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Description
Description of your problem
I would like to set the start value explicitly when calling pm.sample() using start=
, but it seems like the tuning does not use the input. I know that for some initialization methods (e.g., jitter+adapt_diag
), the init can override the start. However, I would not expect adapt_diag
to override the input start. As example:
with pm.Model() as model:
lnx = pm.Uniform('lnx', 0., 5.)
infdata = pm.sample(tune=100, draws=0,
start={'lnx': 1.},
init='adapt_diag',
return_inferencedata=True,
discard_tuned_samples=False,
chains=1)
Please provide the full traceback.
I would expect infdata.warmup_posterior.lnx.values[0, 0] == 1.
with the example above, but instead it seems to initialize at a random point.
Versions and main components
- PyMC3 Version: 3.11.1
- Aesara Version: n/a
- Python Version: 3.8
- Operating system: macOS
- How did you install PyMC3: pip