"Bayesian Methods for Hackers" jupyter notebook not working - tensorflow2.0

Question

I am reading the online TensorFlow Probability (TFP) version of "Bayesian Methods for Hackers".
But when I excecute the first cell of Ch2_MorePyMC_TFP.ipynb
the following error occurs:
AttributeError: module 'tensorflow' has no attribute 'contrib'
I suppose this version of "Bayesian Methods for Hackers" jupyter notebook was written for TF1.
Do you have an easy fix or a updated version of this jupyter notebook working with TF2 ?

Answer 1

Some of the contrib functions are removed and some of them are merged into TensorFlow core. You need to find the equivalent version of them.
import tensorflow as tf
import tensorflow_probability as tfp
tfd = tfp.distributions
tfb = tfp.bijectors
print(tf.__version__) # 2.5.0
print(tfp.__version__) # 0.12.1
For example first contrib functions are available in TensorFlow and can be re-written as:
parameter = tfd.Exponential(rate=1., name="poisson_param").sample()
rv_data_generator = tfd.Poisson(parameter, name="data_generator")
data_generator = rv_data_generator.sample()
data_generator_ = tf.nest.pack_sequence_as(
data_generator,
[t.numpy() if tf.is_tensor(t) else t
for t in tf.nest.flatten(data_generator)])
print("Value of sample from data generator random variable:", data_generator_)
For other TF Operations you can replace them like this:
with tf.compat.v1.variable_scope(tf.compat.v1.get_variable_scope(), reuse=tf.compat.v1.AUTO_REUSE):
step_size = tf.compat.v1.get_variable(
name='step_size',
initializer=tf.constant(0.5, dtype=tf.float32),
trainable=False,
use_resource=True
)
More info can be found in the documentation

Answer 2

Frightera, I have problems getting rid of the following error :
module 'tensorflow' has no attribute 'variable_scope'
at cell :
# Initialize the step_size. (It will be automatically adapted.)
with tf.variable_scope(tf.get_variable_scope(), reuse=tf.AUTO_REUSE):
step_size = tf.get_variable(
name='step_size',
initializer=tf.constant(0.5, dtype=tf.float),
trainable=False,
use_resource=True
)
Do you have any clue how to replace this one?