The depsgraph was always created within a fixed evaluation context. Passing
both risks the depsgraph and evaluation context not matching, and it
complicates the Python API where we'd have to expose both which is not so
easy to understand.
This also removes the global evaluation context in main, which assumed there
to be a single active scene and view layer.
Differential Revision: https://developer.blender.org/D3152
- When returning the number of items in a collection use BLI_*_len()
- Keep _size() for size in bytes.
- Keep _count() for data structures that don't store length
(hint this isn't a simple getter).
See P611 to apply instead of manually resolving conflicts.
This statistics is only collected when debug_value is different from 0.
Stored in depsgraph node itself, so we can always have access to average data
and other stats which requires persistent storage. This way we also don't waste
time trying to find stats from a separately stored hash map.
This is something deliver form node type, there is no reason to try cache it
anywhere, especially since it's not used in any performance critical code.
Lighter weight dependency graph is what we want.
The idea is to de-duplicate logic in DEG_id_tag_update() and flushing where we
need to translate depsgraph tag or component type to ID level recalc flag.
Currently unused, but is required for Blender 2.8.
This is crucial bit since batch cache is stored in the evaluated object,
meaning we can't tag it's hatch cache dirty from the notifier system.
Not easily at least. Better to leave this job to depsgraph, it knows
all the copies of data.
Although this works by itself, it should actually happen after:
"Reshuffle collections base flags evaluation, make it so object is gathering
its base flags from collections."
Meanwhile we have one single hacky function (deg_flush_base_flags_and_settings)
to be removed once the task above is tackled.
Reviewers: sergey
Differential Revision: https://developer.blender.org/D2899
Before it was a compile time option which was not very easy to use or test. Now
the project is getting more mature, so very soon we will be able to call for a
public tests of limited features.
The copy-on-write (which includes animation, modifiers) is enabled using
--enable-copy-on-write command line argument.
The is following: split copy on write update for node trees, and if we are only
tagging for uniform buffer update we skip whole datablock copy and only invoke
copy default_values form original nodetree to a copied one.
Thing which i'm not sure is: whether we need to use different branches in graph
itself to control such a conditional behavior, or whether we need to store tag
somewhere in the dependency graph. There are obviously cons and pros in both
approaches, and need to think about this. Maybe with more examples it becomes
more obvious which way is better.
This only fixes manual tweaks for now, animation support is coming.
This commit is a work forward having less updates during playback, which speeds
things up a lot here. The idea is simple: stop update all copy-on-write
datablocks (which implies full re-evaluation actually) on frame change and
re-use existing evaluated meshes as much as possible.
This brings playback speed to 24 fps on the dino test scene here. Performance
drops down a lot when armature is animated tho, but that's because of need of
tangent space calculation which we can't do much about from just a dependency
graph.
Hopefully this doesn't make copy-on-write too unstable, quick tests here are
surviving fine.
