2023-02-18 04:23:24 +00:00
{
2023-03-08 03:30:51 +00:00
"accessibility" : {
2023-03-11 02:49:16 +00:00
"copyMetadataJson" : "Copy metadata JSON" ,
2023-04-24 06:03:48 +00:00
"exitViewer" : "Exit Viewer" ,
2023-03-11 02:49:16 +00:00
"flipHorizontally" : "Flip Horizontally" ,
"flipVertically" : "Flip Vertically" ,
2023-09-13 07:31:34 +00:00
"invokeProgressBar" : "Invoke progress bar" ,
"menu" : "Menu" ,
"modelSelect" : "Model Select" ,
2023-03-11 02:49:16 +00:00
"modifyConfig" : "Modify Config" ,
2023-09-13 07:31:34 +00:00
"nextImage" : "Next Image" ,
"previousImage" : "Previous Image" ,
"reset" : "Reset" ,
"rotateClockwise" : "Rotate Clockwise" ,
"rotateCounterClockwise" : "Rotate Counter-Clockwise" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"showGalleryPanel" : "Show Gallery Panel" ,
2023-08-23 04:17:18 +00:00
"showOptionsPanel" : "Show Side Panel" ,
2023-09-13 07:31:34 +00:00
"toggleAutoscroll" : "Toggle autoscroll" ,
"toggleLogViewer" : "Toggle Log Viewer" ,
"uploadImage" : "Upload Image" ,
"useThisParameter" : "Use this parameter" ,
"zoomIn" : "Zoom In" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"zoomOut" : "Zoom Out" ,
"loadMore" : "Load More"
2023-09-13 07:31:34 +00:00
} ,
"boards" : {
"addBoard" : "Add Board" ,
"autoAddBoard" : "Auto-Add Board" ,
"bottomMessage" : "Deleting this board and its images will reset any features currently using them." ,
"cancel" : "Cancel" ,
"changeBoard" : "Change Board" ,
"clearSearch" : "Clear Search" ,
"loading" : "Loading..." ,
"menuItemAutoAdd" : "Auto-add to this Board" ,
"move" : "Move" ,
"myBoard" : "My Board" ,
"noMatching" : "No matching Boards" ,
"searchBoard" : "Search Boards..." ,
"selectBoard" : "Select a Board" ,
"topMessage" : "This board contains images used in the following features:" ,
2023-10-11 23:27:22 +00:00
"uncategorized" : "Uncategorized" ,
"downloadBoard" : "Download Board"
2023-03-08 03:30:51 +00:00
} ,
2023-02-18 04:23:24 +00:00
"common" : {
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"accept" : "Accept" ,
"advanced" : "Advanced" ,
"areYouSure" : "Are you sure?" ,
2023-10-12 11:46:47 +00:00
"auto" : "Auto" ,
2023-09-13 07:31:34 +00:00
"back" : "Back" ,
"batch" : "Batch Manager" ,
"cancel" : "Cancel" ,
"close" : "Close" ,
2023-10-12 11:46:47 +00:00
"on" : "On" ,
2023-07-26 05:33:02 +00:00
"communityLabel" : "Community" ,
2023-10-07 06:07:32 +00:00
"controlNet" : "ControlNet" ,
2023-10-05 11:40:21 +00:00
"controlAdapter" : "Control Adapter" ,
2023-09-16 00:50:30 +00:00
"ipAdapter" : "IP Adapter" ,
2023-10-07 06:07:32 +00:00
"t2iAdapter" : "T2I Adapter" ,
2023-06-29 18:05:08 +00:00
"darkMode" : "Dark Mode" ,
2023-02-18 04:23:24 +00:00
"discordLabel" : "Discord" ,
2023-09-13 07:31:34 +00:00
"dontAskMeAgain" : "Don't ask me again" ,
"generate" : "Generate" ,
"githubLabel" : "Github" ,
"hotkeysLabel" : "Hotkeys" ,
"imagePrompt" : "Image Prompt" ,
2023-09-26 15:24:53 +00:00
"imageFailedToLoad" : "Unable to Load Image" ,
2023-09-13 07:31:34 +00:00
"img2img" : "Image To Image" ,
2023-02-18 04:23:24 +00:00
"langArabic" : "العربية" ,
2023-09-13 07:31:34 +00:00
"langBrPortuguese" : "Português do Brasil" ,
2023-02-18 04:23:24 +00:00
"langDutch" : "Nederlands" ,
2023-09-13 07:31:34 +00:00
"langEnglish" : "English" ,
2023-02-18 04:23:24 +00:00
"langFrench" : "Français" ,
"langGerman" : "Deutsch" ,
2023-03-06 09:02:40 +00:00
"langHebrew" : "עברית" ,
2023-02-18 04:23:24 +00:00
"langItalian" : "Italiano" ,
"langJapanese" : "日本語" ,
2023-03-06 09:02:40 +00:00
"langKorean" : "한국어" ,
2023-02-18 04:23:24 +00:00
"langPolish" : "Polski" ,
2023-03-06 09:02:40 +00:00
"langPortuguese" : "Português" ,
2023-02-18 04:23:24 +00:00
"langRussian" : "Русский" ,
"langSimplifiedChinese" : "简体中文" ,
"langSpanish" : "Español" ,
2023-09-13 07:31:34 +00:00
"languagePickerLabel" : "Language" ,
"langUkranian" : "Украї́нська" ,
"lightMode" : "Light Mode" ,
Partial migration of UI to nodes API (#3195)
* 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>
2023-04-22 03:10:20 +00:00
"linear" : "Linear" ,
2023-09-13 07:31:34 +00:00
"load" : "Load" ,
2023-09-27 14:54:20 +00:00
"loading" : "Loading" ,
2023-09-13 07:31:34 +00:00
"loadingInvokeAI" : "Loading Invoke AI" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"learnMore" : "Learn More" ,
2023-07-08 00:19:51 +00:00
"modelManager" : "Model Manager" ,
2023-09-13 07:31:34 +00:00
"nodeEditor" : "Node Editor" ,
"nodes" : "Workflow Editor" ,
2023-02-18 04:23:24 +00:00
"nodesDesc" : "A node based system for the generation of images is under development currently. Stay tuned for updates about this amazing feature." ,
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"openInNewTab" : "Open in New Tab" ,
2023-02-18 04:23:24 +00:00
"postProcessDesc1" : "Invoke AI offers a wide variety of post processing features. Image Upscaling and Face Restoration are already available in the WebUI. You can access them from the Advanced Options menu of the Text To Image and Image To Image tabs. You can also process images directly, using the image action buttons above the current image display or in the viewer." ,
"postProcessDesc2" : "A dedicated UI will be released soon to facilitate more advanced post processing workflows." ,
"postProcessDesc3" : "The Invoke AI Command Line Interface offers various other features including Embiggen." ,
2023-09-13 07:31:34 +00:00
"postprocessing" : "Post Processing" ,
"postProcessing" : "Post Processing" ,
"random" : "Random" ,
"reportBugLabel" : "Report Bug" ,
"settingsLabel" : "Settings" ,
2023-02-18 04:23:24 +00:00
"statusConnected" : "Connected" ,
2023-09-13 07:31:34 +00:00
"statusConvertingModel" : "Converting Model" ,
2023-02-18 04:23:24 +00:00
"statusDisconnected" : "Disconnected" ,
"statusError" : "Error" ,
"statusGenerating" : "Generating" ,
"statusGeneratingImageToImage" : "Generating Image To Image" ,
"statusGeneratingInpainting" : "Generating Inpainting" ,
"statusGeneratingOutpainting" : "Generating Outpainting" ,
2023-09-13 07:31:34 +00:00
"statusGeneratingTextToImage" : "Generating Text To Image" ,
2023-02-18 04:23:24 +00:00
"statusGenerationComplete" : "Generation Complete" ,
"statusIterationComplete" : "Iteration Complete" ,
2023-09-13 07:31:34 +00:00
"statusLoadingModel" : "Loading Model" ,
"statusMergedModels" : "Models Merged" ,
"statusMergingModels" : "Merging Models" ,
"statusModelChanged" : "Model Changed" ,
"statusModelConverted" : "Model Converted" ,
"statusPreparing" : "Preparing" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"statusProcessing" : "Processing" ,
2023-09-13 07:31:34 +00:00
"statusProcessingCanceled" : "Processing Canceled" ,
"statusProcessingComplete" : "Processing Complete" ,
2023-02-18 04:23:24 +00:00
"statusRestoringFaces" : "Restoring Faces" ,
"statusRestoringFacesCodeFormer" : "Restoring Faces (CodeFormer)" ,
2023-09-13 07:31:34 +00:00
"statusRestoringFacesGFPGAN" : "Restoring Faces (GFPGAN)" ,
"statusSavingImage" : "Saving Image" ,
2023-02-18 04:23:24 +00:00
"statusUpscaling" : "Upscaling" ,
"statusUpscalingESRGAN" : "Upscaling (ESRGAN)" ,
2023-09-13 07:31:34 +00:00
"training" : "Training" ,
"trainingDesc1" : "A dedicated workflow for training your own embeddings and checkpoints using Textual Inversion and Dreambooth from the web interface." ,
"trainingDesc2" : "InvokeAI already supports training custom embeddourings using Textual Inversion using the main script." ,
"txt2img" : "Text To Image" ,
"unifiedCanvas" : "Unified Canvas" ,
"upload" : "Upload"
} ,
"controlnet" : {
2023-10-12 11:46:47 +00:00
"controlAdapter_one" : "Control Adapter" ,
"controlAdapter_other" : "Control Adapters" ,
2023-10-15 07:16:10 +00:00
"controlnet" : "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.controlNet))" ,
"ip_adapter" : "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.ipAdapter))" ,
"t2i_adapter" : "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.t2iAdapter))" ,
2023-10-07 06:07:32 +00:00
"addControlNet" : "Add $t(common.controlNet)" ,
"addIPAdapter" : "Add $t(common.ipAdapter)" ,
"addT2IAdapter" : "Add $t(common.t2iAdapter)" ,
2023-10-07 07:16:19 +00:00
"controlNetEnabledT2IDisabled" : "$t(common.controlNet) enabled, $t(common.t2iAdapter)s disabled" ,
"t2iEnabledControlNetDisabled" : "$t(common.t2iAdapter) enabled, $t(common.controlNet)s disabled" ,
"controlNetT2IMutexDesc" : "$t(common.controlNet) and $t(common.t2iAdapter) at same time is currently unsupported." ,
2023-09-13 07:31:34 +00:00
"amult" : "a_mult" ,
"autoConfigure" : "Auto configure processor" ,
"balanced" : "Balanced" ,
"beginEndStepPercent" : "Begin / End Step Percentage" ,
"bgth" : "bg_th" ,
"canny" : "Canny" ,
"cannyDescription" : "Canny edge detection" ,
2023-09-22 20:49:15 +00:00
"colorMap" : "Color" ,
"colorMapDescription" : "Generates a color map from the image" ,
2023-09-13 07:31:34 +00:00
"coarse" : "Coarse" ,
"contentShuffle" : "Content Shuffle" ,
"contentShuffleDescription" : "Shuffles the content in an image" ,
"control" : "Control" ,
"controlMode" : "Control Mode" ,
"crop" : "Crop" ,
"delete" : "Delete" ,
"depthMidas" : "Depth (Midas)" ,
"depthMidasDescription" : "Depth map generation using Midas" ,
"depthZoe" : "Depth (Zoe)" ,
"depthZoeDescription" : "Depth map generation using Zoe" ,
"detectResolution" : "Detect Resolution" ,
"duplicate" : "Duplicate" ,
"enableControlnet" : "Enable ControlNet" ,
"f" : "F" ,
"fill" : "Fill" ,
"h" : "H" ,
"handAndFace" : "Hand and Face" ,
"hed" : "HED" ,
"hedDescription" : "Holistically-Nested Edge Detection" ,
"hideAdvanced" : "Hide Advanced" ,
"highThreshold" : "High Threshold" ,
"imageResolution" : "Image Resolution" ,
2023-09-22 20:49:15 +00:00
"colorMapTileSize" : "Tile Size" ,
2023-09-13 07:31:34 +00:00
"importImageFromCanvas" : "Import Image From Canvas" ,
"importMaskFromCanvas" : "Import Mask From Canvas" ,
"incompatibleBaseModel" : "Incompatible base model:" ,
"lineart" : "Lineart" ,
"lineartAnime" : "Lineart Anime" ,
"lineartAnimeDescription" : "Anime-style lineart processing" ,
"lineartDescription" : "Converts image to lineart" ,
"lowThreshold" : "Low Threshold" ,
"maxFaces" : "Max Faces" ,
"mediapipeFace" : "Mediapipe Face" ,
"mediapipeFaceDescription" : "Face detection using Mediapipe" ,
"megaControl" : "Mega Control" ,
"minConfidence" : "Min Confidence" ,
"mlsd" : "M-LSD" ,
"mlsdDescription" : "Minimalist Line Segment Detector" ,
"none" : "None" ,
"noneDescription" : "No processing applied" ,
"normalBae" : "Normal BAE" ,
"normalBaeDescription" : "Normal BAE processing" ,
"openPose" : "Openpose" ,
"openPoseDescription" : "Human pose estimation using Openpose" ,
"pidi" : "PIDI" ,
"pidiDescription" : "PIDI image processing" ,
"processor" : "Processor" ,
"prompt" : "Prompt" ,
"resetControlImage" : "Reset Control Image" ,
"resize" : "Resize" ,
"resizeMode" : "Resize Mode" ,
"safe" : "Safe" ,
"saveControlImage" : "Save Control Image" ,
"scribble" : "scribble" ,
"selectModel" : "Select a model" ,
"setControlImageDimensions" : "Set Control Image Dimensions To W/H" ,
"showAdvanced" : "Show Advanced" ,
"toggleControlNet" : "Toggle this ControlNet" ,
"w" : "W" ,
2023-09-15 23:33:29 +00:00
"weight" : "Weight" ,
"enableIPAdapter" : "Enable IP Adapter" ,
2023-09-16 00:14:04 +00:00
"ipAdapterModel" : "Adapter Model" ,
"resetIPAdapterImage" : "Reset IP Adapter Image" ,
"ipAdapterImageFallback" : "No IP Adapter Image Selected"
2023-09-13 07:31:34 +00:00
} ,
"embedding" : {
"addEmbedding" : "Add Embedding" ,
"incompatibleModel" : "Incompatible base model:" ,
"noMatchingEmbedding" : "No matching Embeddings"
2023-02-18 04:23:24 +00:00
} ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"queue" : {
"queue" : "Queue" ,
"queueFront" : "Add to Front of Queue" ,
"queueBack" : "Add to Queue" ,
"queueCountPrediction" : "Add {{predicted}} to Queue" ,
"queueMaxExceeded" : "Max of {{max_queue_size}} exceeded, would skip {{skip}}" ,
"queuedCount" : "{{pending}} Pending" ,
"queueTotal" : "{{total}} Total" ,
"queueEmpty" : "Queue Empty" ,
"enqueueing" : "Queueing Batch" ,
"resume" : "Resume" ,
"resumeTooltip" : "Resume Processor" ,
"resumeSucceeded" : "Processor Resumed" ,
"resumeFailed" : "Problem Resuming Processor" ,
"pause" : "Pause" ,
"pauseTooltip" : "Pause Processor" ,
"pauseSucceeded" : "Processor Paused" ,
"pauseFailed" : "Problem Pausing Processor" ,
"cancel" : "Cancel" ,
"cancelTooltip" : "Cancel Current Item" ,
