This PR corrects a bug in which embeddings were not being applied when a
non-diffusers model was loaded.
- Fixes#2954
- Also improves diagnostic reporting during embedding loading.
- This PR turns on pickle scanning before a legacy checkpoint file
is loaded from disk within the checkpoint_to_diffusers module.
- Also miscellaneous diagnostic message cleanup.
- When a legacy checkpoint model is loaded via --convert_ckpt and its
models.yaml stanza refers to a custom VAE path (using the 'vae:'
key), the custom VAE will be converted and used within the diffusers
model. Otherwise the VAE contained within the legacy model will be
used.
- Note that the heuristic_import() method, which imports arbitrary
legacy files on disk and URLs, will continue to default to the
the standard stabilityai/sd-vae-ft-mse VAE. This can be fixed after
the fact by editing the models.yaml stanza using the Web or CLI
UIs.
- Fixes issue #2917
- 86932469e76f1315ee18bfa2fc52b588241dace1 add image_to_dataURL util
- 0c2611059711b45bb6142d30b1d1343ac24268f3 make fast latents method
static
- this method doesn't really need `self` and should be able to be called
without instantiating `Generator`
- 2360bfb6558ea511e9c9576f3d4b5535870d84b4 fix schema gen for
GraphExecutionState
- `GraphExecutionState` uses `default_factory` in its fields; the result
is the OpenAPI schema marks those fields as optional, which propagates
to the generated API client, which means we need a lot of unnecessary
type guards to use this data type. the [simple
fix](https://github.com/pydantic/pydantic/discussions/4577) is to add
config to explicitly say all class properties are required. looks this
this will be resolved in a future pydantic release
- 3cd7319cfdb0f07c6bb12d62d7d02efe1ab12675 fix step callback and fast
latent generation on nodes. have this working in UI. depends on the
small change in #2957
Update `compel` to 1.0.0.
This fixes#2832.
It also changes the way downweighting is applied. In particular,
downweighting should now be much better and more controllable.
From the [compel
changelog](https://github.com/damian0815/compel#changelog):
> Downweighting now works by applying an attention mask to remove the
downweighted tokens, rather than literally removing them from the
sequence. This behaviour is the default, but the old behaviour can be
re-enabled by passing `downweight_mode=DownweightMode.REMOVE` on init of
the `Compel` instance.
>
> Formerly, downweighting a token worked by both multiplying the
weighting of the token's embedding, and doing an inverse-weighted blend
with a copy of the token sequence that had the downweighted tokens
removed. The intuition is that as weight approaches zero, the tokens
being downweighted should be actually removed from the sequence.
However, removing the tokens resulted in the positioning of all
downstream tokens becoming messed up. The blend ended up blending a lot
more than just the tokens in question.
>
> As of v1.0.0, taking advice from @keturn and @bonlime
(https://github.com/damian0815/compel/issues/7) the procedure is by
default different. Downweighting still involves a blend but what is
blended is a version of the token sequence with the downweighted tokens
masked out, rather than removed. This correctly preserves positioning
embeddings of the other tokens.
* Update root component to allow optional children that will render as
dynamic header of UI
* Export additional components (logo & themeChanger) for use in said
dynamic header (more to come here)
