A tfp.util.TransformedVariable generally behaves like any tensor-like object. For example, a less-than-equal comparison works element-wise, as expected:

import tensorflow as tf
import tensorflow_probability as tfp
var = tf.Variable(1.0)
assert var <= 1.0 and var >= 1.0 and var == 1.0  # passes
t_var = tfp.util.TransformedVariable(1.0, tfp.bijectors.Identity())
assert t_var <= 1.0 and t_var >= 1.0  # passes

However, equality comparison does not behave likewise, and the following fails:

assert t_var == 1.0  # FAILS

This is completely unexpected behaviour which can lead to very subtle downstream bugs.

The reason for this behaviour seems to be due to explicitly removing __eq__ and __ne__ in

What was the motivation for excluding equality comparisons? Would there be any objections to a PR that removes that line, thereby allowing tfp TransformedVariables to behave more expectedly like tf Variables?