keras_utils.py 文件源码

def test_data_ann_rnn(feats, target, groups, ann, rnn):
    """
    mode = 'scores' or 'preds'
    take two ready trained models (cnn+rnn)
    test on input data and return acc+f1
    """
    if target.ndim==2: target = np.argmax(target,1)



    cnn_pred = ann.predict_classes(feats, 1024, verbose=0)

    cnn_acc = accuracy_score(target, cnn_pred)
    cnn_f1  = f1_score(target, cnn_pred, average='macro')

    seqlen = rnn.input_shape[1]
    features_seq, target_seq, groups_seq = tools.to_sequences(feats, target, seqlen=seqlen, groups=groups)
    new_targ_seq = np.roll(target_seq, 4)
    rnn_pred = rnn.predict_classes(features_seq, 1024, verbose=0)
    rnn_acc = accuracy_score(new_targ_seq, rnn_pred)
    rnn_f1  = f1_score(new_targ_seq,rnn_pred, average='macro')
    confmat = confusion_matrix(new_targ_seq, rnn_pred)
    return [cnn_acc, cnn_f1, rnn_acc, rnn_f1, confmat, (rnn_pred, target_seq, groups_seq)]