Support PyTensor deterministic operations as observations

[williambdean]

Description

Will need some help on this implementation and how to best test this.

Related Issue

• Closes BUG: data as observed in RV #7649
• Related to #

Checklist

• Checked that the pre-commit linting/style checks pass
• Included tests that prove the fix is effective or that the new feature works
• Added necessary documentation (docstrings and/or example notebooks)
• If you are a pro: each commit corresponds to a relevant logical change

Type of change

• New feature / enhancement
• Bug fix
• Documentation
• Maintenance
• Other (please specify):

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📚 Documentation preview 📚: https://pymc--7656.org.readthedocs.build/en/7656/

[ricardoV94]

We need to tell InferenceData converter how to get the data values to put in constant_data, and observed_data. It had some hardcode logic assuming you could only due Casts

[ricardoV94]

I don't consider this a bugfix, it's behavior that was explicitly forbidden for conservative reasons (more like a NotImplementedError)

[williambdean]

We need to tell InferenceData converter how to get the data values to put in constant_data, and observed_data. It had some hardcode logic assuming you could only due Casts

Where does this happen in the code?

[williambdean]

I think the MiniBatch tests will still fail. Any thoughts on how that should behave?

[williambdean]

Also, feel free to choose a better title! I couldn't express it too well

[ricardoV94]

We need to tell InferenceData converter how to get the data values to put in constant_data, and observed_data. It had some hardcode logic assuming you could only due Casts

Where does this happen in the code?

pymc/pymc/backends/arviz.py

Line 63 in fa43eba

obs_data = extract_obs_data(aux_obs)

pymc/pymc/pytensorf.py

Line 152 in fa43eba

def extract_obs_data(x: TensorVariable) -> np.ndarray:

We should be able to just use constant_fold (also in pytensor) for it

[williambdean]

We should be able to just use constant_fold (also in pytensor) for it

I have an implementation before this suggestion. I need a little help understanding this. Feel free to put suggestion

[ricardoV94]

We should be able to just use constant_fold (also in pytensor) for it

I have an implementation before this suggestion. I need a little help understanding this. Feel free to put suggestion

What do you mean? My suggestion is to simply call constant_fold on the observed variable

[williambdean]

I am not able to make this work with either constant_fold(x) or constant_fold([x]). Both return errors. Is the constant_fold from pymc.pytensorf or from pytensor?

[ricardoV94]

I am not able to make this work with either constant_fold(x) or constant_fold([x]). Both return errors. Is the constant_fold from pymc.pytensorf or from pytensor?

From pymc.pytensorf. There's a raise_if_not_constant flag you can set, but what cases is it failing?

[ricardoV94]

Ah if it's a SharedVariable like pm.Data of course constant_fold is not going to work... Dummy me.

[ricardoV94]

from pytensor.compile.mode import Mode
import pymc as pm

with pm.Model(coords={"date": [0, 1, 2]}) as m:
    data = pm.Data("data", [0, 1, 2], dims="date")
    x = pm.Normal("x")
    y = pm.Normal("y", x, observed=data, dims="date")

cheap_eval_mode = Mode(linker="py", optimizer=None)
m.rvs_to_values[y].eval(mode=cheap_eval_mode)
# array([0., 1., 2.])

[williambdean]

Thanks for the suggestion. I've used mode on the random variable directly. Is it different to get the rvs_to_values from the model? it currently isn't accessed from the function at the moment.

[williambdean]

Could you point me to similar tests for this?

[williambdean]

I've just added to associated pytensorf test suite