'MCMCPosterior' object has no attribute 'copy_hyperparameters_from'

When trying to run snle as in the documentation example, the code runs into an error when calling posterior.copy_hyperparameters_from(posteriors[-1]) in snle.py, as it seems like MCMCPosterir does not have any function called copy_hyperparameters_from. What should be the correct behaviour? Would it make sense to just remove the line, or does this require a proper fix?

Here is my code to reproduce the error:

import sbibm

task = sbibm.get_task("two_moons")  # See sbibm.get_available_tasks() for all tasks
prior = task.get_prior()
simulator = task.get_simulator()
observation = task.get_observation(num_observation=1)  # 10 per task

# These objects can then be used for custom inference algorithms, e.g.
# we might want to generate simulations by sampling from prior:
thetas = prior(num_samples=10_000)
xs = simulator(thetas)

# Alternatively, we can import existing algorithms, e.g:
from sbibm.algorithms import snle  # See help(rej_abc) for keywords
posterior_samples, _, _ = snle(task=task, num_samples=10_000, num_observation=1, num_simulations=100_000, neural_net='maf')

# Once we got samples from an approximate posterior, compare them to the reference:
from sbibm.metrics import c2st
reference_samples = task.get_reference_posterior_samples(num_observation=1)
c2st_accuracy = c2st(reference_samples, posterior_samples)

# Visualise both posteriors:
from sbibm.visualisation import fig_posterior
fig = fig_posterior(task_name="two_moons", observation=1, samples=[posterior_samples])
# Note: Use fig.show() or fig.save() to show or save the figure

# Get results from other algorithms for comparison:
from sbibm.visualisation import fig_metric
results_df = sbibm.get_results(dataset="main_paper.csv")
fig = fig_metric(results_df.query("task == 'two_moons'"), metric="C2ST")

sbi-benchmark / sbibm

'MCMCPosterior' object has no attribute 'copy_hyperparameters_from' #53