Evaluate Keras model with scikit-learn metrics
You could use class KerasClassifier from keras.wrappers.scikit_learn, which wraps a Keras model in a scikit-learn interface, so that it can be used like other scikit-learn models and then you could evaluate it with scikit-learn's scoring functions, e.g.:

from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.metrics import roc_curve, auc

keras_model = ...
classifier = KerasClassifier(keras_model, batch_size=32)
y_pred_keras = classifier.predict(X_test).ravel()
fpr, tpr, thresholds = roc_curve(y_test, y_pred_keras)
auc_score = auc(fpr, tpr)


You can find more info on the Keras docs, or googling around (e.g. this and this).