Commit Graph

554 Commits

Author SHA1 Message Date
Kent Keirsey
e66d0f7372
Merge branch 'main' into feat/nodes/freeu 2023-11-06 05:39:58 -08:00
Ryan Dick
aa02ebf8f5 Fix model cache gc.collect() condition. 2023-11-04 08:52:10 -04:00
Ryan Dick
fb3d0c4b12 Fix bug in model cache reference count checking. 2023-11-03 13:50:40 -07:00
Ryan Dick
8488ab0134 Reduce frequency that we call gc.collect() in the model cache. 2023-11-03 13:50:40 -07:00
Ryan Dick
875231ed3d Add reminder to clean up our model cache clearing logic. 2023-11-03 13:50:40 -07:00
Ryan Dick
43b300498f Remove explicit gc.collect() after transferring models from device to CPU. I'm not sure why this was there in the first place, but it was taking a significant amount of time (up to ~1sec in my tests). 2023-11-03 13:50:40 -07:00
Ryan Dick
e391f3c9a8 Skip torch.nn.Embedding.reset_parameters(...) when loading a text encoder model. 2023-11-02 19:41:33 -07:00
Ryan Dick
6e7a3f0546 (minor) Fix static checks and typo. 2023-11-02 19:20:37 -07:00
Ryan Dick
4a683cc669 Add a app config parameter to control the ModelCache logging behavior. 2023-11-02 19:20:37 -07:00
Ryan Dick
3781e56e57 Add log_memory_usage param to ModelCache. 2023-11-02 19:20:37 -07:00
Ryan Dick
8ff49109a8 Update get_pretty_snapshot_diff(...) to handle None-snapshots. 2023-11-02 19:20:37 -07:00
Ryan Dick
bac2a757e8 Replace deepcopy with a pickle roundtrip in apply_ti(...) to improve speed. 2023-11-02 19:05:24 -07:00
Ryan Dick
fa7f6a6a10 Further tidying of LoRA patching. Revert some changes that didn't end up being important under the constraint that calculations are done on the same device as the model. 2023-11-02 10:03:17 -07:00
Ryan Dick
61b17c475a Add TODO note about improving _resolve_lora_key(...). 2023-11-02 10:03:17 -07:00
Ryan Dick
379d68f595 Patch LoRA on device when model is already on device. 2023-11-02 10:03:17 -07:00
Ryan Dick
545c811bf1 Remove device and dtype members from LoRAModelRaw, they can too easily get out-of-sync with the underlying layer states. 2023-11-02 10:03:17 -07:00
Ryan Dick
2ba5b44ec4 Remove unused _lora_forward_hook(...). 2023-11-02 10:03:17 -07:00
Ryan Dick
7f4ce518b7 auto-format lora.py 2023-11-02 10:03:17 -07:00
Lincoln Stein
6cbc69f3b7 support conversion of controlnets from safetensors to diffusers 2023-10-23 22:06:10 -04:00
d8ahazard
fdf02c33d0 Catch generic model errors
Prevent the app from dying on invalid models.
2023-10-19 07:28:33 +11:00
Millun Atluri
001bba1719
Merge branch 'main' into feat/nodes/freeu 2023-10-17 15:58:00 +11:00
psychedelicious
c238a7f18b feat(api): chore: pydantic & fastapi upgrade
Upgrade pydantic and fastapi to latest.

- pydantic~=2.4.2
- fastapi~=103.2
- fastapi-events~=0.9.1

**Big Changes**

There are a number of logic changes needed to support pydantic v2. Most changes are very simple, like using the new methods to serialized and deserialize models, but there are a few more complex changes.

**Invocations**

The biggest change relates to invocation creation, instantiation and validation.

Because pydantic v2 moves all validation logic into the rust pydantic-core, we may no longer directly stick our fingers into the validation pie.

Previously, we (ab)used models and fields to allow invocation fields to be optional at instantiation, but required when `invoke()` is called. We directly manipulated the fields and invocation models when calling `invoke()`.

With pydantic v2, this is much more involved. Changes to the python wrapper do not propagate down to the rust validation logic - you have to rebuild the model. This causes problem with concurrent access to the invocation classes and is not a free operation.

This logic has been totally refactored and we do not need to change the model any more. The details are in `baseinvocation.py`, in the `InputField` function and `BaseInvocation.invoke_internal()` method.

In the end, this implementation is cleaner.

**Invocation Fields**

In pydantic v2, you can no longer directly add or remove fields from a model.

