Keras clipping custom metric. Adapted from https://neptune.ai/blog/keras-metrics

clip.py

def recall(y_true, y_pred):
    y_true = K.ones_like(y_true) 
    true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))
    all_positives = K.sum(K.round(K.clip(y_true, 0, 1)))
    
    recall = true_positives / (all_positives + K.epsilon())
    return recall

def precision(y_true, y_pred):
    y_true = K.ones_like(y_true) 
    true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))
    
    predicted_positives = K.sum(K.round(K.clip(y_pred, 0, 1)))
    precision = true_positives / (predicted_positives + K.epsilon())
    return precision

def f1_score(y_true, y_pred):
    precision = precision_m(y_true, y_pred)
    recall = recall_m(y_true, y_pred)
    return 2*((precision*recall)/(precision+recall+K.epsilon()))
  

 model.compile(...,metrics=['accuracy', f1_score, precision, recall])