def elmo_2x2048_256_2048cnn_1xhighway(dataset_name=None, pretrained=False, ctx=mx.cpu(),<EOL>root=os.path.join(get_home_dir(), '<STR_LIT>'), **kwargs):
predefined_args = {'<STR_LIT>': '<STR_LIT>',<EOL>'<STR_LIT>': <NUM_LIT>,<EOL>'<STR_LIT>': [[<NUM_LIT:1>, <NUM_LIT:32>], [<NUM_LIT:2>, <NUM_LIT:32>], [<NUM_LIT:3>, <NUM_LIT:64>], [<NUM_LIT:4>, <NUM_LIT>],<EOL>[<NUM_LIT:5>, <NUM_LIT>], [<NUM_LIT:6>, <NUM_LIT>], [<NUM_LIT:7>, <NUM_LIT>]],<EOL>'<STR_LIT>': <NUM_LIT:16>,<EOL>'<STR_LIT>': <NUM_LIT:1>,<EOL>'<STR_LIT>': '<STR_LIT:relu>',<EOL>'<STR_LIT>': <NUM_LIT:50>,<EOL>'<STR_LIT>': <NUM_LIT>,<EOL>'<STR_LIT>': <NUM_LIT>,<EOL>'<STR_LIT>': <NUM_LIT>,<EOL>'<STR_LIT>': <NUM_LIT:2>,<EOL>'<STR_LIT>': <NUM_LIT:3>,<EOL>'<STR_LIT>': <NUM_LIT:3>,<EOL>'<STR_LIT>': True}<EOL>assert all((k not in kwargs) for k in predefined_args),'<STR_LIT>'<EOL>predefined_args.update(kwargs)<EOL>return _get_elmo_model(ELMoBiLM, '<STR_LIT>', dataset_name, pretrained,<EOL>ctx, root, **predefined_args)<EOL>
r"""ELMo 2-layer BiLSTM with 2048 hidden units, 256 projection size, 1 highway layer.

    Parameters
    ----------
    dataset_name : str or None, default None
        The dataset name on which the pre-trained model is trained.
        Options are 'gbw'.
    pretrained : bool, default False
        Whether to load the pre-trained weights for model.
    ctx : Context, default CPU
        The context in which to load the pre-trained weights.
    root : str, default '$MXNET_HOME/models'
        Location for keeping the model parameters.
        MXNET_HOME defaults to '~/.mxnet'.

    Returns
    -------
    gluon.Block