def save_features()

in save_features.py [0:0]

• 20 lines of code
• 4 McCabe index (conditional complexity)

def save_features(model, data_loader, outfile ):

    f = h5py.File(outfile, 'w')
    max_count = len(data_loader)*data_loader.batch_size
    all_labels = f.create_dataset('all_labels',(max_count,), dtype='i')
    all_feats=None
    count=0
    for i, (x,y) in enumerate(data_loader):
        if i%10 == 0:
            print('{:d}/{:d}'.format(i, len(data_loader)))
        x = x.cuda()
        x_var = Variable(x)
        scores, feats = model(x_var)
        if all_feats is None:
            all_feats = f.create_dataset('all_feats', (max_count, feats.size(1)), dtype='f')
        all_feats[count:count+feats.size(0),:] = feats.data.cpu().numpy()
        all_labels[count:count+feats.size(0)] = y.cpu().numpy()
        count = count + feats.size(0)

    count_var = f.create_dataset('count', (1,), dtype='i')
    count_var[0] = count

    f.close()