"cancelSucceeded" : "Item Canceled" ,
"cancelFailed" : "Problem Canceling Item" ,
"prune" : "Prune" ,
"pruneTooltip" : "Prune {{item_count}} Completed Items" ,
"pruneSucceeded" : "Pruned {{item_count}} Completed Items from Queue" ,
"pruneFailed" : "Problem Pruning Queue" ,
"clear" : "Clear" ,
"clearTooltip" : "Cancel and Clear All Items" ,
"clearSucceeded" : "Queue Cleared" ,
"clearFailed" : "Problem Clearing Queue" ,
"cancelBatch" : "Cancel Batch" ,
"cancelItem" : "Cancel Item" ,
"cancelBatchSucceeded" : "Batch Canceled" ,
"cancelBatchFailed" : "Problem Canceling Batch" ,
2023-09-20 12:39:54 +00:00
"clearQueueAlertDialog" : "Clearing the queue immediately cancels any processing items and clears the queue entirely." ,
"clearQueueAlertDialog2" : "Are you sure you want to clear the queue?" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"current" : "Current" ,
"next" : "Next" ,
"status" : "Status" ,
"total" : "Total" ,
"pending" : "Pending" ,
"in_progress" : "In Progress" ,
"completed" : "Completed" ,
"failed" : "Failed" ,
"canceled" : "Canceled" ,
"completedIn" : "Completed in" ,
"batch" : "Batch" ,
"item" : "Item" ,
"session" : "Session" ,
"batchValues" : "Batch Values" ,
"notReady" : "Unable to Queue" ,
"batchQueued" : "Batch Queued" ,
2023-10-12 10:34:24 +00:00
"batchQueuedDesc_one" : "Added {{count}} sessions to {{direction}} of queue" ,
"batchQueuedDesc_other" : "Added {{count}} sessions to {{direction}} of queue" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"front" : "front" ,
"back" : "back" ,
"batchFailedToQueue" : "Failed to Queue Batch" ,
"graphQueued" : "Graph queued" ,
"graphFailedToQueue" : "Failed to queue graph"
} ,
2023-09-21 08:57:52 +00:00
"invocationCache" : {
"invocationCache" : "Invocation Cache" ,
"cacheSize" : "Cache Size" ,
"maxCacheSize" : "Max Cache Size" ,
"hits" : "Cache Hits" ,
"misses" : "Cache Misses" ,
"clear" : "Clear" ,
"clearSucceeded" : "Invocation Cache Cleared" ,
"clearFailed" : "Problem Clearing Invocation Cache" ,
"enable" : "Enable" ,
"enableSucceeded" : "Invocation Cache Enabled" ,
"enableFailed" : "Problem Enabling Invocation Cache" ,
"disable" : "Disable" ,
"disableSucceeded" : "Invocation Cache Disabled" ,
"disableFailed" : "Problem Disabling Invocation Cache"
} ,
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"gallery" : {
"allImagesLoaded" : "All Images Loaded" ,
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"assets" : "Assets" ,
"autoAssignBoardOnClick" : "Auto-Assign Board on Click" ,
"autoSwitchNewImages" : "Auto-Switch to New Images" ,
"copy" : "Copy" ,
"currentlyInUse" : "This image is currently in use in the following features:" ,
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"deleteImage" : "Delete Image" ,
"deleteImageBin" : "Deleted images will be sent to your operating system's Bin." ,
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"deleteImagePermanent" : "Deleted images cannot be restored." ,
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"download" : "Download" ,
"featuresWillReset" : "If you delete this image, those features will immediately be reset." ,
"galleryImageResetSize" : "Reset Size" ,
"galleryImageSize" : "Image Size" ,
"gallerySettings" : "Gallery Settings" ,
"generations" : "Generations" ,
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"images" : "Images" ,
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"loading" : "Loading" ,
"loadMore" : "Load More" ,
"maintainAspectRatio" : "Maintain Aspect Ratio" ,
"noImagesInGallery" : "No Images to Display" ,
"setCurrentImage" : "Set as Current Image" ,
"showGenerations" : "Show Generations" ,
"showUploads" : "Show Uploads" ,
"singleColumnLayout" : "Single Column Layout" ,
"unableToLoad" : "Unable to load Gallery" ,
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"uploads" : "Uploads" ,
"downloadSelection" : "Download Selection" ,
"preparingDownload" : "Preparing Download" ,
"preparingDownloadFailed" : "Problem Preparing Download"
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} ,
"hotkeys" : {
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"acceptStagingImage" : {
"desc" : "Accept Current Staging Area Image" ,
"title" : "Accept Staging Image"
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} ,
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"addNodes" : {
"desc" : "Opens the add node menu" ,
"title" : "Add Nodes"
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} ,
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"appHotkeys" : "App Hotkeys" ,
"cancel" : {
"desc" : "Cancel image generation" ,
"title" : "Cancel"
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} ,
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"changeTabs" : {
"desc" : "Switch to another workspace" ,
"title" : "Change Tabs"
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} ,
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"clearMask" : {
"desc" : "Clear the entire mask" ,
"title" : "Clear Mask"
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} ,
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"closePanels" : {
"desc" : "Closes open panels" ,
"title" : "Close Panels"
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} ,
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"colorPicker" : {
"desc" : "Selects the canvas color picker" ,
"title" : "Select Color Picker"
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} ,
"consoleToggle" : {
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"desc" : "Open and close console" ,
"title" : "Console Toggle"
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} ,
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"copyToClipboard" : {
"desc" : "Copy current canvas to clipboard" ,
"title" : "Copy to Clipboard"
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} ,
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"decreaseBrushOpacity" : {
"desc" : "Decreases the opacity of the canvas brush" ,
"title" : "Decrease Brush Opacity"
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} ,
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"decreaseBrushSize" : {
"desc" : "Decreases the size of the canvas brush/eraser" ,
"title" : "Decrease Brush Size"
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} ,
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"decreaseGalleryThumbSize" : {
"desc" : "Decreases gallery thumbnails size" ,
"title" : "Decrease Gallery Image Size"
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} ,
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"deleteImage" : {
"desc" : "Delete the current image" ,
"title" : "Delete Image"
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} ,
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"downloadImage" : {
"desc" : "Download current canvas" ,
"title" : "Download Image"
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} ,
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"eraseBoundingBox" : {
"desc" : "Erases the bounding box area" ,
"title" : "Erase Bounding Box"
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} ,
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"fillBoundingBox" : {
"desc" : "Fills the bounding box with brush color" ,
"title" : "Fill Bounding Box"
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} ,
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"focusPrompt" : {
"desc" : "Focus the prompt input area" ,
"title" : "Focus Prompt"
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} ,
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"galleryHotkeys" : "Gallery Hotkeys" ,
"generalHotkeys" : "General Hotkeys" ,
"hideMask" : {
"desc" : "Hide and unhide mask" ,
"title" : "Hide Mask"
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} ,
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"increaseBrushOpacity" : {
"desc" : "Increases the opacity of the canvas brush" ,
"title" : "Increase Brush Opacity"
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} ,
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"increaseBrushSize" : {
"desc" : "Increases the size of the canvas brush/eraser" ,
"title" : "Increase Brush Size"
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} ,
"increaseGalleryThumbSize" : {
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"desc" : "Increases gallery thumbnails size" ,
"title" : "Increase Gallery Image Size"
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} ,
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"invoke" : {
"desc" : "Generate an image" ,
"title" : "Invoke"
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} ,
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"keyboardShortcuts" : "Keyboard Shortcuts" ,
"maximizeWorkSpace" : {
"desc" : "Close panels and maximize work area" ,
"title" : "Maximize Workspace"
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} ,
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"mergeVisible" : {
"desc" : "Merge all visible layers of canvas" ,
"title" : "Merge Visible"
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} ,
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"moveTool" : {
"desc" : "Allows canvas navigation" ,
"title" : "Move Tool"
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} ,
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"nextImage" : {
"desc" : "Display the next image in gallery" ,
"title" : "Next Image"
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} ,
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"nextStagingImage" : {
"desc" : "Next Staging Area Image" ,
"title" : "Next Staging Image"
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} ,
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"nodesHotkeys" : "Nodes Hotkeys" ,
"pinOptions" : {
"desc" : "Pin the options panel" ,
"title" : "Pin Options"
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} ,
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"previousImage" : {
"desc" : "Display the previous image in gallery" ,
"title" : "Previous Image"
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} ,
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"previousStagingImage" : {
"desc" : "Previous Staging Area Image" ,
"title" : "Previous Staging Image"
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} ,
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"quickToggleMove" : {
"desc" : "Temporarily toggles Move mode" ,
"title" : "Quick Toggle Move"
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} ,
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"redoStroke" : {
"desc" : "Redo a brush stroke" ,
"title" : "Redo Stroke"
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} ,
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"resetView" : {
"desc" : "Reset Canvas View" ,
"title" : "Reset View"
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} ,
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"restoreFaces" : {
"desc" : "Restore the current image" ,
"title" : "Restore Faces"
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} ,
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"saveToGallery" : {
"desc" : "Save current canvas to gallery" ,
"title" : "Save To Gallery"
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} ,
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"selectBrush" : {
"desc" : "Selects the canvas brush" ,
"title" : "Select Brush"
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} ,
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"selectEraser" : {
"desc" : "Selects the canvas eraser" ,
"title" : "Select Eraser"
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} ,
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"sendToImageToImage" : {
"desc" : "Send current image to Image to Image" ,
"title" : "Send To Image To Image"
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} ,
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"setParameters" : {
"desc" : "Use all parameters of the current image" ,
"title" : "Set Parameters"
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} ,
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"setPrompt" : {
"desc" : "Use the prompt of the current image" ,
"title" : "Set Prompt"
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} ,
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"setSeed" : {
