Will Dean comments

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                                            Will Dean

`LogisticSaturation` class does not document all of it's parameters

Yeah, thats why I have the second item to add documentation for each transformation class

Initial gitlab MR support

What is the status here?

`mmm.fit()` generates XlaRuntimeError unless `pytensor.config.floatX = "float32"`

What is the action here? Add this to the documentation? Or just have this as an issue to reference?

`mmm.fit()` generates XlaRuntimeError unless `pytensor.config.floatX = "float32"`

Hi @kb-open, this is an open source project. Would you like to make this contribution?

ENH: Native support for dims in tensors and tensor operations

not sure how eval would work in the case where shapes are not provided. ```python a = pt.vector("a", dims="channel") b = pt.vector("b", dims="geo") result = a + b # raise...

ENH: Native support for dims in tensors and tensor operations

> There's also the question of what should be the output, xarrays? Because if dims order is arbitrary users don't know what they're getting, but building xarray for the output...

Add `hdi_list` kwarg to plot functions `sample_prior_predictive` and `plot_errors`

I am against adding the `hdi_list` kwargs to `sample_prior_predictive` method `sample_prior_predictive` returns the InferenceData object. The user would be able to call az.hdi on this object. More control is given...

Cannot set a constant value as the parameter of an Adstock or Saturation transformation

You can initialize as a constant value, say 1.0. Maybe the deserialization doesn't work though

keywords used in docs instead of positional args

It and sweep_values seem to be positional only: https://github.com/pymc-labs/pymc-marketing/blob/eb2f846d42139c55ec3e2ae3689536839f7781ee/pymc_marketing/mmm/sensitivity_analysis.py?plain=1#L289-L293 Would you like to make the fix in the documentation, @nipnipj?

`VariableFactory` factory should come with a default `to_dict` and `from_dict` method

Related to #1341