Previously, we did this to add the `type` field to invocations.

**Invocation Decorators**

With pydantic v2, we instead use the imperative `create_model()` API to create a new model with the additional field. This is done in `baseinvocation.py` in the `invocation()` wrapper.

A similar technique is used for `invocation_output()`.

**Minor Changes**

There are a number of minor changes around the pydantic v2 models API.

**Protected `model_` Namespace**

All models' pydantic-provided methods and attributes are prefixed with `model_` and this is considered a protected namespace. This causes some conflict, because "model" means something to us, and we have a ton of pydantic models with attributes starting with "model_".

Forunately, there are no direct conflicts. However, in any pydantic model where we define an attribute or method that starts with "model_", we must tell set the protected namespaces to an empty tuple.

```py
class IPAdapterModelField(BaseModel):
    model_name: str = Field(description="Name of the IP-Adapter model")
    base_model: BaseModelType = Field(description="Base model")

    model_config = ConfigDict(protected_namespaces=())
```

**Model Serialization**

Pydantic models no longer have `Model.dict()` or `Model.json()`.

Instead, we use `Model.model_dump()` or `Model.model_dump_json()`.

**Model Deserialization**

Pydantic models no longer have `Model.parse_obj()` or `Model.parse_raw()`, and there are no `parse_raw_as()` or `parse_obj_as()` functions.

Instead, you need to create a `TypeAdapter` object to parse python objects or JSON into a model.

```py
adapter_graph = TypeAdapter(Graph)
deserialized_graph_from_json = adapter_graph.validate_json(graph_json)
deserialized_graph_from_dict = adapter_graph.validate_python(graph_dict)
```

**Field Customisation**

Pydantic `Field`s no longer accept arbitrary args.

Now, you must put all additional arbitrary args in a `json_schema_extra` arg on the field.

**Schema Customisation**

FastAPI and pydantic schema generation now follows the OpenAPI version 3.1 spec.

This necessitates two changes:
- Our schema customization logic has been revised
- Schema parsing to build node templates has been revised

The specific aren't important, but this does present additional surface area for bugs.

**Performance Improvements**

Pydantic v2 is a full rewrite with a rust backend. This offers a substantial performance improvement (pydantic claims 5x to 50x depending on the task). We'll notice this the most during serialization and deserialization of sessions/graphs, which happens very very often - a couple times per node.

I haven't done any benchmarks, but anecdotally, graph execution is much faster. Also, very larges graphs - like with massive iterators - are much, much faster.
2023-10-17 14:59:25 +11:00
blessedcoolant
c9d95e5758
Merge branch 'main' into bugfix/ignore-dot-directories-on-model-scan 2023-10-15 17:23:02 +05:30
psychedelicious
48626c40fd fix(backend): handle systems with glibc < 2.33
`mallinfo2` is not available on `glibc` < 2.33.

On these systems, we successfully load the library but get an `AttributeError` on attempting to access `mallinfo2`.

I'm not sure if the old `mallinfo` will work, and not sure how to install it safely to test, so for now we just handle the `AttributeError`.

This means the enhanced memory snapshot logic will be skipped for these systems, which isn't a big deal.
2023-10-15 07:56:55 +11:00
Lincoln Stein
15cabc4968 Possibly closes #4815 2023-10-12 23:37:05 -04:00
Ryan Dick
40f9e49b5e Demote model cache logs from warning to debug based on the conversation here: https://discord.com/channels/1020123559063990373/1049495067846524939/1161647290189090816 2023-10-11 12:02:46 -04:00
psychedelicious
15b33ad501 feat(nodes): add freeu support
Add support for FreeU. See:
- https://huggingface.co/docs/diffusers/main/en/using-diffusers/freeu
- https://github.com/ChenyangSi/FreeU

Implementation:
- `ModelPatcher.apply_freeu()` handles the enabling freeu (which is very simple with diffusers).
- `FreeUConfig` model added to hold the hyperparameters.
- `freeu_config` added as optional sub-field on `UNetField`.
- `FreeUInvocation` added, works like LoRA - chain it to add the FreeU config to the UNet
- No support for model-dependent presets, this will be a future workflow editor enhancement

Closes #4845
2023-10-11 13:49:28 +11:00
Ryan Dick
61242bf86a Fix bug in skip_torch_weight_init() where the original behavior of torch.nn.Conv*d modules wasn't being restored correctly. 2023-10-10 10:05:50 -04:00
Ryan Dick
58b56e9b1e Add a skip_torch_weight_init() context manager to improve model load times (from disk). 2023-10-09 14:12:56 -04:00
Ryan Dick
096d195d6e
Merge branch 'main' into ryan/model-cache-logging-only 2023-10-06 09:52:45 -04:00
Ryan Dick
78377469db
Add support for T2I-Adapter in node workflows (#4612)
* Bump diffusers to 0.21.2.

