ImageDataGenerator - trained with model.fit instead of model.fit_generator

Question

I am a beginner in using the ImageDataGenerator from Keras and I accidentally used model.fit instead of model.fit_generator.

train_gen = gen_Image_data()
test_gen = ImageDataGenerator()
train_samples = train_gen.flow(X,y, batch_size=64)
test_samples = test_gen.flow(X_val, y_val, batch_size=64)
history = model.fit(train_samples, steps_per_epoch = np.ceil(len(X)/64),
                  validation_data=(test_samples),
                  validation_steps=np.ceil(len(X_val)/64),
                  epochs=300, verbose=1, callbacks=[es])

Is that a glaring mistake, do I have to re-train everything with fit_generator?

Thanks for every help

Update I have forgotten the code for gen_Image_data()

def gen_Image_data():
   gen = ImageDataGenerator(
         width_shift_range=0.1,
         horizontal_flip=True)
   return gen

Answer 1

You don't have bother re-training the model, because model.fit method supports generators as well and also model.fit_generator is subsumed by model.fit method!