tfp.JointDistributionSequential._build() -> line 236, in _build if not isinstance(model, collections.Sequence): AttributeError: module 'collections' has no attribute 'Sequence'

Code taken from:

https://github.com/tensorflow/probability/blob/main/tensorflow_probability/examples/jupyter_notebooks/Modeling_with_JointDistribution.ipynb

Code to reproduce:

dfhogg = pd.DataFrame(np.array([[1,201,592,61,9,-0.84],
[2,244,401,25,4,0.31],
[3,47,583,38,11,0.64],
[4,287,402,15,7,-0.27],
[5,203,495,21,5,-0.33],
[6,58,173,15,9,0.67],
[7,210,479,27,4,-0.02],
[8,202,504,14,4,-0.05],
[9,198,510,30,11,-0.84],
[10,158,416,16,7,-0.69],
[11,165,393,14,5,0.30],
[12,201,442,25,5,-0.46],
[13,157,317,52,5,-0.03],
[14,131,311,16,6,0.50],
[15,166,400,34,6,0.73],
[16,160,337,31,5,-0.52],
[17,186,423,42,9,0.90],
[18,125,334,26,8,0.40],
[19,218,533,16,6,-0.78],
[20,146,344,22,5,-0.56]]),
columns=['id','x','y','sigma_y','sigma_x','rho_xy'])

for convenience zero-base the 'id' and use as index

dfhogg['id'] = dfhogg['id'] - 1
dfhogg.set_index('id',inplace=True)

standardize (mean center and divide by 1 sd)

dfhoggs = (dfhogg[['x','y']] - dfhogg[['x','y']].mean(0)) / dfhogg[['x','y']].std(0)
dfhoggs['sigma_y'] = dfhogg['sigma_y'] / dfhogg['y'].std(0)
dfhoggs['sigma_x'] = dfhogg['sigma_x'] / dfhogg['x'].std(0)

X_np = dfhogg['x'].values
sigma_y_np = dfhogg['y'].values
Y_np = dfhogg['y'].values

mdl_ols = tfd.JointDistributionSequential([
# b0 ~ Normal(0, 1)
tfd.Normal(loc=tf.cast(0, dtype), scale=1.),
# b1 ~ Normal(0, 1)
tfd.Normal(loc=tf.cast(0, dtype), scale=1.),
# x ~ Normal(b0+b1X, 1)
lambda b1, b0: tfd.Normal(
# Parameter transformation
loc=b0 + b1X_np,
scale=sigma_y_np)
])

output:

line 236, in _build
if not isinstance(model, collections.Sequence):
AttributeError: module 'collections' has no attribute 'Sequence'

##################################################################################################################################################

What I tried before creating issue:

import collections.abc as collections

According to python doc:

isinstance(object, classinfo),
Return True if the object argument is an instance of the classinfo argument

However, the classinfo argument in Pycharm is
{ABCMeta} <class 'collections.abc.Sequence'>

and tfp code is

"if not isinstance(model, collections.Sequence)"

My guess is tfp code should be:

"if not isinstance(model, collections.abc.Sequence)"

Start with JointDistributionSequential._build at the reported line and reproduce the example from the Modeling_with_JointDistribution notebook under the affected Python version. Check the sequence type check and confirm that the example runs without the AttributeError when done.