Skip to content

oas skip grad on caching #1644

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Dec 13, 2022
Merged

oas skip grad on caching #1644

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 10 additions & 2 deletions src/Serialization/services/DispatchPackedConversions.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -72,16 +72,23 @@ end
##

"""
$(SIGNATURES)
$(SIGNATURES)

After deserializing a factor using decodePackedType, use this to
completely rebuild the factor's CCW and user data.

Notes:
- This function is likely to be used for cache heavy factors, e.g. `ObjectAffordanceSubcloud`.

Dev Notes:
- TODO: We should only really do this in-memory if we can by without it (review this).
- TODO: needs testing
"""
function rebuildFactorMetadata!(
dfg::AbstractDFG{SolverParams},
factor::DFGFactor,
neighbors = map(vId -> getVariable(dfg, vId), getNeighbors(dfg, factor)),
neighbors = map(vId -> getVariable(dfg, vId), getNeighbors(dfg, factor));
_blockRecursionGradients::Bool=false
)
#
# Set up the neighbor data
Expand All @@ -100,6 +107,7 @@ function rebuildFactorMetadata!(
potentialused = fsd.potentialused,
edgeIDs = fsd.edgeIDs,
solveInProgress = fsd.solveInProgress,
_blockRecursion=_blockRecursionGradients
)
#

Expand Down
6 changes: 3 additions & 3 deletions src/services/FactorGraph.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -717,11 +717,11 @@ function getDefaultFactorData(
_blockRecursion::Bool = false,
) where {T <: AbstractFactor}
#

# prepare multihypo particulars
# storeMH::Vector{Float64} = multihypo == nothing ? Float64[] : [multihypo...]
mhcat, nh = parseusermultihypo(multihypo, nullhypo)

# allocate temporary state for convolutional operations (not stored)
userCache = preambleCache(dfg, Xi, usrfnc)
ccw = _prepCCW(
Expand All @@ -734,7 +734,7 @@ function getDefaultFactorData(
_blockRecursion,
userCache,
)

# and the factor data itself
return FunctionNodeData{typeof(ccw)}(
eliminated,
Expand Down