How to load MobileNet weights with an input tensor

问题:

I'm trying to apply transfer learning to MNIST using MobileNet weights in Keras. Keras documentation to use MobileNet https://keras.io/applications/#mobilenet

Mobilenet accepts 224x224x3 as input but MNIST is 28x28x1. I'm creating a Lambda layer which can convert 28x28x1 image into 224x224x3 and send it as input to MobileNet. The following code causes

TypeError: Input layers to a Model must be InputLayer objects. Received inputs: Tensor("lambda_2/ResizeNearestNeighbor:0", shape=(?, 224, 224, 3), dtype=float32). Input 0 (0-based) originates from layer type Lambda.

height = 28
width = 28
input_image = Input(shape=(height,width,1))

def resize_image_to_inception(x):
    x = K.repeat_elements(x, 3, axis=3)
    x = K.resize_images(x, 8, 8, data_format="channels_last")
    return x

input_image_ = Lambda(resize_image_to_inception, output_shape=(224, 224, 3))(input_image)
print(type(input_image_))
base_model = MobileNet(input_tensor=input_image_, weights='imagenet', include_top=False)