Convert a UpSampling layer from mxnet to coreml.

    Parameters
    ----------
    net: network
        A mxnet network object.

    node: layer
        Node to convert.

    module: module
        An module for MXNet

    builder: NeuralNetworkBuilder
        A neural network builder object.

def convert_upsample(net, node, module, builder):
    """Convert a UpSampling layer from mxnet to coreml.

    Parameters
    ----------
    net: network
        A mxnet network object.

    node: layer
        Node to convert.

    module: module
        An module for MXNet

    builder: NeuralNetworkBuilder
        A neural network builder object.
    """
    input_name, output_name = _get_input_output_name(net, node)
    name = node['name']
    param = _get_attr(node)
    inputs = node['inputs']
    args, _ = module.get_params()

    scale = literal_eval(param['scale'])

    #method
    if 'sample_type' in param.keys():
        method = param['sample_type']
        if method == 'nearest':
            mode = 'NN'
        elif method == '':
            mode = 'BILINEAR'

    builder.add_upsample(name, scaling_factor_h=scale, scaling_factor_w=scale,
                         input_name=input_name, output_name=output_name, mode=mode)