There was an issue where for graphs w/ iterations, your images were output all at once, at the very end of processing. So if you canceled halfway through an execution of 10 nodes, you wouldn't get any images - even though you'd completed 5 images' worth of inference.
## Cause
Because graphs executed breadth-first (i.e. depth-by-depth), leaf nodes were necessarily processed last. For image generation graphs, your `LatentsToImage` will be leaf nodes, and be the last depth to be executed.
For example, a `TextToLatents` graph w/ 3 iterations would execute all 3 `TextToLatents` nodes fully before moving to the next depth, where the `LatentsToImage` nodes produce output images, resulting in a node execution order like this:
1. TextToLatents
2. TextToLatents
3. TextToLatents
4. LatentsToImage
5. LatentsToImage
6. LatentsToImage
## Solution
This PR makes a two changes to graph execution to execute as deeply as it can along each branch of the graph.
### Eager node preparation
We now prepare as many nodes as possible, instead of just a single node at a time.
We also need to change the conditions in which nodes are prepared. Previously, nodes were prepared only when all of their direct ancestors were executed.
The updated logic prepares nodes that:
- are *not* `Iterate` nodes whose inputs have *not* been executed
- do *not* have any unexecuted `Iterate` ancestor nodes
This results in graphs always being maximally prepared.
### Always execute the deepest prepared node
We now choose the next node to execute by traversing from the bottom of the graph instead of the top, choosing the first node whose inputs are all executed.
This means we always execute the deepest node possible.
## Result
Graphs now execute depth-first, so instead of an execution order like this:
1. TextToLatents
2. TextToLatents
3. TextToLatents
4. LatentsToImage
5. LatentsToImage
6. LatentsToImage
... we get an execution order like this:
1. TextToLatents
2. LatentsToImage
3. TextToLatents
4. LatentsToImage
5. TextToLatents
6. LatentsToImage
Immediately after inference, the image is decoded and sent to the gallery.
fixes#3400
- The invokeai.db database file has now been moved into
`INVOKEAIROOT/databases`. Using plural here for possible
future with more than one database file.
- Removed a few dangling debug messages that appeared during
testing.
- Rebuilt frontend to test web.
Because we dynamically insert images into the DB and UI's images state, `page`/`per_page` pagination makes loading the images awkward.
Using `offset`/`limit` pagination lets us query for images with an offset equal to the number of images already loaded (which match the query parameters).
The result is that we always get the correct next page of images when loading more.
- Remove `ImageType` entirely, it is confusing
- Create `ResourceOrigin`, may be `internal` or `external`
- Revamp `ImageCategory`, may be `general`, `mask`, `control`, `user`, `other`. Expect to add more as time goes on
- Update images `list` route to accept `include_categories` OR `exclude_categories` query parameters to afford finer-grained querying. All services are updated to accomodate this change.
The new setup should account for our types of images, including the combinations we couldn't really handle until now:
- Canvas init and masks
- Canvas when saved-to-gallery or merged
Currenly only used to make names for images, but when latents, conditioning, etc are managed in DB, will do the same for them.
Intended to eventually support custom naming schemes.
- `ImageType` is now restricted to `results` and `uploads`.
- Add a reserved `meta` field to nodes to hold the `is_intermediate` boolean. We can extend it in the future to support other node `meta`.
- Add a `is_intermediate` column to the `images` table to hold this. (When `latents`, `conditioning` etc are added to the DB, they will also have this column.)
- All nodes default to `*not* intermediate`. Nodes must explicitly be marked `intermediate` for their outputs to be `intermediate`.
- When building a graph, you can set `node.meta.is_intermediate=True` and it will be handled as an intermediate.
- Add a new `update()` method to the `ImageService`, and a route to call it. Updates have a strict model, currently only `session_id` and `image_category` may be updated.
- Add a new `update()` method to the `ImageRecordStorageService` to update the image record using the model.
When returning a `FileResponse`, we must provide a valid path, else an exception is raised outside the route handler.
Add the `validate_path` method back to the service so we can validate paths before returning the file.
I don't like this but apparently this is just how `starlette` and `fastapi` works with `FileResponse`.
- Address database feedback:
- Remove all the extraneous tables. Only an `images` table now:
- `image_type` and `image_category` are unrestricted strings. When creating images, the provided values are checked to ensure they are a valid type and category.
- Add `updated_at` and `deleted_at` columns. `deleted_at` is currently unused.
- Use SQLite's built-in timestamp features to populate these. Add a trigger to update `updated_at` when the row is updated. Currently no way to update a row.
- Rename the `id` column in `images` to `image_name`
- Rename `ImageCategory.IMAGE` to `ImageCategory.GENERAL`
- Move all exceptions outside their base classes to make them more portable.
- Add `width` and `height` columns to the database. These store the actual dimensions of the image file, whereas the metadata's `width` and `height` refer to the respective generation parameters and are nullable.
- Make `deserialize_image_record` take a `dict` instead of `sqlite3.Row`
- Improve comments throughout
- Tidy up unused code/files and some minor organisation
feat(nodes): add ResultsServiceABC & SqliteResultsService
**Doesn't actually work bc of circular imports. Can't even test it.**
- add a base class for ResultsService and SQLite implementation
- use `graph_execution_manager` `on_changed` callback to keep `results` table in sync
fix(nodes): fix results service bugs
chore(ui): regen api
fix(ui): fix type guards
feat(nodes): add `result_type` to results table, fix types
fix(nodes): do not shadow `list` builtin
feat(nodes): add results router
It doesn't work due to circular imports still
fix(nodes): Result class should use outputs classes, not fields
feat(ui): crude results router
fix(ui): send to canvas in currentimagebuttons not working
feat(nodes): add core metadata builder
feat(nodes): add design doc
feat(nodes): wip latents db stuff
feat(nodes): images_db_service and resources router
feat(nodes): wip images db & router
feat(nodes): update image related names
feat(nodes): update urlservice
feat(nodes): add high-level images service
- Make environment variable settings case InSenSiTive:
INVOKEAI_MAX_LOADED_MODELS and InvokeAI_Max_Loaded_Models
environment variables will both set `max_loaded_models`
- Updated realesrgan to use new config system.
- Updated textual_inversion_training to use new config system.
- Discovered a race condition when InvokeAIAppConfig is created
at module load time, which makes it impossible to customize
or replace the help message produced with --help on the command
line. To fix this, moved all instances of get_invokeai_config()
from module load time to object initialization time. Makes code
cleaner, too.
- Added `--from_file` argument to `invokeai-node-cli` and changed
github action to match. CI tests will hopefully work now.
1. if retrieving an item from the queue raises an exception, the
InvocationProcessor thread crashes, but the API continues running in
a non-functional state. This fixes the issue
2. when there are no items in the queue, sleep 1 second before checking
again.
3. Also ensures the thread isn't crashed if an exception is raised from
invoker, and emits the error event
Intentionally using base Exceptions because for now we don't know which
specific exception to expect.
Fixes (sort of)? #3222
On hyperthreaded CPUs we get two threads operating on the queue by
default on each core. This cases two threads to process queue items.
This results in pytorch errors and sometimes generates garbage.
Locking this to single thread makes sense because we are bound by the
number of GPUs in the system, not by CPU cores. And to parallelize
across GPUs we should just start multiple processors (and use async
instead of threading)
Fixes#3289
* feat(ui): add axios client generator and simple example
* fix(ui): update client & nodes test code w/ new Edge type
* chore(ui): organize generated files
* chore(ui): update .eslintignore, .prettierignore
* chore(ui): update openapi.json
* feat(backend): fixes for nodes/generator
* feat(ui): generate object args for api client
* feat(ui): more nodes api prototyping
* feat(ui): nodes cancel
* chore(ui): regenerate api client
* fix(ui): disable OG web server socket connection
* fix(ui): fix scrollbar styles typing and prop
just noticed the typo, and made the types stronger.
* feat(ui): add socketio types
* feat(ui): wip nodes
- extract api client method arg types instead of manually declaring them
- update example to display images
- general tidy up
* start building out node translations from frontend state and add notes about missing features
* use reference to sampler_name
* use reference to sampler_name
* add optional apiUrl prop
* feat(ui): start hooking up dynamic txt2img node generation, create middleware for session invocation
* feat(ui): write separate nodes socket layer, txt2img generating and rendering w single node
* feat(ui): img2img implementation
* feat(ui): get intermediate images working but types are stubbed out
* chore(ui): add support for package mode
* feat(ui): add nodes mode script
* feat(ui): handle random seeds
* fix(ui): fix middleware types
* feat(ui): add rtk action type guard
* feat(ui): disable NodeAPITest
This was polluting the network/socket logs.
* feat(ui): fix parameters panel border color
This commit should be elsewhere but I don't want to break my flow
* feat(ui): make thunk types more consistent
* feat(ui): add type guards for outputs
* feat(ui): load images on socket connect
Rudimentary
* chore(ui): bump redux-toolkit
* docs(ui): update readme
* chore(ui): regenerate api client
* chore(ui): add typescript as dev dependency
I am having trouble with TS versions after vscode updated and now uses TS 5. `madge` has installed 3.9.10 and for whatever reason my vscode wants to use that. Manually specifying 4.9.5 and then setting vscode to use that as the workspace TS fixes the issue.
* feat(ui): begin migrating gallery to nodes
Along the way, migrate to use RTK `createEntityAdapter` for gallery images, and separate `results` and `uploads` into separate slices. Much cleaner this way.
* feat(ui): clean up & comment results slice
* fix(ui): separate thunk for initial gallery load so it properly gets index 0
* feat(ui): POST upload working
* fix(ui): restore removed type
* feat(ui): patch api generation for headers access
* chore(ui): regenerate api
* feat(ui): wip gallery migration
* feat(ui): wip gallery migration
* chore(ui): regenerate api
* feat(ui): wip refactor socket events
* feat(ui): disable panels based on app props
* feat(ui): invert logic to be disabled
* disable panels when app mounts
* feat(ui): add support to disableTabs
* docs(ui): organise and update docs
* lang(ui): add toast strings
* feat(ui): wip events, comments, and general refactoring
* feat(ui): add optional token for auth
* feat(ui): export StatusIndicator and ModelSelect for header use
* feat(ui) working on making socket URL dynamic
* feat(ui): dynamic middleware loading
* feat(ui): prep for socket jwt
* feat(ui): migrate cancelation
also updated action names to be event-like instead of declaration-like
sorry, i was scattered and this commit has a lot of unrelated stuff in it.
* fix(ui): fix img2img type
* chore(ui): regenerate api client
* feat(ui): improve InvocationCompleteEvent types
* feat(ui): increase StatusIndicator font size
* fix(ui): fix middleware order for multi-node graphs
* feat(ui): add exampleGraphs object w/ iterations example
* feat(ui): generate iterations graph
* feat(ui): update ModelSelect for nodes API
* feat(ui): add hi-res functionality for txt2img generations
* feat(ui): "subscribe" to particular nodes
feels like a dirty hack but oh well it works
* feat(ui): first steps to node editor ui
* fix(ui): disable event subscription
it is not fully baked just yet
* feat(ui): wip node editor
* feat(ui): remove extraneous field types
* feat(ui): nodes before deleting stuff
* feat(ui): cleanup nodes ui stuff
* feat(ui): hook up nodes to redux
* fix(ui): fix handle
* fix(ui): add basic node edges & connection validation
* feat(ui): add connection validation styling
* feat(ui): increase edge width
* feat(ui): it blends
* feat(ui): wip model handling and graph topology validation
* feat(ui): validation connections w/ graphlib
* docs(ui): update nodes doc
* feat(ui): wip node editor
* chore(ui): rebuild api, update types
* add redux-dynamic-middlewares as a dependency
* feat(ui): add url host transformation
* feat(ui): handle already-connected fields
* feat(ui): rewrite SqliteItemStore in sqlalchemy
* fix(ui): fix sqlalchemy dynamic model instantiation
* feat(ui, nodes): metadata wip
* feat(ui, nodes): models
* feat(ui, nodes): more metadata wip
* feat(ui): wip range/iterate
* fix(nodes): fix sqlite typing
* feat(ui): export new type for invoke component
* tests(nodes): fix test instantiation of ImageField
* feat(nodes): fix LoadImageInvocation
* feat(nodes): add `title` ui hint
* feat(nodes): make ImageField attrs optional
* feat(ui): wip nodes etc
* feat(nodes): roll back sqlalchemy
* fix(nodes): partially address feedback
* fix(backend): roll back changes to pngwriter
* feat(nodes): wip address metadata feedback
* feat(nodes): add seeded rng to RandomRange
* feat(nodes): address feedback
* feat(nodes): move GET images error handling to DiskImageStorage
* feat(nodes): move GET images error handling to DiskImageStorage
* fix(nodes): fix image output schema customization
* feat(ui): img2img/txt2img -> linear
- remove txt2img and img2img tabs
- add linear tab
- add initial image selection to linear parameters accordion
* feat(ui): tidy graph builders
* feat(ui): tidy misc
* feat(ui): improve invocation union types
* feat(ui): wip metadata viewer recall
* feat(ui): move fonts to normal deps
* feat(nodes): fix broken upload
* feat(nodes): add metadata module + tests, thumbnails
- `MetadataModule` is stateless and needed in places where the `InvocationContext` is not available, so have not made it a `service`
- Handles loading/parsing/building metadata, and creating png info objects
- added tests for MetadataModule
- Lifted thumbnail stuff to util
* fix(nodes): revert change to RandomRangeInvocation
* feat(nodes): address feedback
- make metadata a service
- rip out pydantic validation, implement metadata parsing as simple functions
- update tests
- address other minor feedback items
* fix(nodes): fix other tests
* fix(nodes): add metadata service to cli
* fix(nodes): fix latents/image field parsing
* feat(nodes): customise LatentsField schema
* feat(nodes): move metadata parsing to frontend
* fix(nodes): fix metadata test
---------
Co-authored-by: maryhipp <maryhipp@gmail.com>
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
- add `list_images` endpoint at `GET api/v1/images`
- extend `ImageStorageBase` with `list()` method, implemented it for `DiskImageStorage`
- add `ImageReponse` class to for image responses, which includes urls, metadata
- add `ImageMetadata` class (basically a stub at the moment)
- uploaded images now named `"{uuid}_{timestamp}.png"`
- add `models` modules. besides separating concerns more clearly, this helps to mitigate circular dependencies
- improve thumbnail handling
* Add latents nodes.
* Fix iteration expansion.
* Add collection generator nodes, math nodes.
* Add noise node.
* Add some graph debug commands to the CLI.
* Fix negative id linking in CLI.
* Fix a CLI bug with multiple links per node.
This PR fixes the following scripts:
1) Scripts that can be executed within the repo's scripts directory.
Note that these are for development testing and are not intended
to be exposed to the user.
configure_invokeai.py - configuration
dream.py - the legacy CLI
images2prompt.py - legacy "dream prompt" retriever
invoke-new.py - new nodes-based CLI
invoke.py - the legacy CLI under another name
make_models_markdown_table.py - a utility used during the release/doc process
pypi_helper.py - another utility used during the release process
sd-metadata.py - retrieve JSON-formatted metadata from a PNG file
2) Scripts that are installed by pip install. They get placed into the venv's
PATH and are intended to be the official entry points:
invokeai-node-cli - new nodes-based CLI
invokeai-node-web - new nodes-based web server
invokeai - legacy CLI
invokeai-configure - install time configuration script
invokeai-merge - model merging script
invokeai-ti - textual inversion script
invokeai-model-install - model installer
invokeai-update - update script
invokeai-metadata" - retrieve JSON-formatted metadata from PNG files
