results={}
OPTIMIZERS=[Adam(lr=1e-3) , RectifiedAdam(lr=1e-3)]

for optim in OPTIMIZERS:
    base_model=VGG16(input_shape=(224,224,3),include_top=False)
    base_model.trainable = False

    model = models.Sequential()
    model.add(base_model)
    model.add(layers.Flatten())
    model.add(layers.Dense(256, activation='relu'))
    model.add(layers.Dense(1, activation='sigmoid'))
    model.summary()

    model.compile(optimizer=optim ,
                  loss='binary_crossentropy' ,
                  metrics=['accuracy'])
    model.fit_generator(train_batches,
                    steps_per_epoch = train_batches.samples / 64,
                    validation_data = valid_batches,
                    validation_steps = valid_batches.samples /64,
                    epochs = 100,
                    callbacks=[LR_function])

    train_acc=model.history.history['acc']
    train_loss=model.history.history['loss']
    val_acc=model.history.history['val_acc']
    val_loss=model.history.history['val_acc']

    exp_tag_name=f'exp-optimizer-{optim}'
    results[exp_tag_name] = {'train-acc':train_acc,
                          'train-loss':train_loss,
                          'val-acc':val_acc,
                          'val-loss':val_loss}