* Add T2IAdapterInvocation boilerplate.

* Add T2I-Adapter model to model-management.

* (minor) Tidy prepare_control_image(...).

* Add logic to run the T2I-Adapter models at the start of the DenoiseLatentsInvocation.

* Add logic for applying T2I-Adapter weights and accumulating.

* Add T2IAdapter to MODEL_CLASSES map.

* yarn typegen

* Add model probes for T2I-Adapter models.

* Add all of the frontend boilerplate required to use T2I-Adapter in the nodes editor.

* Add T2IAdapterModel.convert_if_required(...).

* Fix errors in T2I-Adapter input image sizing logic.

* Fix bug with handling of multiple T2I-Adapters.

* black / flake8

* Fix typo

* yarn build

* Add num_channels param to prepare_control_image(...).

* Link to upstream diffusers bugfix PR that currently requires a workaround.

* feat: Add Color Map Preprocessor

Needed for the color T2I Adapter

* feat: Add Color Map Preprocessor to Linear UI

* Revert "feat: Add Color Map Preprocessor"

This reverts commit a1119a00bf.

* Revert "feat: Add Color Map Preprocessor to Linear UI"

This reverts commit bd8a9b82d8.

* Fix T2I-Adapter field rendering in workflow editor.

* yarn build, yarn typegen

---------

Co-authored-by: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
2023-10-05 16:29:16 +11:00
Ryan Dick
2479a59e5e Re-enable garbage collection in model cache MemorySnapshots. 2023-10-03 15:18:47 -04:00
Ryan Dick
7d0ac2c36d (minor) clean up typos. 2023-10-03 15:00:03 -04:00
Ryan Dick
519b892f0c Add unit test for Struct_mallinfo2.__str__() 2023-10-03 14:25:34 -04:00
Ryan Dick
763dcacfd3 Add unit test for get_pretty_snapshot_diff(...). 2023-10-03 14:25:34 -04:00
Ryan Dick
22a84930f6 Disable garbage collection in ModelCache calls to MemorySnapshot in order minimize snapshot overhead. 2023-10-03 14:25:34 -04:00
Ryan Dick
d64e17e043 Add README with info about glib memory fragmentation caused by the model cache. 2023-10-03 14:25:34 -04:00
Ryan Dick
ba54277011 Catch a more specific exception in environments that do not have a libc shared library. 2023-10-03 14:25:34 -04:00
Ryan Dick
5915a4a51c Minor fixes. 2023-10-03 14:25:34 -04:00
Ryan Dick
4580ba0d87 Remove logic to update model cache size estimates dynamically. 2023-10-03 14:25:34 -04:00
Ryan Dick
b9fd2e9e76 Improve get_pretty_snapshot_diff(...) message formatting. 2023-10-03 14:25:34 -04:00
Ryan Dick
75b65597af Add malloc info to MemorySnapshot. 2023-10-03 14:25:34 -04:00
Ryan Dick
2a3c0ab5d2 Move MemorySnapshot to its own file. 2023-10-03 14:25:34 -04:00
Ryan Dick
7d61373b82 Add LibcUtil class. 2023-10-03 14:25:34 -04:00
Ryan Dick
7d65555a5a Fix type error in torch device comparison. 2023-10-03 14:25:34 -04:00
Ryan Dick
123f2b2dbc Update cache model size estimates based on changes in VRAM when moving models to/from CUDA. 2023-10-03 14:25:34 -04:00
Ryan Dick
1e4e42556e Update model cache device comparison to treat 'cuda' and 'cuda:0' as the same device type. 2023-10-03 14:25:34 -04:00
Ryan Dick
1f6699ac43 Consolidate all model.to(...) calls in the model cache to use a utility function with better logging. 2023-10-03 14:25:34 -04:00
Ryan Dick
ace8665411 Add warning log if moving a model from cuda to cpu causes unexpected change in VRAM usage. 2023-10-03 14:25:34 -04:00
Ryan Dick
7fa5bae8fd Add warning log if moving model from RAM to VRAM causes an unexpected change in VRAM usage. 2023-10-03 14:25:34 -04:00