How to get intermediate output for eager mode

Question

I established a transfer learning model and tried to get the intermediate output. I followed one of the suggestion here in order to get the intermediate output of a model, as follows:

import tensorflow as tf
from tensorflow.keras import backend as K

tf.enable_eager_execution()

base_conv = tf.keras.applications.MobileNetV2(input_shape= None, 
            alpha=1.0, depth_multiplier=1, \
            include_top=True, weights='imagenet', input_tensor=None, \
            pooling=None, classes=1000)

model = tf.keras.models.Sequential()

model.add(base_conv)

model.add(tf.keras.layers.Dense(512, activation='relu'))

model.add(tf.keras.layers.Dense(5, activation='softmax'))

# with a Sequential model
get_layer_output = K.function([model.layers[0].input],                                 
                          [model.layers[0].get_layer('Conv_1').output])

#x is the input image
layer_output = get_layer_output([x])

But then I got an error:

AttributeError: Tensor.name is meaningless when eager execution is enabled.