## What type of PR is this? (check all applicable)
Release Invoke 3.6.3
## Have you discussed this change with the InvokeAI team?
- [X] Yes
- [ ] No, because:
## Have you updated all relevant documentation?
- [X] Yes
- [ ] No
## Description
Invoke 3.6.3 Release
## QA Instructions, Screenshots, Recordings
Test the installer:
[InvokeAI-installer-v3.6.3.zip](https://github.com/invoke-ai/InvokeAI/files/14233359/InvokeAI-installer-v3.6.3.zip)
<!--
Please provide steps on how to test changes, any hardware or
software specifications as well as any other pertinent information.
-->
## Merge Plan
Merge once approved
<!--
A merge plan describes how this PR should be handled after it is
approved.
Example merge plans:
- "This PR can be merged when approved"
- "This must be squash-merged when approved"
- "DO NOT MERGE - I will rebase and tidy commits before merging"
- "#dev-chat on discord needs to be advised of this change when it is
merged"
A merge plan is particularly important for large PRs or PRs that touch
the
database in any way.
-->
## [optional] Are there any post deployment tasks we need to perform?
1. Release on PyPi & GitHub
2. Announce on Discord
## What type of PR is this? (check all applicable)
- [ ] Refactor
- [ ] Feature
- [ ] Bug Fix
- [ ] Optimization
- [x] Documentation Update
- [ ] Community Node Submission
## Have you discussed this change with the InvokeAI team?
- [ ] Yes
- [x] No, because: it is text only, simple, and (hopefully) self-evident
## Have you updated all relevant documentation?
- [x] Yes - as far as I can grep.
- [ ] No
## Description
`.env.sample` was misspelled as `env.sample` in a few places.
This changes documentation only. You may need to re-build/deploy docs,
I'm not sure.
## What type of PR is this? (check all applicable)
- [ ] Refactor
- [ ] Feature
- [x] Bug Fix
- [ ] Optimization
- [ ] Documentation Update
- [ ] Community Node Submission
## Description
The change to memory session storage brings a subtle behaviour change.
Previously, we serialized and deserialized everything (e.g. field state,
invocation outputs, etc) constantly. The meant we were effectively
working with deep-copied objects at all time. We could mutate objects
freely without worrying about other references to the object.
With memory storage, objects are now passed around by reference, and we
cannot handle them in the same way.
This is problematic for nodes that mutate their own inputs. There are
two ways this causes a problem:
- An output is used as input for multiple nodes. If the first node
mutates the output object while `invoke`ing, the next node will get the
mutated object.
- The invocation cache stores live python objects. When a node mutates
an output pulled from the cache, the next node that uses the cached
object will get the mutated object.
The solution is to deep-copy a node's inputs as they are set,
effectively reproducing the same behaviour as we had with the SQLite
session storage. Nodes can safely mutate their inputs and those changes
never leave the node's scope.
## Related Tickets & Documents
<!--
For pull requests that relate or close an issue, please include them
below.
For example having the text: "closes #1234" would connect the current
pull
request to issue 1234. And when we merge the pull request, Github will
automatically close the issue.
-->
- Closes #5665
The root issue affects CLIP Skip because that node mutates its input
`ClipField`. Specifically, it increments `self.clip.skipped_layers` and
passes `self.clip` as its output. I don't know if there are any other
nodes that do this.
## QA Instructions, Screenshots, Recordings
Two issues to reproduce.
First is the caching issue:
Note the cache is enabled. Run this simple graph a couple times, and
check the outputs of the CLIP Skip node. You'll see the `skipped_layers`
value increasing each time.
Second is the nodes-sharing-inputs issue:
Note the cache is _disabled_. Run the graph a couple times and check the
outputs of the two CLIP Skip nodes. You'll see that one has the expected
value for `skipped_layers` and the other has double that.
Now update to the PR and try again. You should see `skipped_layers` is
the right value in all cases.
<!--
Please provide steps on how to test changes, any hardware or
software specifications as well as any other pertinent information.
-->
## Merge Plan
This PR can be merged when approved. It needs a real review with
braintime.
<!--
A merge plan describes how this PR should be handled after it is
approved.
Example merge plans:
- "This PR can be merged when approved"
- "This must be squash-merged when approved"
- "DO NOT MERGE - I will rebase and tidy commits before merging"
- "#dev-chat on discord needs to be advised of this change when it is
merged"
A merge plan is particularly important for large PRs or PRs that touch
the
database in any way.
-->
The change to memory session storage brings a subtle behaviour change.
Previously, we serialized and deserialized everything (e.g. field state, invocation outputs, etc) constantly. The meant we were effectively working with deep-copied objects at all time. We could mutate objects freely without worrying about other references to the object.
With memory storage, objects are now passed around by reference, and we cannot handle them in the same way.
This is problematic for nodes that mutate their own inputs. There are two ways this causes a problem:
- An output is used as input for multiple nodes. If the first node mutates the output object while `invoke`ing, the next node will get the mutated object.
- The invocation cache stores live python objects. When a node mutates an output pulled from the cache, the next node that uses the cached object will get the mutated object.
The solution is to deep-copy a node's inputs as they are set, effectively reproducing the same behaviour as we had with the SQLite session storage. Nodes can safely mutate their inputs and those changes never leave the node's scope.
Closes #5665
Currently translated at 74.4% (1054 of 1416 strings)
translationBot(ui): update translation (German)
Currently translated at 69.6% (986 of 1416 strings)
translationBot(ui): update translation (German)
Currently translated at 68.6% (972 of 1416 strings)
Co-authored-by: B N <berndnieschalk@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/
Translation: InvokeAI/Web UI
…elected
## What type of PR is this? (check all applicable)
- [ ] Refactor
- [ ] Feature
- [x] Bug Fix
- [ ] Optimization
- [ ] Documentation Update
- [ ] Community Node Submission
## Have you discussed this change with the InvokeAI team?
- [x] Yes
- [ ] No, because:
## Have you updated all relevant documentation?
- [ ] Yes
- [ ] No
## Description
Small bugfix: the installer would always print the latest stable version
as the one to be installed, even if a different one was selected. The
selected version would still be installed correctly. This PR fixes the
message.
## QA Instructions, Screenshots, Recordings
Select a pre-release version on install and observe the correct version
being printed. Compare to current behaviour to ascertain the fix.
## Merge Plan
- "This PR can be merged when approved"
## Added/updated tests?
- [ ] Yes
- [x] No
This has repeatedly shown itself useful in fixing install issues,
especially regarding pytorch CPU/GPU version, so there is little
downside to making this the default.
Performance impact of this should be negligible. Packages will
be reinstalled from pip cache if possible, and downloaded only if
necessary. Impact may be felt on slower disks.
