使用网格搜索对GANs进行超参数调整

from sklearn.model_selection import GridSearchCV
from keras.wrappers.scikit_learn import KerasClassifier
from keras.models import Sequential
from keras.layers import Dense

def create_model(optimizer='adam'):
    model = Sequential()
    model.add(Dense(12, input_dim=8, activation='relu'))
    model.add(Dense(1, activation='sigmoid'))
    model.compile(loss='binary_crossentropy', optimizer=optimizer, metrics=['accuracy'])
    return model

model = KerasClassifier(build_fn=create_model, verbose=0)

param_grid = {
    'batch_size': [16, 32],
    'epochs': [10, 20],
    'optimizer': ['adam', 'sgd']
}

grid = GridSearchCV(estimator=model, param_grid=param_grid, cv=3)
grid_result = grid.fit(X_train, y_train)

print(f"Best: {grid_result.best_score_} using {grid_result.best_params_}")