AttributeError: 'UserRegisteredTypeKerasTensor' object has no attribute 'mean' error raised.

Please can anyone let me know why the following code:

from tensorflow.keras.layers import Input
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import Concatenate
from tensorflow.keras.models import Model
from tensorflow.keras.optimizers import Adam

def neg_log_likelihood(y, distr): 
    return -distr.log_prob(y) 

def my_dist(params): #723 
    return tfd.Normal(loc=params, scale=1)

inputs = Input(shape=(1,))
params = Dense(1)(inputs)
dist = tfp.layers.DistributionLambda(my_dist)(params) 
model_sd1 = Model(inputs=inputs, outputs=dist) 
model_sd1.compile(Adam(), loss=neg_log_likelihood) 

And then running the following code;

model_mean_sd1 = Model(inputs=inputs, outputs=dist.mean())

leads to the following error:

AttributeError: 'UserRegisteredTypeKerasTensor' object has no attribute 'mean'

Any help will be greatly appreciated. Thanks.

Start by running the supplied Python example and inspect the interaction between tensorflow.keras Model, tfp.layers.DistributionLambda, and the dist.mean() output expression. No repository file or test is named; done would mean determining the cause of the reported AttributeError and documenting or implementing a verified resolution.