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[Merged by Bors] - Perform invlinking in assume rather than implicitly in getindex #360
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Maybe |
Ideally this is indeed how we do it. The current impl is super-confusing, e.g. if you use a sampler in But I assume we need to do a bit of tracking down of all references to |
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
bors try |
tryBuild failed: |
bors try |
tryBuild failed: |
Tests are failing on Julia 1.3 because the fix from TuringLang/Turing.jl#1758 hasn't made it through yet. (It doesn't fail on Julia#latest because it's Julia 1.7 which makes it incompatible with latest release of Turing) EDIT: It's passing locally using |
@torfjelde it’s ok to make a new release from |
Canceled. |
bors r+ |
Currently, in `assume`, etc., `invlink` is called implicitly in `getindex` using the distribution extracted from `vi`. This has a couple of drawbacks: 1. We can only use the distribution for a particular `vn` stored in `vi` obtained during the initial run. This means that we can't even run models where the distributions has dynamic domains, i.e. the domain of a particular random variable is dependent on the realizations of other random variables. 2. We have to store the distribution for each `vn` in `vi`. This was fine when we only had `VarInfo` because we also need it for other functionality, but this is not the case in `SimpleVarInfo` (nor will it be). So. In this PR we introduce a `getindex_raw` which is `getindex` but without `invlink` if it's already linked, and uses this within `assume`, etc. where we now use the distributions that are passed to `assume` rather than those stored in `vi`. E.g. the following now works: ``` julia julia> @model demo() = x ~ InverseGamma(2, 3) demo (generic function with 2 methods) julia> vi = SimpleVarInfo((x = 10.0, ), true) SimpleVarInfo((x = 10.0,), 0.0, true) julia> _, vi = DynamicPPL.evaluate!!(model, vi, DefaultContext()) (22026.465794806718, SimpleVarInfo{NamedTuple{(:x,), Tuple{Float64}}, Float64}((x = 10.0,), -17.80291162245307, true)) ``` Co-authored-by: Hong Ge <[email protected]>
Timed out. |
bors r+ |
Currently, in `assume`, etc., `invlink` is called implicitly in `getindex` using the distribution extracted from `vi`. This has a couple of drawbacks: 1. We can only use the distribution for a particular `vn` stored in `vi` obtained during the initial run. This means that we can't even run models where the distributions has dynamic domains, i.e. the domain of a particular random variable is dependent on the realizations of other random variables. 2. We have to store the distribution for each `vn` in `vi`. This was fine when we only had `VarInfo` because we also need it for other functionality, but this is not the case in `SimpleVarInfo` (nor will it be). So. In this PR we introduce a `getindex_raw` which is `getindex` but without `invlink` if it's already linked, and uses this within `assume`, etc. where we now use the distributions that are passed to `assume` rather than those stored in `vi`. E.g. the following now works: ``` julia julia> @model demo() = x ~ InverseGamma(2, 3) demo (generic function with 2 methods) julia> vi = SimpleVarInfo((x = 10.0, ), true) SimpleVarInfo((x = 10.0,), 0.0, true) julia> _, vi = DynamicPPL.evaluate!!(model, vi, DefaultContext()) (22026.465794806718, SimpleVarInfo{NamedTuple{(:x,), Tuple{Float64}}, Float64}((x = 10.0,), -17.80291162245307, true)) ``` Co-authored-by: Hong Ge <[email protected]>
Build failed: |
bors r+ |
Currently, in `assume`, etc., `invlink` is called implicitly in `getindex` using the distribution extracted from `vi`. This has a couple of drawbacks: 1. We can only use the distribution for a particular `vn` stored in `vi` obtained during the initial run. This means that we can't even run models where the distributions has dynamic domains, i.e. the domain of a particular random variable is dependent on the realizations of other random variables. 2. We have to store the distribution for each `vn` in `vi`. This was fine when we only had `VarInfo` because we also need it for other functionality, but this is not the case in `SimpleVarInfo` (nor will it be). So. In this PR we introduce a `getindex_raw` which is `getindex` but without `invlink` if it's already linked, and uses this within `assume`, etc. where we now use the distributions that are passed to `assume` rather than those stored in `vi`. E.g. the following now works: ``` julia julia> @model demo() = x ~ InverseGamma(2, 3) demo (generic function with 2 methods) julia> vi = SimpleVarInfo((x = 10.0, ), true) SimpleVarInfo((x = 10.0,), 0.0, true) julia> _, vi = DynamicPPL.evaluate!!(model, vi, DefaultContext()) (22026.465794806718, SimpleVarInfo{NamedTuple{(:x,), Tuple{Float64}}, Float64}((x = 10.0,), -17.80291162245307, true)) ``` Co-authored-by: Hong Ge <[email protected]>
