2 kinds of warnings with Aesara

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Jerry Morrison

May 6, 2021, 9:18:25 PM5/6/21
to theano-users
I'm finding the switch from Theano to Aesara straightforward, our simulation code produced the same output, and one program runs 19% faster once there's an ~/.aesara cache!

This is fantastic. I was getting worried about depending on Theano.

It did print two kinds of warnings:

RuntimeWarning: divide by zero encountered in true_divide

.../lib/python3.8/site-packages/aesara/graph/fg.py:525: UserWarning: Variable Elemwise{mul}.0 cannot be replaced; it isn't in the FunctionGraph

The first warning is from our code calling NumPy. It turns out that `import theano` suppresses that warning globally!

It's great that Aesara doesn't suppress that warning, but it could've saved debugging time if the release notes mentioned that. :)

The second kind of warning comes from deep in Aesara, in code that used to "just return silently because it makes it easier to implement some optimizations for multiple-output ops".

Here's the stack trace (OCR'd from a screen shot of the PyCharm debugger's "frames" pane):

    replace, fg.py:525 
    replace_all_validate, toolbox.py:574
    replace_all_validate_remove, toolbox.py:642
    process_node, opt.py:2058
    apply, opt.py:2535
    optimize, opt.py:84
    apply, opt.py:246
    optimize, opt.py:84
    __call__, opt.py:93
    __init__, types.py:1616
    orig_function, types.py:1971
    pfunc, pfunc.py:524
    function, __init__.py:337
    make_thunk, op.py:970
    make_all, vm.py:1133
    make_thunk, basic.py:293
    create, types.py:1837
    orig_function, types.py:1982
    pfunc, pfunc.py:524
    function, __init__.py:337
    km_loss_function, rna_decay.py:179

km_loss_function is in our code:

    import aesara.tensor as T
    from aesara import function, gradient

    km = T.dvector()

    J = gradient.jacobian(LossFunction, km)
    J_aux = gradient.jacobian(LossFunction_aux, km)
    Jacob = function([km], J)

Should our code do this differently?
Do you need a small test case?

Brandon T. Willard

May 7, 2021, 11:22:28 AM5/7/21
to theano-users
> Should our code do this differently?

No, that warning can be ignored.  We have some things to update internally that will make that go away.  See https://github.com/pymc-devs/aesara/issues/338.
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