"desc" : "Use the seed of the current image" ,
"title" : "Set Seed"
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} ,
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"showHideBoundingBox" : {
"desc" : "Toggle visibility of bounding box" ,
"title" : "Show/Hide Bounding Box"
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} ,
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"showInfo" : {
"desc" : "Show metadata info of the current image" ,
"title" : "Show Info"
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} ,
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"toggleGallery" : {
"desc" : "Open and close the gallery drawer" ,
"title" : "Toggle Gallery"
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} ,
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"toggleGalleryPin" : {
"desc" : "Pins and unpins the gallery to the UI" ,
"title" : "Toggle Gallery Pin"
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} ,
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"toggleLayer" : {
"desc" : "Toggles mask/base layer selection" ,
"title" : "Toggle Layer"
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} ,
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"toggleOptions" : {
"desc" : "Open and close the options panel" ,
"title" : "Toggle Options"
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} ,
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"toggleSnap" : {
"desc" : "Toggles Snap to Grid" ,
"title" : "Toggle Snap"
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} ,
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"toggleViewer" : {
"desc" : "Open and close Image Viewer" ,
"title" : "Toggle Viewer"
} ,
"undoStroke" : {
"desc" : "Undo a brush stroke" ,
"title" : "Undo Stroke"
} ,
"unifiedCanvasHotkeys" : "Unified Canvas Hotkeys" ,
"upscale" : {
"desc" : "Upscale the current image" ,
"title" : "Upscale"
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}
} ,
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"metadata" : {
"cfgScale" : "CFG scale" ,
"createdBy" : "Created By" ,
"fit" : "Image to image fit" ,
"generationMode" : "Generation Mode" ,
"height" : "Height" ,
"hiresFix" : "High Resolution Optimization" ,
"imageDetails" : "Image Details" ,
"initImage" : "Initial image" ,
"metadata" : "Metadata" ,
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"model" : "Model" ,
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"negativePrompt" : "Negative Prompt" ,
"noImageDetails" : "No image details found" ,
"noMetaData" : "No metadata found" ,
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"noRecallParameters" : "No parameters to recall found" ,
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"perlin" : "Perlin Noise" ,
"positivePrompt" : "Positive Prompt" ,
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"recallParameters" : "Recall Parameters" ,
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"scheduler" : "Scheduler" ,
"seamless" : "Seamless" ,
"seed" : "Seed" ,
"steps" : "Steps" ,
"strength" : "Image to image strength" ,
"Threshold" : "Noise Threshold" ,
"variations" : "Seed-weight pairs" ,
"width" : "Width" ,
"workflow" : "Workflow"
} ,
"modelManager" : {
"active" : "active" ,
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"addCheckpointModel" : "Add Checkpoint / Safetensor Model" ,
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"addDifference" : "Add Difference" ,
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"addDiffuserModel" : "Add Diffusers" ,
"addManually" : "Add Manually" ,
"addModel" : "Add Model" ,
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"addNew" : "Add New" ,
"addNewModel" : "Add New Model" ,
"addSelected" : "Add Selected" ,
"advanced" : "Advanced" ,
"allModels" : "All Models" ,
"alpha" : "Alpha" ,
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"availableModels" : "Available Models" ,
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"baseModel" : "Base Model" ,
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"cached" : "cached" ,
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"cannotUseSpaces" : "Cannot Use Spaces" ,
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"checkpointFolder" : "Checkpoint Folder" ,
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"checkpointModels" : "Checkpoints" ,
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"clearCheckpointFolder" : "Clear Checkpoint Folder" ,
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"closeAdvanced" : "Close Advanced" ,
"config" : "Config" ,
"configValidationMsg" : "Path to the config file of your model." ,
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"convert" : "Convert" ,
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"convertingModelBegin" : "Converting Model. Please wait." ,
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"convertToDiffusers" : "Convert To Diffusers" ,
"convertToDiffusersHelpText1" : "This model will be converted to the 🧨 Diffusers format." ,
"convertToDiffusersHelpText2" : "This process will replace your Model Manager entry with the Diffusers version of the same model." ,
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"convertToDiffusersHelpText3" : "Your checkpoint file on disk WILL be deleted if it is in InvokeAI root folder. If it is in a custom location, then it WILL NOT be deleted." ,
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"convertToDiffusersHelpText4" : "This is a one time process only. It might take around 30s-60s depending on the specifications of your computer." ,
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"convertToDiffusersHelpText5" : "Please make sure you have enough disk space. Models generally vary between 2GB-7GB in size." ,
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"convertToDiffusersHelpText6" : "Do you wish to convert this model?" ,
"convertToDiffusersSaveLocation" : "Save Location" ,
"custom" : "Custom" ,
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"customConfig" : "Custom Config" ,
"customConfigFileLocation" : "Custom Config File Location" ,
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"customSaveLocation" : "Custom Save Location" ,
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"delete" : "Delete" ,
"deleteConfig" : "Delete Config" ,
"deleteModel" : "Delete Model" ,
"deleteMsg1" : "Are you sure you want to delete this model from InvokeAI?" ,
"deleteMsg2" : "This WILL delete the model from disk if it is in the InvokeAI root folder. If you are using a custom location, then the model WILL NOT be deleted from disk." ,
"description" : "Description" ,
"descriptionValidationMsg" : "Add a description for your model" ,
"deselectAll" : "Deselect All" ,
"diffusersModels" : "Diffusers" ,
"findModels" : "Find Models" ,
"formMessageDiffusersModelLocation" : "Diffusers Model Location" ,
"formMessageDiffusersModelLocationDesc" : "Please enter at least one." ,
"formMessageDiffusersVAELocation" : "VAE Location" ,
"formMessageDiffusersVAELocationDesc" : "If not provided, InvokeAI will look for the VAE file inside the model location given above." ,
"height" : "Height" ,
"heightValidationMsg" : "Default height of your model." ,
"ignoreMismatch" : "Ignore Mismatches Between Selected Models" ,
"importModels" : "Import Models" ,
"inpainting" : "v1 Inpainting" ,
"interpolationType" : "Interpolation Type" ,
"inverseSigmoid" : "Inverse Sigmoid" ,
"invokeAIFolder" : "Invoke AI Folder" ,
"invokeRoot" : "InvokeAI folder" ,
"load" : "Load" ,
"loraModels" : "LoRAs" ,
"manual" : "Manual" ,
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"merge" : "Merge" ,
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"mergedModelCustomSaveLocation" : "Custom Path" ,
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"mergedModelName" : "Merged Model Name" ,
"mergedModelSaveLocation" : "Save Location" ,
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"mergeModels" : "Merge Models" ,
"model" : "Model" ,
"modelAdded" : "Model Added" ,
"modelConversionFailed" : "Model Conversion Failed" ,
"modelConverted" : "Model Converted" ,
"modelDeleted" : "Model Deleted" ,
"modelDeleteFailed" : "Failed to delete model" ,
"modelEntryDeleted" : "Model Entry Deleted" ,
"modelExists" : "Model Exists" ,
"modelLocation" : "Model Location" ,
"modelLocationValidationMsg" : "Provide the path to a local folder where your Diffusers Model is stored" ,
"modelManager" : "Model Manager" ,
"modelMergeAlphaHelp" : "Alpha controls blend strength for the models. Lower alpha values lead to lower influence of the second model." ,
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"modelMergeHeaderHelp1" : "You can merge up to three different models to create a blend that suits your needs." ,
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"modelMergeHeaderHelp2" : "Only Diffusers are available for merging. If you want to merge a checkpoint model, please convert it to Diffusers first." ,
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"modelMergeInterpAddDifferenceHelp" : "In this mode, Model 3 is first subtracted from Model 2. The resulting version is blended with Model 1 with the alpha rate set above." ,
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"modelOne" : "Model 1" ,
"modelsFound" : "Models Found" ,
"modelsMerged" : "Models Merged" ,
"modelsMergeFailed" : "Model Merge Failed" ,
"modelsSynced" : "Models Synced" ,
"modelSyncFailed" : "Model Sync Failed" ,
"modelThree" : "Model 3" ,
"modelTwo" : "Model 2" ,
"modelType" : "Model Type" ,
"modelUpdated" : "Model Updated" ,
"modelUpdateFailed" : "Model Update Failed" ,
"name" : "Name" ,
"nameValidationMsg" : "Enter a name for your model" ,
"noCustomLocationProvided" : "No Custom Location Provided" ,
"noModels" : "No Models Found" ,
"noModelsFound" : "No Models Found" ,
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"none" : "none" ,
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"notLoaded" : "not loaded" ,
"oliveModels" : "Olives" ,
"onnxModels" : "Onnx" ,
"pathToCustomConfig" : "Path To Custom Config" ,
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"pickModelType" : "Pick Model Type" ,
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"predictionType" : "Prediction Type (for Stable Diffusion 2.x Models and occasional Stable Diffusion 1.x Models)" ,
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"quickAdd" : "Quick Add" ,
"repo_id" : "Repo ID" ,
"repoIDValidationMsg" : "Online repository of your model" ,
"safetensorModels" : "SafeTensors" ,
"sameFolder" : "Same folder" ,
"scanAgain" : "Scan Again" ,
"scanForModels" : "Scan For Models" ,
"search" : "Search" ,
"selectAll" : "Select All" ,
"selectAndAdd" : "Select and Add Models Listed Below" ,
"selected" : "Selected" ,
"selectFolder" : "Select Folder" ,
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"selectModel" : "Select Model" ,
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"settings" : "Settings" ,
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"showExisting" : "Show Existing" ,
"sigmoid" : "Sigmoid" ,
"simpleModelDesc" : "Provide a path to a local Diffusers model, local checkpoint / safetensors model a HuggingFace Repo ID, or a checkpoint/diffusers model URL." ,
"statusConverting" : "Converting" ,
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"syncModels" : "Sync Models" ,
"syncModelsDesc" : "If your models are out of sync with the backend, you can refresh them up using this option. This is generally handy in cases where you manually update your models.yaml file or add models to the InvokeAI root folder after the application has booted." ,
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"updateModel" : "Update Model" ,
"useCustomConfig" : "Use Custom Config" ,
"v1" : "v1" ,
"v2_768" : "v2 (768px)" ,
"v2_base" : "v2 (512px)" ,
"vae" : "VAE" ,
"vaeLocation" : "VAE Location" ,
"vaeLocationValidationMsg" : "Path to where your VAE is located." ,
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"vaePrecision" : "VAE Precision" ,
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"vaeRepoID" : "VAE Repo ID" ,
"vaeRepoIDValidationMsg" : "Online repository of your VAE" ,
"variant" : "Variant" ,
"weightedSum" : "Weighted Sum" ,
"width" : "Width" ,
"widthValidationMsg" : "Default width of your model."
} ,
"models" : {
"loading" : "loading" ,
"noLoRAsAvailable" : "No LoRAs available" ,
"noMatchingLoRAs" : "No matching LoRAs" ,
"noMatchingModels" : "No matching Models" ,
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"noModelsAvailable" : "No models available" ,
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"selectLoRA" : "Select a LoRA" ,
"selectModel" : "Select a Model"
} ,
"nodes" : {
"addNode" : "Add Node" ,
"addNodeToolTip" : "Add Node (Shift+A, Space)" ,
"animatedEdges" : "Animated Edges" ,
"animatedEdgesHelp" : "Animate selected edges and edges connected to selected nodes" ,
2023-09-22 02:09:24 +00:00
"boardField" : "Board" ,
"boardFieldDescription" : "A gallery board" ,
2023-09-13 11:15:36 +00:00
"boolean" : "Booleans" ,
"booleanCollection" : "Boolean Collection" ,
"booleanCollectionDescription" : "A collection of booleans." ,
"booleanDescription" : "Booleans are true or false." ,
"booleanPolymorphic" : "Boolean Polymorphic" ,
"booleanPolymorphicDescription" : "A collection of booleans." ,
2023-09-13 07:31:34 +00:00
"cannotConnectInputToInput" : "Cannot connect input to input" ,
"cannotConnectOutputToOutput" : "Cannot connect output to output" ,
"cannotConnectToSelf" : "Cannot connect to self" ,
2023-09-26 15:54:35 +00:00
"cannotDuplicateConnection" : "Cannot create duplicate connections" ,
2023-09-13 11:15:36 +00:00
"clipField" : "Clip" ,
"clipFieldDescription" : "Tokenizer and text_encoder submodels." ,
"collection" : "Collection" ,
"collectionDescription" : "TODO" ,
"collectionItem" : "Collection Item" ,
"collectionItemDescription" : "TODO" ,
2023-09-13 07:31:34 +00:00
"colorCodeEdges" : "Color-Code Edges" ,
"colorCodeEdgesHelp" : "Color-code edges according to their connected fields" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"colorCollection" : "A collection of colors." ,
"colorCollectionDescription" : "TODO" ,
2023-09-13 11:15:36 +00:00
"colorField" : "Color" ,
"colorFieldDescription" : "A RGBA color." ,
"colorPolymorphic" : "Color Polymorphic" ,
"colorPolymorphicDescription" : "A collection of colors." ,
"conditioningCollection" : "Conditioning Collection" ,
"conditioningCollectionDescription" : "Conditioning may be passed between nodes." ,
"conditioningField" : "Conditioning" ,
"conditioningFieldDescription" : "Conditioning may be passed between nodes." ,
"conditioningPolymorphic" : "Conditioning Polymorphic" ,
"conditioningPolymorphicDescription" : "Conditioning may be passed between nodes." ,
2023-09-13 07:31:34 +00:00
"connectionWouldCreateCycle" : "Connection would create a cycle" ,
2023-09-13 11:15:36 +00:00
"controlCollection" : "Control Collection" ,
"controlCollectionDescription" : "Control info passed between nodes." ,
"controlField" : "Control" ,
"controlFieldDescription" : "Control info passed between nodes." ,
2023-09-13 07:31:34 +00:00
"currentImage" : "Current Image" ,
"currentImageDescription" : "Displays the current image in the Node Editor" ,
2023-09-13 11:15:36 +00:00
"denoiseMaskField" : "Denoise Mask" ,
"denoiseMaskFieldDescription" : "Denoise Mask may be passed between nodes" ,
"doesNotExist" : "does not exist" ,
2023-09-13 07:31:34 +00:00
"downloadWorkflow" : "Download Workflow JSON" ,
2023-09-13 11:15:36 +00:00
"edge" : "Edge" ,
"enum" : "Enum" ,
"enumDescription" : "Enums are values that may be one of a number of options." ,
"executionStateCompleted" : "Completed" ,
"executionStateError" : "Error" ,
"executionStateInProgress" : "In Progress" ,
2023-09-13 07:31:34 +00:00
"fieldTypesMustMatch" : "Field types must match" ,
"fitViewportNodes" : "Fit View" ,
2023-09-13 11:15:36 +00:00
"float" : "Float" ,
"floatCollection" : "Float Collection" ,
"floatCollectionDescription" : "A collection of floats." ,
"floatDescription" : "Floats are numbers with a decimal point." ,
"floatPolymorphic" : "Float Polymorphic" ,
"floatPolymorphicDescription" : "A collection of floats." ,
2023-09-13 07:31:34 +00:00
"fullyContainNodes" : "Fully Contain Nodes to Select" ,
"fullyContainNodesHelp" : "Nodes must be fully inside the selection box to be selected" ,
"hideGraphNodes" : "Hide Graph Overlay" ,
"hideLegendNodes" : "Hide Field Type Legend" ,
"hideMinimapnodes" : "Hide MiniMap" ,
2023-09-13 11:15:36 +00:00
"imageCollection" : "Image Collection" ,
"imageCollectionDescription" : "A collection of images." ,
"imageField" : "Image" ,
"imageFieldDescription" : "Images may be passed between nodes." ,
"imagePolymorphic" : "Image Polymorphic" ,
"imagePolymorphicDescription" : "A collection of images." ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"inputField" : "Input Field" ,
"inputFields" : "Input Fields" ,
2023-09-13 07:31:34 +00:00
"inputMayOnlyHaveOneConnection" : "Input may only have one connection" ,
2023-09-13 11:15:36 +00:00
"inputNode" : "Input Node" ,
"integer" : "Integer" ,
"integerCollection" : "Integer Collection" ,
"integerCollectionDescription" : "A collection of integers." ,
"integerDescription" : "Integers are whole numbers, without a decimal point." ,
"integerPolymorphic" : "Integer Polymorphic" ,
"integerPolymorphicDescription" : "A collection of integers." ,
"invalidOutputSchema" : "Invalid output schema" ,
2023-10-06 21:15:13 +00:00
"ipAdapter" : "IP-Adapter" ,
"ipAdapterCollection" : "IP-Adapters Collection" ,
"ipAdapterCollectionDescription" : "A collection of IP-Adapters." ,
"ipAdapterDescription" : "An Image Prompt Adapter (IP-Adapter)." ,
"ipAdapterModel" : "IP-Adapter Model" ,
"ipAdapterModelDescription" : "IP-Adapter Model Field" ,
"ipAdapterPolymorphic" : "IP-Adapter Polymorphic" ,
"ipAdapterPolymorphicDescription" : "A collection of IP-Adapters." ,
2023-09-13 11:15:36 +00:00
"latentsCollection" : "Latents Collection" ,
"latentsCollectionDescription" : "Latents may be passed between nodes." ,
"latentsField" : "Latents" ,
"latentsFieldDescription" : "Latents may be passed between nodes." ,
"latentsPolymorphic" : "Latents Polymorphic" ,
"latentsPolymorphicDescription" : "Latents may be passed between nodes." ,
2023-09-13 07:31:34 +00:00
"loadingNodes" : "Loading Nodes..." ,
"loadWorkflow" : "Load Workflow" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"noWorkflow" : "No Workflow" ,
2023-09-13 11:15:36 +00:00
"loRAModelField" : "LoRA" ,
"loRAModelFieldDescription" : "TODO" ,
"mainModelField" : "Model" ,
"mainModelFieldDescription" : "TODO" ,
"maybeIncompatible" : "May be Incompatible With Installed" ,
"mismatchedVersion" : "Has Mismatched Version" ,
"missingCanvaInitImage" : "Missing canvas init image" ,
"missingCanvaInitMaskImages" : "Missing canvas init and mask images" ,
"missingTemplate" : "Missing Template" ,
2023-09-13 07:31:34 +00:00
"noConnectionData" : "No connection data" ,
"noConnectionInProgress" : "No connection in progress" ,
2023-09-13 11:15:36 +00:00
"node" : "Node" ,
2023-09-13 07:31:34 +00:00
"nodeOutputs" : "Node Outputs" ,
"nodeSearch" : "Search for nodes" ,
"nodeTemplate" : "Node Template" ,
2023-09-13 11:15:36 +00:00
"nodeType" : "Node Type" ,
2023-09-13 07:31:34 +00:00
"noFieldsLinearview" : "No fields added to Linear View" ,
"noFieldType" : "No field type" ,
2023-09-13 11:15:36 +00:00
"noImageFoundState" : "No initial image found in state" ,
2023-09-13 07:31:34 +00:00
"noMatchingNodes" : "No matching nodes" ,
"noNodeSelected" : "No node selected" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"nodeOpacity" : "Node Opacity" ,
2023-09-13 07:31:34 +00:00
"noOutputRecorded" : "No outputs recorded" ,
2023-09-13 11:15:36 +00:00
"noOutputSchemaName" : "No output schema name found in ref object" ,
2023-09-13 07:31:34 +00:00
"notes" : "Notes" ,
"notesDescription" : "Add notes about your workflow" ,
2023-09-13 11:15:36 +00:00
"oNNXModelField" : "ONNX Model" ,
"oNNXModelFieldDescription" : "ONNX model field." ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"outputField" : "Output Field" ,
"outputFields" : "Output Fields" ,
2023-09-13 11:15:36 +00:00
"outputNode" : "Output node" ,
"outputSchemaNotFound" : "Output schema not found" ,
2023-09-13 07:31:34 +00:00
"pickOne" : "Pick One" ,
2023-09-13 11:15:36 +00:00
"problemReadingMetadata" : "Problem reading metadata from image" ,
"problemReadingWorkflow" : "Problem reading workflow from image" ,
2023-09-13 07:31:34 +00:00
"problemSettingTitle" : "Problem Setting Title" ,
"reloadNodeTemplates" : "Reload Node Templates" ,
"removeLinearView" : "Remove from Linear View" ,
"resetWorkflow" : "Reset Workflow" ,
"resetWorkflowDesc" : "Are you sure you want to reset this workflow?" ,
"resetWorkflowDesc2" : "Resetting the workflow will clear all nodes, edges and workflow details." ,
2023-09-13 11:15:36 +00:00
"scheduler" : "Scheduler" ,
"schedulerDescription" : "TODO" ,
"sDXLMainModelField" : "SDXL Model" ,
"sDXLMainModelFieldDescription" : "SDXL model field." ,
"sDXLRefinerModelField" : "Refiner Model" ,
"sDXLRefinerModelFieldDescription" : "TODO" ,
2023-09-13 07:31:34 +00:00
"showGraphNodes" : "Show Graph Overlay" ,
"showLegendNodes" : "Show Field Type Legend" ,
"showMinimapnodes" : "Show MiniMap" ,
2023-09-13 11:15:36 +00:00
"skipped" : "Skipped" ,
"skippedReservedInput" : "Skipped reserved input field" ,
"skippedReservedOutput" : "Skipped reserved output field" ,
"skippingInputNoTemplate" : "Skipping input field with no template" ,
"skippingReservedFieldType" : "Skipping reserved field type" ,
"skippingUnknownInputType" : "Skipping unknown input field type" ,
"skippingUnknownOutputType" : "Skipping unknown output field type" ,
2023-09-13 07:31:34 +00:00
"snapToGrid" : "Snap to Grid" ,
"snapToGridHelp" : "Snap nodes to grid when moved" ,
2023-09-13 11:15:36 +00:00
"sourceNode" : "Source node" ,
"string" : "String" ,
"stringCollection" : "String Collection" ,
"stringCollectionDescription" : "A collection of strings." ,
"stringDescription" : "Strings are text." ,
"stringPolymorphic" : "String Polymorphic" ,
"stringPolymorphicDescription" : "A collection of strings." ,
2023-09-13 07:31:34 +00:00
"unableToLoadWorkflow" : "Unable to Validate Workflow" ,
2023-09-13 11:15:36 +00:00
"unableToParseEdge" : "Unable to parse edge" ,
"unableToParseNode" : "Unable to parse node" ,
2023-09-13 07:31:34 +00:00
"unableToValidateWorkflow" : "Unable to Validate Workflow" ,
2023-09-13 11:15:36 +00:00
"uNetField" : "UNet" ,
"uNetFieldDescription" : "UNet submodel." ,
"unhandledInputProperty" : "Unhandled input property" ,
"unhandledOutputProperty" : "Unhandled output property" ,
2023-09-13 07:31:34 +00:00
"unknownField" : "Unknown Field" ,
2023-09-13 11:15:36 +00:00
"unknownNode" : "Unknown Node" ,
"unknownTemplate" : "Unknown Template" ,
2023-09-13 07:31:34 +00:00
"unkownInvocation" : "Unknown Invocation type" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"updateNode" : "Update Node" ,
2023-09-13 11:15:36 +00:00
"updateApp" : "Update App" ,
"vaeField" : "Vae" ,
"vaeFieldDescription" : "Vae submodel." ,
"vaeModelField" : "VAE" ,
"vaeModelFieldDescription" : "TODO" ,
2023-09-13 07:31:34 +00:00
"validateConnections" : "Validate Connections and Graph" ,
"validateConnectionsHelp" : "Prevent invalid connections from being made, and invalid graphs from being invoked" ,
2023-09-13 11:15:36 +00:00
"version" : "Version" ,
"versionUnknown" : " Version Unknown" ,
2023-09-13 07:31:34 +00:00
"workflow" : "Workflow" ,
"workflowAuthor" : "Author" ,
"workflowContact" : "Contact" ,
"workflowDescription" : "Short Description" ,
"workflowName" : "Name" ,
"workflowNotes" : "Notes" ,
"workflowSettings" : "Workflow Editor Settings" ,
"workflowTags" : "Tags" ,
"workflowValidation" : "Workflow Validation Error" ,
"workflowVersion" : "Version" ,
"zoomInNodes" : "Zoom In" ,
2023-09-13 11:15:36 +00:00
"zoomOutNodes" : "Zoom Out"
2023-02-18 04:23:24 +00:00
} ,
"parameters" : {
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"aspectRatio" : "Aspect Ratio" ,
2023-10-12 11:46:47 +00:00
"aspectRatioFree" : "Free" ,
2023-02-18 04:23:24 +00:00
"boundingBoxHeader" : "Bounding Box" ,
2023-09-13 07:31:34 +00:00
"boundingBoxHeight" : "Bounding Box Height" ,
"boundingBoxWidth" : "Bounding Box Width" ,
2023-02-19 00:25:01 +00:00
"cancel" : {
2023-09-13 07:31:34 +00:00
"cancel" : "Cancel" ,
2023-02-19 00:25:01 +00:00
"immediate" : "Cancel immediately" ,
"isScheduled" : "Canceling" ,
2023-09-13 07:31:34 +00:00
"schedule" : "Cancel after current iteration" ,
2023-02-19 00:25:01 +00:00
"setType" : "Set cancel type"
2023-02-18 21:35:33 +00:00
} ,
2023-09-13 07:31:34 +00:00
"cfgScale" : "CFG Scale" ,
"clipSkip" : "CLIP Skip" ,
2023-09-20 14:19:31 +00:00
"clipSkipWithLayerCount" : "CLIP Skip {{layerCount}}" ,
2023-09-13 07:31:34 +00:00
"closeViewer" : "Close Viewer" ,
"codeformerFidelity" : "Fidelity" ,
"coherenceMode" : "Mode" ,
"coherencePassHeader" : "Coherence Pass" ,
"coherenceSteps" : "Steps" ,
"coherenceStrength" : "Strength" ,
"compositingSettingsHeader" : "Compositing Settings" ,
"controlNetControlMode" : "Control Mode" ,
2023-02-18 04:23:24 +00:00
"copyImage" : "Copy Image" ,
"copyImageToLink" : "Copy Image To Link" ,
2023-09-13 07:31:34 +00:00
"denoisingStrength" : "Denoising Strength" ,
2023-02-18 04:23:24 +00:00
"downloadImage" : "Download Image" ,
2023-09-13 07:31:34 +00:00
"enableNoiseSettings" : "Enable Noise Settings" ,
"faceRestoration" : "Face Restoration" ,
"general" : "General" ,
"height" : "Height" ,
"hidePreview" : "Hide Preview" ,
"hiresOptim" : "High Res Optimization" ,
"hiresStrength" : "High Res Strength" ,
"hSymmetryStep" : "H Symmetry Step" ,
"imageFit" : "Fit Initial Image To Output Size" ,
"images" : "Images" ,
"imageToImage" : "Image to Image" ,
"img2imgStrength" : "Image To Image Strength" ,
"infillMethod" : "Infill Method" ,
"infillScalingHeader" : "Infill and Scaling" ,
2023-02-18 04:23:24 +00:00
"info" : "Info" ,
"initialImage" : "Initial Image" ,
2023-09-13 07:31:34 +00:00
"invoke" : {
"addingImagesTo" : "Adding images to" ,
"invoke" : "Invoke" ,
"missingFieldTemplate" : "Missing field template" ,
"missingInputForField" : "{{nodeLabel}} -> {{fieldLabel}} missing input" ,
"missingNodeTemplate" : "Missing node template" ,
2023-10-12 03:16:54 +00:00
"noControlImageForControlAdapter" : "Control Adapter #{{number}} has no control image" ,
2023-09-13 07:31:34 +00:00
"noInitialImageSelected" : "No initial image selected" ,
2023-10-12 03:16:54 +00:00
"noModelForControlAdapter" : "Control Adapter #{{number}} has no model selected." ,
"incompatibleBaseModelForControlAdapter" : "Control Adapter #{{number}} model is invalid with main model." ,
2023-09-13 07:31:34 +00:00
"noModelSelected" : "No model selected" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"noPrompts" : "No prompts generated" ,
2023-09-13 07:31:34 +00:00
"noNodesInGraph" : "No nodes in graph" ,
"readyToInvoke" : "Ready to Invoke" ,
"systemBusy" : "System busy" ,
"systemDisconnected" : "System disconnected" ,
"unableToInvoke" : "Unable to Invoke"
} ,
"maskAdjustmentsHeader" : "Mask Adjustments" ,
"maskBlur" : "Blur" ,
"maskBlurMethod" : "Blur Method" ,
"negativePromptPlaceholder" : "Negative Prompt" ,
"noiseSettings" : "Noise" ,
"noiseThreshold" : "Noise Threshold" ,
"openInViewer" : "Open In Viewer" ,
"otherOptions" : "Other Options" ,
"patchmatchDownScaleSize" : "Downscale" ,
"perlinNoise" : "Perlin Noise" ,
"positivePromptPlaceholder" : "Positive Prompt" ,
"randomizeSeed" : "Randomize Seed" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"manualSeed" : "Manual Seed" ,
"randomSeed" : "Random Seed" ,
2023-09-13 07:31:34 +00:00
"restoreFaces" : "Restore Faces" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"iterations" : "Iterations" ,
"iterationsWithCount_one" : "{{count}} Iteration" ,
"iterationsWithCount_other" : "{{count}} Iterations" ,
2023-09-13 07:31:34 +00:00
"scale" : "Scale" ,
"scaleBeforeProcessing" : "Scale Before Processing" ,
"scaledHeight" : "Scaled H" ,
"scaledWidth" : "Scaled W" ,
"scheduler" : "Scheduler" ,
"seamCorrectionHeader" : "Seam Correction" ,
"seamHighThreshold" : "High" ,
"seamlessTiling" : "Seamless Tiling" ,
"seamlessXAxis" : "X Axis" ,
"seamlessYAxis" : "Y Axis" ,
2023-09-20 14:19:31 +00:00
"seamlessX" : "Seamless X" ,
"seamlessY" : "Seamless Y" ,
"seamlessX&Y" : "Seamless X & Y" ,
2023-09-13 07:31:34 +00:00
"seamLowThreshold" : "Low" ,
"seed" : "Seed" ,
"seedWeights" : "Seed Weights" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"imageActions" : "Image Actions" ,
2023-09-13 07:31:34 +00:00
"sendTo" : "Send to" ,
"sendToImg2Img" : "Send to Image to Image" ,
"sendToUnifiedCanvas" : "Send To Unified Canvas" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"showOptionsPanel" : "Show Side Panel (O or T)" ,
2023-06-14 08:01:17 +00:00
"showPreview" : "Show Preview" ,
2023-09-13 07:31:34 +00:00
"shuffle" : "Shuffle Seed" ,
"steps" : "Steps" ,
"strength" : "Strength" ,
"symmetry" : "Symmetry" ,
"tileSize" : "Tile Size" ,
"toggleLoopback" : "Toggle Loopback" ,
"type" : "Type" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"upscale" : "Upscale (Shift + U)" ,
2023-09-13 07:31:34 +00:00
"upscaleImage" : "Upscale Image" ,
"upscaling" : "Upscaling" ,
"useAll" : "Use All" ,
"useCpuNoise" : "Use CPU Noise" ,
2023-09-20 14:19:31 +00:00
"cpuNoise" : "CPU Noise" ,
"gpuNoise" : "GPU Noise" ,
2023-09-13 07:31:34 +00:00
"useInitImg" : "Use Initial Image" ,
"usePrompt" : "Use Prompt" ,
"useSeed" : "Use Seed" ,
"variationAmount" : "Variation Amount" ,
"variations" : "Variations" ,
"vSymmetryStep" : "V Symmetry Step" ,
2023-10-02 23:25:05 +00:00
"width" : "Width" ,
"isAllowedToUpscale" : {
"useX2Model" : "Image is too large to upscale with x4 model, use x2 model" ,
"tooLarge" : "Image is too large to upscale, select smaller image"
}
2023-09-13 07:31:34 +00:00
} ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"dynamicPrompts" : {
2023-09-13 07:31:34 +00:00
"combinatorial" : "Combinatorial Generation" ,
"dynamicPrompts" : "Dynamic Prompts" ,
"enableDynamicPrompts" : "Enable Dynamic Prompts" ,
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
"maxPrompts" : "Max Prompts" ,
"promptsWithCount_one" : "{{count}} Prompt" ,
"promptsWithCount_other" : "{{count}} Prompts" ,
"seedBehaviour" : {
"label" : "Seed Behaviour" ,
"perIterationLabel" : "Seed per Iteration" ,
"perIterationDesc" : "Use a different seed for each iteration" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"perPromptLabel" : "Seed per Image" ,
"perPromptDesc" : "Use a different seed for each image"
feat: queued generation (#4502)
* fix(config): fix typing issues in `config/`
`config/invokeai_config.py`:
- use `Optional` for things that are optional
- fix typing of `ram_cache_size()` and `vram_cache_size()`
- remove unused and incorrectly typed method `autoconvert_path`
- fix types and logic for `parse_args()`, in which `InvokeAIAppConfig.initconf` *must* be a `DictConfig`, but function would allow it to be set as a `ListConfig`, which presumably would cause issues elsewhere
`config/base.py`:
- use `cls` for first arg of class methods
- use `Optional` for things that are optional
- fix minor type issue related to setting of `env_prefix`
- remove unused `add_subparser()` method, which calls `add_parser()` on an `ArgumentParser` (method only available on the `_SubParsersAction` object, which is returned from ArgumentParser.add_subparsers()`)
* feat: queued generation and batches
Due to a very messy branch with broad addition of `isort` on `main` alongside it, some git surgery was needed to get an agreeable git history. This commit represents all of the work on queued generation. See PR for notes.