Build failed: |
Unfortunately integration tests will fail because the tests for In addition, I've bumped the minimum supported Julia version to 1.6 for DPPL; 1.6 is now LTS and we've already done this for Turing.jl, so continue to test against 1.3 but not 1.6 seems strange. |
bors r+ |
Currently, in `assume`, etc., `invlink` is called implicitly in `getindex` using the distribution extracted from `vi`. This has a couple of drawbacks: 1. We can only use the distribution for a particular `vn` stored in `vi` obtained during the initial run. This means that we can't even run models where the distributions has dynamic domains, i.e. the domain of a particular random variable is dependent on the realizations of other random variables. 2. We have to store the distribution for each `vn` in `vi`. This was fine when we only had `VarInfo` because we also need it for other functionality, but this is not the case in `SimpleVarInfo` (nor will it be). So. In this PR we introduce a `getindex_raw` which is `getindex` but without `invlink` if it's already linked, and uses this within `assume`, etc. where we now use the distributions that are passed to `assume` rather than those stored in `vi`. E.g. the following now works: ``` julia julia> @model demo() = x ~ InverseGamma(2, 3) demo (generic function with 2 methods) julia> vi = SimpleVarInfo((x = 10.0, ), true) SimpleVarInfo((x = 10.0,), 0.0, true) julia> _, vi = DynamicPPL.evaluate!!(model, vi, DefaultContext()) (22026.465794806718, SimpleVarInfo{NamedTuple{(:x,), Tuple{Float64}}, Float64}((x = 10.0,), -17.80291162245307, true)) ``` Co-authored-by: Hong Ge <[email protected]>
@yebai Can you just merge this once Bors comes back with failure, assuming the ESS tests are the only ones failing? |
Actually, given that we bump the lower bound for the Julia version, we should bump minor rather than patch version. This will also make bors happy 👍 |
Canceled. |
bors r+ |
Currently, in `assume`, etc., `invlink` is called implicitly in `getindex` using the distribution extracted from `vi`. This has a couple of drawbacks: 1. We can only use the distribution for a particular `vn` stored in `vi` obtained during the initial run. This means that we can't even run models where the distributions has dynamic domains, i.e. the domain of a particular random variable is dependent on the realizations of other random variables. 2. We have to store the distribution for each `vn` in `vi`. This was fine when we only had `VarInfo` because we also need it for other functionality, but this is not the case in `SimpleVarInfo` (nor will it be). So. In this PR we introduce a `getindex_raw` which is `getindex` but without `invlink` if it's already linked, and uses this within `assume`, etc. where we now use the distributions that are passed to `assume` rather than those stored in `vi`. E.g. the following now works: ``` julia julia> @model demo() = x ~ InverseGamma(2, 3) demo (generic function with 2 methods) julia> vi = SimpleVarInfo((x = 10.0, ), true) SimpleVarInfo((x = 10.0,), 0.0, true) julia> _, vi = DynamicPPL.evaluate!!(model, vi, DefaultContext()) (22026.465794806718, SimpleVarInfo{NamedTuple{(:x,), Tuple{Float64}}, Float64}((x = 10.0,), -17.80291162245307, true)) ``` Co-authored-by: Hong Ge <[email protected]>
Pull request successfully merged into master. Build succeeded: |
Currently, in
assume
, etc.,invlink
is called implicitly ingetindex
using the distribution extracted fromvi
.This has a couple of drawbacks:
vn
stored invi
obtained during the initial run. This means that we can't even run models where the distributions has dynamic domains, i.e. the domain of a particular random variable is dependent on the realizations of other random variables.vn
invi
. This was fine when we only hadVarInfo
because we also need it for other functionality, but this is not the case inSimpleVarInfo
(nor will it be).So. In this PR we introduce a
getindex_raw
which isgetindex
but withoutinvlink
if it's already linked, and uses this withinassume
, etc. where we now use the distributions that are passed toassume
rather than those stored invi
.E.g. the following now works: