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Brandon Rising 2024-08-14 11:53:07 -04:00 committed by Brandon
parent 56fda669fd
commit 9ed53af520
6 changed files with 8 additions and 11 deletions
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5
invokeai/app/invocations/flux_text_to_image.py
View File

@ -101,10 +101,7 @@ class FluxTextToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
# if the cache is not empty.
# context.models._services.model_manager.load.ram_cache.make_room(24 * 2**30)
with (
transformer_info as transformer,
scheduler_info as scheduler
):
with transformer_info as transformer, scheduler_info as scheduler:
assert isinstance(transformer, FluxTransformer2DModel)
assert isinstance(scheduler, FlowMatchEulerDiscreteScheduler)

2
invokeai/app/invocations/model.py
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@ -60,11 +60,11 @@ class CLIPField(BaseModel):
loras: List[LoRAField] = Field(description="LoRAs to apply on model loading")
class TransformerField(BaseModel):
transformer: ModelIdentifierField = Field(description="Info to load Transformer submodel")
scheduler: ModelIdentifierField = Field(description="Info to load scheduler submodel")
class T5EncoderField(BaseModel):
tokenizer: ModelIdentifierField = Field(description="Info to load tokenizer submodel")
text_encoder: ModelIdentifierField = Field(description="Info to load text_encoder submodel")

4
invokeai/backend/model_manager/load/model_util.py
View File

@ -52,9 +52,7 @@ def calc_model_size_by_data(logger: logging.Logger, model: AnyModel) -> int:
return model.calc_size()
elif isinstance(
model,
(
T5TokenizerFast,
),
(T5TokenizerFast,),
):
return len(model)
else:

2
invokeai/backend/model_manager/util/select_hf_files.py
View File

@ -54,7 +54,7 @@ def filter_files(
"lora_weights.safetensors",
"weights.pb",
"onnx_data",
"spiece.model", # Added for `black-forest-labs/FLUX.1-schnell`.
"spiece.model", # Added for `black-forest-labs/FLUX.1-schnell`.
)
):
paths.append(file)

2
invokeai/backend/quantization/fast_quantized_diffusion_model.py
View File

@ -19,7 +19,7 @@ from invokeai.backend.requantize import requantize
class FastQuantizedDiffusersModel(QuantizedDiffusersModel):
@classmethod
def from_pretrained(cls, model_name_or_path: Union[str, os.PathLike], base_class = FluxTransformer2DModel, **kwargs):
def from_pretrained(cls, model_name_or_path: Union[str, os.PathLike], base_class=FluxTransformer2DModel, **kwargs):
"""We override the `from_pretrained()` method in order to use our custom `requantize()` implementation."""
base_class = base_class or cls.base_class
if base_class is None:

4
invokeai/backend/quantization/fast_quantized_transformers_model.py
View File

@ -15,7 +15,9 @@ from invokeai.backend.requantize import requantize
class FastQuantizedTransformersModel(QuantizedTransformersModel):
@classmethod
def from_pretrained(cls, model_name_or_path: Union[str, os.PathLike], auto_class = AutoModelForTextEncoding, **kwargs):
def from_pretrained(
cls, model_name_or_path: Union[str, os.PathLike], auto_class=AutoModelForTextEncoding, **kwargs
):
"""We override the `from_pretrained()` method in order to use our custom `requantize()` implementation."""
auto_class = auto_class or cls.auto_class
if auto_class is None: