为什么我在Keras NN-模型上进行Gridsearch循环？

Question

我有一个与GridSearch keras问题有关的问题，该问题每次以相同的纪元= 25循环吗？不会更改为35。

def build_classifier(optimizer):
    classifier = Sequential()
    classifier.add(Dense(units = 3000, kernel_initializer = 'uniform', activation = 'relu', input_dim = pca_dimensions))
    classifier.add(Dense(units = 3000, kernel_initializer = 'uniform', activation = 'relu'))
    classifier.add(Dense(units = 1, kernel_initializer = 'uniform', activation = 'sigmoid'))
    classifier.compile(optimizer = optimizer, loss = 'binary_crossentropy', metrics = ['accuracy'])
    return classifier

classifier = KerasClassifier(build_fn = build_classifier)

parameters = {'batch_size': [1000],
              'epochs': [25,35,45],
              'optimizer': ['adam']}

grid_search = GridSearchCV(estimator = classifier,
                           param_grid = parameters,
                           scoring = 'accuracy',
                           cv = 10)enter code here
grid_results = grid_search.fit(X_train, y_train)

print("Best: %f using %s" % (grid_results.best_score_, grid_results.best_params_))
means = grid_results.cv_results_['mean_test_score']
stds = grid_results.cv_results_['std_test_score']
params = grid_results.cv_results_['params']
for mean, stdev, param in zip(means, stds, params):
    print("%f (%f) with: %r" % (mean, stdev, param))