LSTM code details

[chen-judge]

In LSTM code, I notice that 'To run the LSTM code, first extract the features using the TSN trained models' Actually, I can't understand how to use this code. Can you provide some details or some h5/pkl files mentiond below?

def read_data(data_dir):
    if osp.exists(args.data_dir + '_val_feats.h5'):
        print('This looks like TSN outputs, reading it so.')
        val_data = read_data_tsn(args.data_dir + '_val_feats.h5')
        train_data = read_data_tsn(args.data_dir + '_train_feats.h5')
    elif osp.exists(osp.join(
            args.data_dir, 'results_probs_test_fullLbl.pkl')):
        print('This looks like NL outputs, reading it so.')
        assert args.lbl_dir is not None, (
            'lbl_dir must be set for NL models, since the labels are not '
            'stored in the PKL file.')
        val_data = read_data_nl(
            osp.join(args.data_dir, 'results_probs_test_fullLbl.pkl'),
            osp.join(args.lbl_dir, 'val.txt'))
        train_data = read_data_nl(
            osp.join(args.data_dir, 'results_probs_train_fullLbl.pkl'),
            osp.join(args.lbl_dir, 'train.txt'))
    else:
        raise NotImplementedError('Dunno how to read data directory {}'.format(
            data_dir))
    return train_data, val_data

Thanks!

[rohitgirdhar]

The instructions are here.