def build_model(optimizer): grid_model = Sequential() grid_model.add(LSTM(50,return_sequences=True,input_shape=(30,5))) grid_model.add(LSTM(50)) grid_model.add(Dropout(0.2)) grid_model.add(Dense(1)) grid_model.compile(loss = 'mse',optimizer = optimizer) return grid_modelgrid_model = KerasRegressor(build_fn=build_model,verbose=1,validation_data=(testX,testY)) parameters = {'batch_size' : [16,20], 'epochs' : [8,10], 'optimizer' : ['adam','Adadelta'] } grid_search = GridSearchCV(estimator = grid_model, param_grid = parameters, cv = 2)这段代码报错

这段代码报错是因为您在 `GridSearchCV` 函数中传入了 `estimator` 参数，但是该参数应该传入一个实例化后的模型，而不是一个函数。修改代码如下：

grid_model = KerasRegressor(build_fn=build_model, verbose=1, validation_data=(testX, testY))
parameters = {'batch_size': [16, 20], 'epochs': [8, 10], 'optimizer': ['adam', 'Adadelta']}
grid_search = GridSearchCV(estimator=grid_model, param_grid=parameters, cv=2)

这里的 `grid_model` 是一个实例化后的模型，可以直接传入 `GridSearchCV` 函数中。