conv2 = mx.sym.Convolution(data=h_conv1, kernel=(3, 3),
                                         num_filter=kernel_num[1], layout="NCHW")
            h_conv2 = mx.sym.Activation(data=h_conv2, act_type="relu")
        else:
            input_view = mx.sym.flatten(data=input_view)
            h_conv2 = mx.sym.FullyConnected(input_view, num_hidden=hidden_size[0])
            h_conv2 = mx.sym.Activation(data=h_conv2, act_type="relu")

        flatten_view = mx.sym.flatten(data=h_conv2)
        h_view = mx.sym.FullyConnected(data=flatten_view, num_hidden=hidden_size[0])
        h_view = mx.sym.Activation(data=h_view, act_type="relu")

        h_emb = mx.sym.FullyConnected(data=input_feature, num_hidden=hidden_size[0])
        h_emb = mx.sym.Activation(data=h_emb, act_type="relu")

        dense = mx.sym.concat(h_view, h_emb)

        if self.use_dueling:
            # state value
            value = mx.sym.FullyConnected(data=dense, num_hidden=1)
            advantage = mx.sym.FullyConnected(data=dense, num_hidden=self.num_actions)

            mean = mx.sym.mean(advantage, axis=1, keepdims=True)
            advantage = mx.sym.broadcast_sub(advantage, mean)
            qvalues = mx.sym.broadcast_add(advantage, value)
        else:
            qvalues = mx.sym.FullyConnected(data=dense, num_hidden=self.num_actions)

        return qvalues
define computation graph of network

        Parameters
        ----------
        input_view: mx.symbol
        input_feature: mx.symbol
            the input tensor
        
python/magent/builtin/mx_model/dqn.py