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PyMC4 development tasks #126

Open
7 of 9 tasks
ferrine opened this issue Jun 8, 2019 · 3 comments
Open
7 of 9 tasks

PyMC4 development tasks #126

ferrine opened this issue Jun 8, 2019 · 3 comments

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@ferrine
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ferrine commented Jun 8, 2019

PyMC4 developer taskboard

Efforts in implementing pymc4 are not single person, so we need a place to sync our progress on this. This issue should be the place where we communicate, update status of every task on a regular basis.

  1. Max

  2. Saurav Implement Tensorflow backend and make forward sampling working.

    • Test Model evaluation is correct against hand crafted scipy implementation
    • We may test some compound models are evaluated correctly
    • Test that do operator works correctly. This is the core in observed API (not yet discussed, should be possible with a prototype, but verbose)
  3. Max Decide on Transforms API. Should be independent from (1.).

    • Decide on implementation details with pymc4-devs
    • Implement transforms API, sync with (1.) progress.

Forward sampling and applying transforms are now splitted as no dependency functionality: forward sampling does not require transforms and transforms usage under the hood is not aware about backend used.

  1. Saurav Use Executor developer API to create LogProb function that is expected in tfp
    3.1 I'd prefer it can accept both list arguments with predefined list of names or dictionary of values.
    3.2 This function should raise an error if we forget any of variables in the graph.
    3.3 should not be aware about the backend
    • Implementation of logprob function
    • test the implementation, sync with Max about transformed variables
    • tested integration with tfp/pymc3 samplers
@ferrine ferrine pinned this issue Jun 8, 2019
@twiecki twiecki changed the title Google Summer of Code timeline PyMC4 development tasks Sep 5, 2019
@lucianopaz
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@ferrine, what would be an updated status on the tasks here? Some refer to the multi backend things that were discarded later. The executors now work and are tested but I don't know if there are tests against a scipy model. The transformed API seems to be inplace but I don't know if there are transformations that should still be tested. Currently, the forward sampler for posterior predictive samples needs to be aware of autotransformed variables, and does so by relying on what the transformed executor does.

@ferrine
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ferrine commented Jul 29, 2020

Updated

@ferrine
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ferrine commented Jul 29, 2020

I think we can add some more input to the board

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