TensorFlow: Variables in bijectors cannot be reused - tensorflow

Question

Describe the problem
I am trying to reuse the weights and biases in the neural network within the MaskedAutoregressiveFlow bijector, by placing it within a tf.variable_scope with reuse=tf.AUTO_REUSE. But found that the weights and biases are not reused in practice.
Reproduce
import tensorflow as tf
from tensorflow.contrib.distributions.python.ops import bijectors as tfb
def get_bijector(name='my_bijector', reuse=None):
"""Returns a MAF bijector."""
with tf.variable_scope(name, reuse=reuse):
shift_and_log_scale_fn = \
tfb.masked_autoregressive_default_template([128])
return tfb.MaskedAutoregressiveFlow(shift_and_log_scale_fn)
x = tf.placeholder(shape=[None, 64], dtype='float32', name='x')
bijector_0 = get_bijector(reuse=tf.AUTO_REUSE)
y_0 = bijector_0.forward(x)
bijector_1 = get_bijector(reuse=tf.AUTO_REUSE)
y_1 = bijector_1.forward(x)
# We were expecting that the `y_0` and `y_1` share the same dependent variables,
# since we used `tf.AUTO_REUSE` within the `tf.variable_scope`. However, the following
# will return a `False`.
print(get_dependent_variables(y_0) == get_dependent_variables(y_1))
wherein we have employed the function that gains all the variables a tensor depends on:
import collections
def get_dependent_variables(tensor):
"""Returns all variables that the tensor `tensor` depends on.
Forked from: https://stackoverflow.com/a/42861919/1218716
Args:
tensor: Tensor.
Returns:
List of variables.
"""
# Initialize
starting_op = tensor.op
dependent_vars = []
queue = collections.deque()
queue.append(starting_op)
op_to_var = {var.op: var for var in tf.trainable_variables()}
visited = {starting_op}
while queue:
op = queue.popleft()
try:
dependent_vars.append(op_to_var[op])
except KeyError:
# `op` is not a variable, so search its inputs (if any).
for op_input in op.inputs:
if op_input.op not in visited:
queue.append(op_input.op)
visited.add(op_input.op)
return dependent_vars