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Repair parallelized population sampling #3559

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merged 4 commits into from
Jul 26, 2019
Merged

Repair parallelized population sampling #3559

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badd446
test with and without parallelization across cores
michaelosthege Jul 21, 2019
6324408
replace parallelize kwarg by reliance on cores setting
michaelosthege Jul 21, 2019
7ac416a
add the changes from pull 3559
michaelosthege Jul 21, 2019
971c8e0
use more general suggestion in the log message
michaelosthege Jul 21, 2019
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1 change: 1 addition & 0 deletions RELEASE-NOTES.md
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@

### Maintenance
- Moved math operations out of `Rice`, `TruncatedNormal`, `Triangular` and `ZeroInflatedNegativeBinomial` `random` methods. Math operations on values returned by `draw_values` might not broadcast well, and all the `size` aware broadcasting is left to `generate_samples`. Fixes [#3481](https://github.com/pymc-devs/pymc3/issues/3481) and [#3508](https://github.com/pymc-devs/pymc3/issues/3508)
- Parallelization of population steppers (`DEMetropolis`) is now set via the `cores` argument. ([#3559](https://github.com/pymc-devs/pymc3/pull/3559))

## PyMC3 3.7 (May 29 2019)

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6 changes: 3 additions & 3 deletions pymc3/sampling.py
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Expand Up @@ -452,7 +452,7 @@ def sample(draws=500, step=None, init='auto', n_init=200000, start=None, trace=N
if has_population_samplers:
_log.info('Population sampling ({} chains)'.format(chains))
_print_step_hierarchy(step)
trace = _sample_population(**sample_args)
trace = _sample_population(**sample_args, parallelize=cores > 1)
else:
_log.info('Sequential sampling ({} chains in 1 job)'.format(chains))
_print_step_hierarchy(step)
Expand Down Expand Up @@ -689,7 +689,7 @@ def __init__(self, steppers, parallelize):
if parallelize:
try:
# configure a child process for each stepper
_log.info('Attempting to parallelize chains.')
_log.info('Attempting to parallelize chains to all cores. You can turn this off with `pm.sample(cores=1)`.')
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import multiprocessing
for c, stepper in enumerate(tqdm(steppers)):
slave_end, master_end = multiprocessing.Pipe()
Expand All @@ -714,7 +714,7 @@ def __init__(self, steppers, parallelize):
_log.debug('Error was: ', exec_info=True)
else:
_log.info('Chains are not parallelized. You can enable this by passing '
'pm.sample(parallelize=True).')
'`pm.sample(cores=n)`, where n > 1.')
return super().__init__()

def __enter__(self):
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15 changes: 14 additions & 1 deletion pymc3/tests/test_step.py
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Expand Up @@ -915,12 +915,25 @@ def test_checks_population_size(self):
trace = sample(draws=100, chains=4, step=step)
pass

def test_nonparallelized_chains_are_random(self):
with Model() as model:
x = Normal("x", 0, 1)
for stepper in TestPopulationSamplers.steppers:
step = stepper()
trace = sample(chains=4, cores=1, draws=20, tune=0, step=DEMetropolis())
samples = np.array(trace.get_values("x", combine=False))[:, 5]

assert len(set(samples)) == 4, "Parallelized {} " "chains are identical.".format(
stepper
)
pass

def test_parallelized_chains_are_random(self):
with Model() as model:
x = Normal("x", 0, 1)
for stepper in TestPopulationSamplers.steppers:
step = stepper()
trace = sample(chains=4, draws=20, tune=0, step=DEMetropolis())
trace = sample(chains=4, cores=4, draws=20, tune=0, step=DEMetropolis())
samples = np.array(trace.get_values("x", combine=False))[:, 5]

assert len(set(samples)) == 4, "Parallelized {} " "chains are identical.".format(
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