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fix: Check parameter shapes for pdf API calls #1461

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@kratsg kratsg commented May 17, 2021

Pull Request Description

Resolves #1459. Check that expected_data, expected_auxdata, and expected_actualdata are being called with the right shape for pars (the parameters) before evaluating. This is usually caught by lower-level code, however the error is not as user-friendly.

A quick note: it is ok to add if/raise in these API calls as they're not meant to be "fast" in our code -- but this could potentially be a problem if we need to allow for autodiff capabilities. For now, we're only enforcing that logpdf() calls are the performant ones.

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* Add checks on input parameter shapes for the pdf API calls to expected_auxdata,
expected_actualdata, and expected_data.
* Add tests for parameter shape checks to properly raise exceptions.InvalidPdfParameters

@kratsg kratsg added API Changes the public API feat/enhancement New feature or request fix A bug fix labels May 17, 2021
@kratsg kratsg self-assigned this May 17, 2021
@kratsg kratsg added this to In progress in v0.6.2 via automation May 17, 2021
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Codecov Report

Merging #1461 (390b100) into master (ce70574) will increase coverage by 0.00%.
The diff coverage is 100.00%.

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##           master    #1461   +/-   ##
=======================================
  Coverage   98.12%   98.12%           
=======================================
  Files          64       64           
  Lines        4270     4278    +8     
  Branches      683      687    +4     
=======================================
+ Hits         4190     4198    +8     
  Misses         46       46           
  Partials       34       34           
Flag Coverage Δ
contrib 26.20% <0.00%> (-0.05%) ⬇️
doctest 60.47% <0.00%> (-0.12%) ⬇️
unittests 96.18% <100.00%> (+<0.01%) ⬆️

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src/pyhf/pdf.py 97.85% <100.00%> (+0.05%) ⬆️

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@lukasheinrich
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I wonder whether for these types of API we shsould have a pattern

def method(self,...):
    # check inputs
    ....
   self._method(...)

such that for performance critical or internal paths (i.e. where pyhf itself calls method we're able to call the "unsafe" _method - relying on prior checks, while the user gets a friendly API with safety checks

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kratsg commented May 17, 2021

I wonder whether for these types of API we shsould have a pattern

I had this idea where I wanted to use decorators. It can introspect the arguments and do the checks based on something consistent, rather than copy/paste code around a lot. In this case, something like @pyhf.checks.pars that checks the number of parameters passed in for pdf calls, and would become a passthrough based on some pyhf.config configuration or similar.

raise exceptions.InvalidPdfParameters(
f'eval failed as pars has len {pars.shape[-1]} but {self.config.npars} was expected'
)

return self.make_pdf(pars)[1].expected_data()

def _modifications(self, pars):
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given that we do input validation here it suggests that this has become a publicly consumable API. maybe we should add a model.modifications and do the input checks there and call _modifications if inputs are ok

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_modifications isn't currently a public API. This certainly could become one, although I might argue that we remove it from Model and keep it on MainModel unless there's a reason to pass-through it. e.g. pdf.main_model.modifications is just as clear to me. Unless the suggestion here is to remove the checks from main_model and constraint_model and keep all checks on model which is also possible, but feels like a mess.

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main_model is needed for return_by_sample, so it feels similarly "public" as Model.

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Sure, but main_model.expected_actualdata(..., return_by_sample) is fine -- since that's public. However main_model._modifications isn't necessarily public. Although at the moment only used by main_model.expected_data -- so I'm fine either way.

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Unless the suggestion here is to remove the checks from main_model and constraint_model

My comment was meant as an example for why that may not be desirable, sorry I should have made that clear. Promoting _modifications to public in the longer term is a nice idea, it looks very useful for model debugging.

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I created an issue regarding the proposal of making _modifications public: #1652.

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as it is now this will be called on each logpdf call.. so it's perf. critical.. should we have some kind of split of "pdf.method" and "pdf._method_unsafe"? or do we think it doesn't make a difference?

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@lukasheinrich @kratsg If we can revisit the performance impact here soon it would be nice to have this get into v0.7.0.

@matthewfeickert matthewfeickert added the tests pytest label May 17, 2021
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This all LGTM @kratsg — thanks. I'll let you and @lukasheinrich resolve the current discussion and implement any changes that you want, but I'm happy to have this merged whenever you both are.

@matthewfeickert matthewfeickert removed this from In progress in v0.6.2 Jun 21, 2021
@matthewfeickert matthewfeickert added this to In progress in v0.6.3 via automation Jun 21, 2021
@matthewfeickert matthewfeickert removed this from In progress in v0.6.3 Aug 25, 2021
@matthewfeickert matthewfeickert added this to In progress in v0.6.4 via automation Aug 25, 2021
@matthewfeickert matthewfeickert removed this from In progress in v0.6.4 Oct 22, 2021
@matthewfeickert matthewfeickert added this to In progress in v0.7.0 via automation Oct 22, 2021
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@kratsg kratsg removed this from In progress in v0.7.0 Aug 30, 2022
@kratsg kratsg added this to In progress in v0.7.1 via automation Aug 30, 2022
@matthewfeickert matthewfeickert changed the base branch from master to main September 21, 2022 20:53
@matthewfeickert matthewfeickert removed this from In progress in v0.7.1 Apr 7, 2023
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Input validation for pyhf.pdf.Model.expected_data
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