* chore: flake8, isort, black
* fix(nodes): fix incorrect service stop() method
* fix(nodes): improve names of a few variables
* fix(tests): fix up tests after changes to batches/queue
* feat(tests): add unit tests for session queue helper functions
* feat(ui): dynamic prompts is always enabled
* feat(queue): add queue_status_changed event
* feat(ui): wip queue graphs
* feat(nodes): move cleanup til after invoker startup
* feat(nodes): add cancel_by_batch_ids
* feat(ui): wip batch graphs & UI
* fix(nodes): remove `Batch.batch_id` from required
* fix(ui): cleanup and use fixedCacheKey for all mutations
* fix(ui): remove orphaned nodes from canvas graphs
* fix(nodes): fix cancel_by_batch_ids result count
* fix(ui): only show cancel batch tooltip when batches were canceled
* chore: isort
* fix(api): return `[""]` when dynamic prompts generates no prompts
Just a simple fallback so we always have a prompt.
* feat(ui): dynamicPrompts.combinatorial is always on
There seems to be little purpose in using the combinatorial generation for dynamic prompts. I've disabled it by hiding it from the UI and defaulting combinatorial to true. If we want to enable it again in the future it's straightforward to do so.
* feat: add queue_id & support logic
* feat(ui): fix upscale button
It prepends the upscale operation to queue
* feat(nodes): return queue item when enqueuing a single graph
This facilitates one-off graph async workflows in the client.
* feat(ui): move controlnet autoprocess to queue
* fix(ui): fix non-serializable DOMRect in redux state
* feat(ui): QueueTable performance tweaks
* feat(ui): update queue list
Queue items expand to show the full queue item. Just as JSON for now.
* wip threaded session_processor
* feat(nodes,ui): fully migrate queue to session_processor
* feat(nodes,ui): add processor events
* feat(ui): ui tweaks
* feat(nodes,ui): consolidate events, reduce network requests
* feat(ui): cleanup & abstract queue hooks
* feat(nodes): optimize batch permutation
Use a generator to do only as much work as is needed.
Previously, though we only ended up creating exactly as many queue items as was needed, there was still some intermediary work that calculated *all* permutations. When that number was very high, the system had a very hard time and used a lot of memory.
The logic has been refactored to use a generator. Additionally, the batch validators are optimized to return early and use less memory.
* feat(ui): add seed behaviour parameter
This dynamic prompts parameter allows the seed to be randomized per prompt or per iteration:
- Per iteration: Use the same seed for all prompts in a single dynamic prompt expansion
- Per prompt: Use a different seed for every single prompt
"Per iteration" is appropriate for exploring a the latents space with a stable starting noise, while "Per prompt" provides more variation.
* fix(ui): remove extraneous random seed nodes from linear graphs
* fix(ui): fix controlnet autoprocess not working when queue is running
* feat(queue): add timestamps to queue status updates
Also show execution time in queue list
* feat(queue): change all execution-related events to use the `queue_id` as the room, also include `queue_item_id` in InvocationQueueItem
This allows for much simpler handling of queue items.
* feat(api): deprecate sessions router
* chore(backend): tidy logging in `dependencies.py`
* fix(backend): respect `use_memory_db`
* feat(backend): add `config.log_sql` (enables sql trace logging)
* feat: add invocation cache
Supersedes #4574
The invocation cache provides simple node memoization functionality. Nodes that use the cache are memoized and not re-executed if their inputs haven't changed. Instead, the stored output is returned.
## Results
This feature provides anywhere some significant to massive performance improvement.
The improvement is most marked on large batches of generations where you only change a couple things (e.g. different seed or prompt for each iteration) and low-VRAM systems, where skipping an extraneous model load is a big deal.
## Overview
A new `invocation_cache` service is added to handle the caching. There's not much to it.
All nodes now inherit a boolean `use_cache` field from `BaseInvocation`. This is a node field and not a class attribute, because specific instances of nodes may want to opt in or out of caching.
The recently-added `invoke_internal()` method on `BaseInvocation` is used as an entrypoint for the cache logic.
To create a cache key, the invocation is first serialized using pydantic's provided `json()` method, skipping the unique `id` field. Then python's very fast builtin `hash()` is used to create an integer key. All implementations of `InvocationCacheBase` must provide a class method `create_key()` which accepts an invocation and outputs a string or integer key.
## In-Memory Implementation
An in-memory implementation is provided. In this implementation, the node outputs are stored in memory as python classes. The in-memory cache does not persist application restarts.
Max node cache size is added as `node_cache_size` under the `Generation` config category.
It defaults to 512 - this number is up for discussion, but given that these are relatively lightweight pydantic models, I think it's safe to up this even higher.
Note that the cache isn't storing the big stuff - tensors and images are store on disk, and outputs include only references to them.
## Node Definition
The default for all nodes is to use the cache. The `@invocation` decorator now accepts an optional `use_cache: bool` argument to override the default of `True`.
Non-deterministic nodes, however, should set this to `False`. Currently, all random-stuff nodes, including `dynamic_prompt`, are set to `False`.
The field name `use_cache` is now effectively a reserved field name and possibly a breaking change if any community nodes use this as a field name. In hindsight, all our reserved field names should have been prefixed with underscores or something.
## One Gotcha
Leaf nodes probably want to opt out of the cache, because if they are not cached, their outputs are not saved again.
If you run the same graph multiple times, you only end up with a single image output, because the image storage side-effects are in the `invoke()` method, which is bypassed if we have a cache hit.
## Linear UI
The linear graphs _almost_ just work, but due to the gotcha, we need to be careful about the final image-outputting node. To resolve this, a `SaveImageInvocation` node is added and used in the linear graphs.
This node is similar to `ImagePrimitive`, except it saves a copy of its input image, and has `use_cache` set to `False` by default.
This is now the leaf node in all linear graphs, and is the only node in those graphs with `use_cache == False` _and_ the only node with `is_intermedate == False`.
## Workflow Editor
All nodes now have a footer with a new `Use Cache [ ]` checkbox. It defaults to the value set by the invocation in its python definition, but can be changed by the user.
The workflow/node validation logic has been updated to migrate old workflows to use the new default values for `use_cache`. Users may still want to review the settings that have been chosen. In the event of catastrophic failure when running this migration, the default value of `True` is applied, as this is correct for most nodes.
Users should consider saving their workflows after loading them in and having them updated.
## Future Enhancements - Callback
A future enhancement would be to provide a callback to the `use_cache` flag that would be run as the node is executed to determine, based on its own internal state, if the cache should be used or not.
This would be useful for `DynamicPromptInvocation`, where the deterministic behaviour is determined by the `combinatorial: bool` field.
## Future Enhancements - Persisted Cache
Similar to how the latents storage is backed by disk, the invocation cache could be persisted to the database or disk. We'd need to be very careful about deserializing outputs, but it's perhaps worth exploring in the future.
* fix(ui): fix queue list item width
* feat(nodes): do not send the whole node on every generator progress
* feat(ui): strip out old logic related to sessions
Things like `isProcessing` are no longer relevant with queue. Removed them all & updated everything be appropriate for queue. May be a few little quirks I've missed...
* feat(ui): fix up param collapse labels
* feat(ui): click queue count to go to queue tab
* tidy(queue): update comment, query format
* feat(ui): fix progress bar when canceling
* fix(ui): fix circular dependency
* feat(nodes): bail on node caching logic if `node_cache_size == 0`
* feat(nodes): handle KeyError on node cache pop
* feat(nodes): bypass cache codepath if caches is disabled
more better no do thing
* fix(ui): reset api cache on connect/disconnect
* feat(ui): prevent enqueue when no prompts generated
* feat(ui): add queue controls to workflow editor
* feat(ui): update floating buttons & other incidental UI tweaks
* fix(ui): fix missing/incorrect translation keys
* fix(tests): add config service to mock invocation services
invoking needs access to `node_cache_size` to occur
* optionally remove pause/resume buttons from queue UI
* option to disable prepending
* chore(ui): remove unused file
* feat(queue): remove `order_id` entirely, `item_id` is now an autoinc pk
---------
Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
2023-09-20 05:09:24 +00:00
}
2023-09-13 07:31:34 +00:00
} ,
"sdxl" : {
"cfgScale" : "CFG Scale" ,
"concatPromptStyle" : "Concatenate Prompt & Style" ,
"denoisingStrength" : "Denoising Strength" ,
"loading" : "Loading..." ,
"negAestheticScore" : "Negative Aesthetic Score" ,
"negStylePrompt" : "Negative Style Prompt" ,
"noModelsAvailable" : "No models available" ,
"posAestheticScore" : "Positive Aesthetic Score" ,
"posStylePrompt" : "Positive Style Prompt" ,
"refiner" : "Refiner" ,
"refinermodel" : "Refiner Model" ,
"refinerStart" : "Refiner Start" ,
"scheduler" : "Scheduler" ,
"selectAModel" : "Select a model" ,
"steps" : "Steps" ,
"useRefiner" : "Use Refiner"
2023-02-18 04:23:24 +00:00
} ,
"settings" : {
2023-07-20 02:17:51 +00:00
"alternateCanvasLayout" : "Alternate Canvas Layout" ,
2023-05-10 04:38:05 +00:00
"antialiasProgressImages" : "Antialias Progress Images" ,
2023-08-29 17:49:57 +00:00
"autoChangeDimensions" : "Update W/H To Model Defaults On Change" ,
2023-09-13 07:31:34 +00:00
"beta" : "Beta" ,
"confirmOnDelete" : "Confirm On Delete" ,
2023-04-29 07:55:39 +00:00
"consoleLogLevel" : "Log Level" ,
2023-04-29 08:25:02 +00:00
"developer" : "Developer" ,
2023-09-13 07:31:34 +00:00
"displayHelpIcons" : "Display Help Icons" ,
"displayInProgress" : "Display Progress Images" ,
"enableImageDebugging" : "Enable Image Debugging" ,
"enableNodesEditor" : "Enable Nodes Editor" ,
"experimental" : "Experimental" ,
2023-06-18 10:01:05 +00:00
"favoriteSchedulers" : "Favorite Schedulers" ,
2023-07-06 17:57:39 +00:00
"favoriteSchedulersPlaceholder" : "No schedulers favorited" ,
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"general" : "General" ,
"generation" : "Generation" ,
"models" : "Models" ,
"resetComplete" : "Web UI has been reset." ,
"resetWebUI" : "Reset Web UI" ,
"resetWebUIDesc1" : "Resetting the web UI only resets the browser's local cache of your images and remembered settings. It does not delete any images from disk." ,
"resetWebUIDesc2" : "If images aren't showing up in the gallery or something else isn't working, please try resetting before submitting an issue on GitHub." ,
"saveSteps" : "Save images every n steps" ,
"shouldLogToConsole" : "Console Logging" ,
2023-07-20 02:17:51 +00:00
"showAdvancedOptions" : "Show Advanced Options" ,
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"showProgressInViewer" : "Show Progress Images in Viewer" ,
"ui" : "User Interface" ,
2023-10-12 07:35:33 +00:00
"useSlidersForAll" : "Use Sliders For All Options" ,
2023-10-15 06:27:25 +00:00
"clearIntermediatesDisabled" : "Queue must be empty to clear intermediates" ,
2023-10-12 07:35:33 +00:00
"clearIntermediatesDesc1" : "Clearing intermediates will reset your Canvas and ControlNet state." ,
"clearIntermediatesDesc2" : "Intermediate images are byproducts of generation, different from the result images in the gallery. Clearing intermediates will free disk space." ,
"clearIntermediatesDesc3" : "Your gallery images will not be deleted." ,
"clearIntermediates" : "Clear Intermediates" ,
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"clearIntermediatesWithCount_one" : "Clear {{count}} Intermediate" ,
"clearIntermediatesWithCount_other" : "Clear {{count}} Intermediates" ,
"clearIntermediatesWithCount_zero" : "No Intermediates to Clear" ,
"intermediatesCleared_one" : "Cleared {{count}} Intermediate" ,
"intermediatesCleared_other" : "Cleared {{count}} Intermediates" ,
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"intermediatesClearedFailed" : "Problem Clearing Intermediates"
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} ,
"toast" : {
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"addedToBoard" : "Added to board" ,
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"baseModelChangedCleared_one" : "Base model changed, cleared or disabled {{count}} incompatible submodel" ,
"baseModelChangedCleared_other" : "Base model changed, cleared or disabled {{count}} incompatible submodels" ,
Partial migration of UI to nodes API (#3195)
* 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>
2023-04-22 03:10:20 +00:00
"canceled" : "Processing Canceled" ,
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"canvasCopiedClipboard" : "Canvas Copied to Clipboard" ,
"canvasDownloaded" : "Canvas Downloaded" ,
2023-09-13 07:31:34 +00:00
"canvasMerged" : "Canvas Merged" ,
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"canvasSavedGallery" : "Canvas Saved to Gallery" ,
"canvasSentControlnetAssets" : "Canvas Sent to ControlNet & Assets" ,
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"connected" : "Connected to Server" ,
"disconnected" : "Disconnected from Server" ,
2023-02-18 04:23:24 +00:00
"downloadImageStarted" : "Image Download Started" ,
2023-09-13 07:31:34 +00:00
"faceRestoreFailed" : "Face Restoration Failed" ,
2023-02-18 04:23:24 +00:00
"imageCopied" : "Image Copied" ,
"imageLinkCopied" : "Image Link Copied" ,
"imageNotLoaded" : "No Image Loaded" ,
2023-05-03 09:27:29 +00:00
"imageNotLoadedDesc" : "Could not find image" ,
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"imageSaved" : "Image Saved" ,
2023-02-18 04:23:24 +00:00
"imageSavedToGallery" : "Image Saved to Gallery" ,
2023-09-15 03:43:32 +00:00
"imageSavingFailed" : "Image Saving Failed" ,
"imageUploaded" : "Image Uploaded" ,
"imageUploadFailed" : "Image Upload Failed" ,
2023-02-18 04:23:24 +00:00
"initialImageNotSet" : "Initial Image Not Set" ,
2023-07-10 19:18:13 +00:00
"initialImageNotSetDesc" : "Could not load initial image" ,
2023-09-13 07:31:34 +00:00
"initialImageSet" : "Initial Image Set" ,
2023-09-15 03:43:32 +00:00
"loadedWithWarnings" : "Workflow Loaded with Warnings" ,
"maskSavedAssets" : "Mask Saved to Assets" ,
"maskSentControlnetAssets" : "Mask Sent to ControlNet & Assets" ,
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"metadataLoadFailed" : "Failed to load metadata" ,
"modelAdded" : "Model Added: {{modelName}}" ,
"modelAddedSimple" : "Model Added" ,
"modelAddFailed" : "Model Add Failed" ,
"nodesBrokenConnections" : "Cannot load. Some connections are broken." ,
"nodesCleared" : "Nodes Cleared" ,
"nodesCorruptedGraph" : "Cannot load. Graph seems to be corrupted." ,
2023-07-10 19:18:13 +00:00
"nodesLoaded" : "Nodes Loaded" ,
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"nodesLoadedFailed" : "Failed To Load Nodes" ,
2023-07-23 03:24:04 +00:00
"nodesNotValidGraph" : "Not a valid InvokeAI Node Graph" ,
"nodesNotValidJSON" : "Not a valid JSON" ,
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"nodesSaved" : "Nodes Saved" ,
2023-07-23 06:12:25 +00:00
"nodesUnrecognizedTypes" : "Cannot load. Graph has unrecognized types" ,
2023-09-13 07:31:34 +00:00
"parameterNotSet" : "Parameter not set" ,
"parameterSet" : "Parameter set" ,
"parametersFailed" : "Problem loading parameters" ,
"parametersFailedDesc" : "Unable to load init image." ,
"parametersNotSet" : "Parameters Not Set" ,
"parametersNotSetDesc" : "No metadata found for this image." ,
"parametersSet" : "Parameters Set" ,
2023-09-15 03:43:32 +00:00
"problemCopyingCanvas" : "Problem Copying Canvas" ,
"problemCopyingCanvasDesc" : "Unable to export base layer" ,
2023-09-13 07:31:34 +00:00
"problemCopyingImage" : "Unable to Copy Image" ,
"problemCopyingImageLink" : "Unable to Copy Image Link" ,
2023-09-15 03:43:32 +00:00
"problemDownloadingCanvas" : "Problem Downloading Canvas" ,
"problemDownloadingCanvasDesc" : "Unable to export base layer" ,
"problemImportingMask" : "Problem Importing Mask" ,
"problemImportingMaskDesc" : "Unable to export mask" ,
"problemMergingCanvas" : "Problem Merging Canvas" ,
"problemMergingCanvasDesc" : "Unable to export base layer" ,
"problemSavingCanvas" : "Problem Saving Canvas" ,
"problemSavingCanvasDesc" : "Unable to export base layer" ,
"problemSavingMask" : "Problem Saving Mask" ,
"problemSavingMaskDesc" : "Unable to export mask" ,
2023-09-13 07:31:34 +00:00
"promptNotSet" : "Prompt Not Set" ,
"promptNotSetDesc" : "Could not find prompt for this image." ,
"promptSet" : "Prompt Set" ,
"seedNotSet" : "Seed Not Set" ,
"seedNotSetDesc" : "Could not find seed for this image." ,
"seedSet" : "Seed Set" ,
"sentToImageToImage" : "Sent To Image To Image" ,
"sentToUnifiedCanvas" : "Sent to Unified Canvas" ,
"serverError" : "Server Error" ,
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"setCanvasInitialImage" : "Set as canvas initial image" ,
"setControlImage" : "Set as control image" ,
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"setIPAdapterImage" : "Set as IP Adapter Image" ,
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"setInitialImage" : "Set as initial image" ,
"setNodeField" : "Set as node field" ,
2023-09-13 07:31:34 +00:00
"tempFoldersEmptied" : "Temp Folder Emptied" ,
"uploadFailed" : "Upload failed" ,
"uploadFailedInvalidUploadDesc" : "Must be single PNG or JPEG image" ,
"uploadFailedUnableToLoadDesc" : "Unable to load file" ,
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"upscalingFailed" : "Upscaling Failed" ,
"workflowLoaded" : "Workflow Loaded"
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} ,
"tooltip" : {
"feature" : {
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"boundingBox" : "The bounding box is the same as the Width and Height settings for Text to Image or Image to Image. Only the area in the box will be processed." ,
"faceCorrection" : "Face correction with GFPGAN or Codeformer: the algorithm detects faces in the image and corrects any defects. High value will change the image more, resulting in more attractive faces. Codeformer with a higher fidelity preserves the original image at the expense of stronger face correction." ,
2023-02-18 04:23:24 +00:00
"gallery" : "Gallery displays generations from the outputs folder as they're created. Settings are stored within files and accesed by context menu." ,
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"imageToImage" : "Image to Image loads any image as initial, which is then used to generate a new one along with the prompt. The higher the value, the more the result image will change. Values from 0.0 to 1.0 are possible, the recommended range is .25-.75" ,
"infillAndScaling" : "Manage infill methods (used on masked or erased areas of the canvas) and scaling (useful for small bounding box sizes)." ,
2023-02-18 21:35:33 +00:00
"other" : "These options will enable alternative processing modes for Invoke. 'Seamless tiling' will create repeating patterns in the output. 'High resolution' is generation in two steps with img2img: use this setting when you want a larger and more coherent image without artifacts. It will take longer than usual txt2img." ,
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"prompt" : "This is the prompt field. Prompt includes generation objects and stylistic terms. You can add weight (token importance) in the prompt as well, but CLI commands and parameters will not work." ,
"seamCorrection" : "Controls the handling of visible seams that occur between generated images on the canvas." ,
2023-02-18 04:23:24 +00:00
"seed" : "Seed value affects the initial noise from which the image is formed. You can use the already existing seeds from previous images. 'Noise Threshold' is used to mitigate artifacts at high CFG values (try the 0-10 range), and Perlin to add Perlin noise during generation: both serve to add variation to your outputs." ,
"upscale" : "Use ESRGAN to enlarge the image immediately after generation." ,
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"variations" : "Try a variation with a value between 0.1 and 1.0 to change the result for a given seed. Interesting variations of the seed are between 0.1 and 0.3."
2023-02-18 04:23:24 +00:00
}
} ,
2023-09-15 14:37:05 +00:00
"popovers" : {
"clipSkip" : {
"heading" : "CLIP Skip" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"Choose how many layers of the CLIP model to skip." ,
"Some models work better with certain CLIP Skip settings." ,
"A higher value typically results in a less detailed image."
]
} ,
"paramNegativeConditioning" : {
"heading" : "Negative Prompt" ,
"paragraphs" : [
"The generation process avoids the concepts in the negative prompt. Use this to exclude qualities or objects from the output." ,
"Supports Compel syntax and embeddings."
]
} ,
"paramPositiveConditioning" : {
"heading" : "Positive Prompt" ,
"paragraphs" : [
"Guides the generation process. You may use any words or phrases." ,
"Compel and Dynamic Prompts syntaxes and embeddings."
]
} ,
"paramScheduler" : {
"heading" : "Scheduler" ,
"paragraphs" : [
"Scheduler defines how to iteratively add noise to an image or how to update a sample based on a model's output."
]
2023-09-15 14:37:05 +00:00
} ,
"compositingBlur" : {
"heading" : "Blur" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [ "The blur radius of the mask." ]
2023-09-15 14:37:05 +00:00
} ,
"compositingBlurMethod" : {
"heading" : "Blur Method" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [ "The method of blur applied to the masked area." ]
2023-09-15 14:37:05 +00:00
} ,
"compositingCoherencePass" : {
"heading" : "Coherence Pass" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"A second round of denoising helps to composite the Inpainted/Outpainted image."
