如何将F1分数与Keras模型结合使用?

由于某些原因,我在尝试使用Keras模型指定f1分数时收到错误消息:

model.compile(optimizer='adam', loss='mse', metrics=['accuracy', 'f1_score'])

我发现这个错误:

ValueError: Unknown metric function:f1_score

在我使用“model”的同一个文件中提供“f1\u score”功能后。编译如下:

def f1_score(y_true, y_pred):

    # Count positive samples.
    c1 = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))
    c2 = K.sum(K.round(K.clip(y_pred, 0, 1)))
    c3 = K.sum(K.round(K.clip(y_true, 0, 1)))

    # If there are no true samples, fix the F1 score at 0.
    if c3 == 0:
        return 0

    # How many selected items are relevant?
    precision = c1 / c2

    # How many relevant items are selected?
    recall = c1 / c3

    # Calculate f1_score
    f1_score = 2 * (precision * recall) / (precision + recall)
    return f1_score 

model.compile(optimizer='adam', loss='mse', metrics=['accuracy', f1_score])

model.save(model_path) # works ok

然而,将其加载到另一个程序中:

from keras import models 
model = models.load_model(model_path)