Missing Values and the Multidimensional Indexing FutureWarning

I am fitting a hierarchical model and get a lot of angry warnings like this:

rval = inputs[0].getitem(inputs[1:])
/theano/tensor/subtensor.py:2339: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result.

Oddly, they appear only if I have missing values in the 2D array that I assign to the observed argument. No missing values = no warnings.

Does someone know what it might mean?

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I am finding this as well. It seems that pymc struggles with missing values in multidimensional distribution arrays.