]
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} ,
2023-09-18 15:03:02 +00:00
"compositingCoherenceMode" : {
2023-09-15 14:37:05 +00:00
"heading" : "Mode" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [ "The mode of the Coherence Pass." ]
2023-09-15 14:37:05 +00:00
} ,
2023-09-18 15:03:02 +00:00
"compositingCoherenceSteps" : {
2023-09-15 14:37:05 +00:00
"heading" : "Steps" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"Number of denoising steps used in the Coherence Pass." ,
"Same as the main Steps parameter."
]
2023-09-15 14:37:05 +00:00
} ,
"compositingStrength" : {
"heading" : "Strength" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"Denoising strength for the Coherence Pass." ,
"Same as the Image to Image Denoising Strength parameter."
]
2023-09-15 14:37:05 +00:00
} ,
"compositingMaskAdjustments" : {
"heading" : "Mask Adjustments" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [ "Adjust the mask." ]
2023-09-15 14:37:05 +00:00
} ,
"controlNetBeginEnd" : {
"heading" : "Begin / End Step Percentage" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"Which steps of the denoising process will have the ControlNet applied." ,
"ControlNets applied at the beginning of the process guide composition, and ControlNets applied at the end guide details."
]
2023-09-15 14:37:05 +00:00
} ,
"controlNetControlMode" : {
"heading" : "Control Mode" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"Lends more weight to either the prompt or ControlNet."
]
2023-09-15 14:37:05 +00:00
} ,
"controlNetResizeMode" : {
"heading" : "Resize Mode" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"How the ControlNet image will be fit to the image output size."
]
2023-09-15 14:37:05 +00:00
} ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"controlNet" : {
"heading" : "ControlNet" ,
"paragraphs" : [
"ControlNets provide guidance to the generation process, helping create images with controlled composition, structure, or style, depending on the model selected."
]
2023-09-15 14:37:05 +00:00
} ,
"controlNetWeight" : {
"heading" : "Weight" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"How strongly the ControlNet will impact the generated image."
]
} ,
"dynamicPrompts" : {
"heading" : "Dynamic Prompts" ,
"paragraphs" : [
"Dynamic Prompts parses a single prompt into many." ,
"The basic syntax is \"a {red|green|blue} ball\". This will produce three prompts: \"a red ball\", \"a green ball\" and \"a blue ball\"." ,
"You can use the syntax as many times as you like in a single prompt, but be sure to keep the number of prompts generated in check with the Max Prompts setting."
]
} ,
"dynamicPromptsMaxPrompts" : {
"heading" : "Max Prompts" ,
"paragraphs" : [
"Limits the number of prompts that can be generated by Dynamic Prompts."
]
} ,
"dynamicPromptsSeedBehaviour" : {
"heading" : "Seed Behaviour" ,
"paragraphs" : [
"Controls how the seed is used when generating prompts." ,
"Per Iteration will use a unique seed for each iteration. Use this to explore prompt variations on a single seed." ,
"For example, if you have 5 prompts, each image will use the same seed." ,
"Per Image will use a unique seed for each image. This provides more variation."
]
2023-09-15 14:37:05 +00:00
} ,
"infillMethod" : {
"heading" : "Infill Method" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [ "Method to infill the selected area." ]
2023-09-15 14:37:05 +00:00
} ,
"lora" : {
2023-09-21 10:01:00 +00:00
"heading" : "LoRA Weight" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"Higher LoRA weight will lead to larger impacts on the final image."
]
2023-09-15 14:37:05 +00:00
} ,
"noiseUseCPU" : {
"heading" : "Use CPU Noise" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"Controls whether noise is generated on the CPU or GPU." ,
"With CPU Noise enabled, a particular seed will produce the same image on any machine." ,
"There is no performance impact to enabling CPU Noise."
]
2023-09-15 14:37:05 +00:00
} ,
2023-09-15 18:48:36 +00:00
"paramCFGScale" : {
2023-09-15 14:37:05 +00:00
"heading" : "CFG Scale" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"Controls how much your prompt influences the generation process."
]
2023-09-15 14:37:05 +00:00
} ,
"paramDenoisingStrength" : {
"heading" : "Denoising Strength" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"How much noise is added to the input image." ,
"0 will result in an identical image, while 1 will result in a completely new image."
]
2023-09-15 14:37:05 +00:00
} ,
2023-09-21 10:01:00 +00:00
"paramIterations" : {
"heading" : "Iterations" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"The number of images to generate." ,
"If Dynamic Prompts is enabled, each of the prompts will be generated this many times."
]
2023-09-15 14:37:05 +00:00
} ,
"paramModel" : {
"heading" : "Model" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"Model used for the denoising steps." ,
"Different models are typically trained to specialize in producing particular aesthetic results and content."
]
2023-09-15 14:37:05 +00:00
} ,
2023-09-15 18:48:36 +00:00
"paramRatio" : {
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"heading" : "Aspect Ratio" ,
"paragraphs" : [
"The aspect ratio of the dimensions of the image generated." ,
"An image size (in number of pixels) equivalent to 512x512 is recommended for SD1.5 models and a size equivalent to 1024x1024 is recommended for SDXL models."
]
2023-09-15 14:37:05 +00:00
} ,
"paramSeed" : {
"heading" : "Seed" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"Controls the starting noise used for generation." ,
"Disable “Random Seed” to produce identical results with the same generation settings."
]
2023-09-15 14:37:05 +00:00
} ,
"paramSteps" : {
"heading" : "Steps" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"Number of steps that will be performed in each generation." ,
"Higher step counts will typically create better images but will require more generation time."
]
2023-09-15 14:37:05 +00:00
} ,
"paramVAE" : {
"heading" : "VAE" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"Model used for translating AI output into the final image."
]
2023-09-15 14:37:05 +00:00
} ,
"paramVAEPrecision" : {
"heading" : "VAE Precision" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"The precision used during VAE encoding and decoding. FP16/half precision is more efficient, at the expense of minor image variations."
]
2023-09-15 14:37:05 +00:00
} ,
"scaleBeforeProcessing" : {
"heading" : "Scale Before Processing" ,
feat(ui): refactor informational popover
- Change translations to use arrays of paragraphs instead of a single paragraph.
- Change component to accept a `feature` prop to identify the feature which the popover describes.
- Add optional `wrapperProps`: passed to the wrapper element, allowing more flexibility when using the popover
- Add optional `popoverProps`: passed to the `<Popover />` component, allowing for overriding individual instances of the popover's props
- Move definitions of features and popover settings to `invokeai/frontend/web/src/common/components/IAIInformationalPopover/constants.ts`
- Add some type safety to the `feature` prop
- Edit `POPOVER_DATA` to provide `image`, `href`, `buttonLabel`, and any popover props. The popover props are applied to all instances of the popover for the given feature. Note that the component prop `popoverProps` will override settings here.
- Remove the popover's arrow. Because the popover is wrapping groups of components, sometimes the error ends up pointing to nothing, which looks kinda janky. I've just removed the arrow entirely, but feel free to add it back if you think it looks better.
- Use a `link` variant button with external link icon to better communicate that clicking the button will open a new tab.
- Default the link button label to "Learn More" (if a label is provided, that will be used instead)
- Make default position `top`, but set manually set some to `right` - namely, anything with a dropdown. This prevents the popovers from obscuring or being obscured by the dropdowns.
- Do a bit more restructuring of the Popover component itself, and how it is integrated with other components
- More ref forwarding
- Make the open delay 1s
- Set the popovers to use lazy mounting (eg do not mount until the user opens the thing)
- Update the verbiage for many popover items and add missing dynamic prompts stuff
2023-09-22 11:04:35 +00:00
"paragraphs" : [
"Scales the selected area to the size best suited for the model before the image generation process."
]
2023-09-15 14:37:05 +00:00
}
} ,
2023-09-13 07:31:34 +00:00
"ui" : {
"hideProgressImages" : "Hide Progress Images" ,
"lockRatio" : "Lock Ratio" ,
"showProgressImages" : "Show Progress Images" ,
"swapSizes" : "Swap Sizes"
} ,
2023-02-18 04:23:24 +00:00
"unifiedCanvas" : {
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"accept" : "Accept" ,
"activeLayer" : "Active Layer" ,
"antialiasing" : "Antialiasing" ,
"autoSaveToGallery" : "Auto Save to Gallery" ,
2023-02-18 04:23:24 +00:00
"base" : "Base" ,
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"betaClear" : "Clear" ,
"betaDarkenOutside" : "Darken Outside" ,
"betaLimitToBox" : "Limit To Box" ,
"betaPreserveMasked" : "Preserve Masked" ,
"boundingBox" : "Bounding Box" ,
"boundingBoxPosition" : "Bounding Box Position" ,
2023-02-18 04:23:24 +00:00
"brush" : "Brush" ,
"brushOptions" : "Brush Options" ,
"brushSize" : "Size" ,
2023-09-13 07:31:34 +00:00
"canvasDimensions" : "Canvas Dimensions" ,
"canvasPosition" : "Canvas Position" ,
"canvasScale" : "Canvas Scale" ,
2023-02-18 04:23:24 +00:00
"canvasSettings" : "Canvas Settings" ,
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"clearCanvas" : "Clear Canvas" ,
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"clearCanvasHistory" : "Clear Canvas History" ,
"clearCanvasHistoryConfirm" : "Are you sure you want to clear the canvas history?" ,
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"clearCanvasHistoryMessage" : "Clearing the canvas history leaves your current canvas intact, but irreversibly clears the undo and redo history." ,
"clearHistory" : "Clear History" ,
"clearMask" : "Clear Mask" ,
"colorPicker" : "Color Picker" ,
"copyToClipboard" : "Copy to Clipboard" ,
"cursorPosition" : "Cursor Position" ,
"darkenOutsideSelection" : "Darken Outside Selection" ,
"discardAll" : "Discard All" ,
"downloadAsImage" : "Download As Image" ,
2023-02-18 04:23:24 +00:00
"emptyFolder" : "Empty Folder" ,
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"emptyTempImageFolder" : "Empty Temp Image Folder" ,
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"emptyTempImagesFolderConfirm" : "Are you sure you want to empty the temp folder?" ,
2023-09-13 07:31:34 +00:00
"emptyTempImagesFolderMessage" : "Emptying the temp image folder also fully resets the Unified Canvas. This includes all undo/redo history, images in the staging area, and the canvas base layer." ,
"enableMask" : "Enable Mask" ,
"eraseBoundingBox" : "Erase Bounding Box" ,
"eraser" : "Eraser" ,
"fillBoundingBox" : "Fill Bounding Box" ,
"layer" : "Layer" ,
"limitStrokesToBox" : "Limit Strokes to Box" ,
"mask" : "Mask" ,
"maskingOptions" : "Masking Options" ,
"mergeVisible" : "Merge Visible" ,
"move" : "Move" ,
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"next" : "Next" ,
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"preserveMaskedArea" : "Preserve Masked Area" ,
"previous" : "Previous" ,
"redo" : "Redo" ,
"resetView" : "Reset View" ,
"saveBoxRegionOnly" : "Save Box Region Only" ,
"saveToGallery" : "Save To Gallery" ,
"scaledBoundingBox" : "Scaled Bounding Box" ,
"showCanvasDebugInfo" : "Show Additional Canvas Info" ,
"showGrid" : "Show Grid" ,
2023-02-18 04:23:24 +00:00
"showHide" : "Show/Hide" ,
2023-09-27 07:12:57 +00:00
"showResultsOn" : "Show Results (On)" ,
"showResultsOff" : "Show Results (Off)" ,
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"showIntermediates" : "Show Intermediates" ,
"snapToGrid" : "Snap to Grid" ,
"undo" : "Undo"
2023-02-18 04:23:24 +00:00
}
}
