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Merge branch 'main' into diffusers-upgrade

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blessedcoolant
2023-06-13 05:29:15 +12:00
committed by GitHub
parent 7bce455d16 60a2fbec41
commit 2a814d886b
55 changed files with 1277 additions and 361 deletions
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37
invokeai/app/invocations/latent.py
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@ -174,22 +174,36 @@ class TextToLatentsInvocation(BaseInvocation):
negative_conditioning: Optional[ConditioningField] = Field(description="Negative conditioning for generation")
noise: Optional[LatentsField] = Field(description="The noise to use")
steps: int = Field(default=10, gt=0, description="The number of steps to use to generate the image")
cfg_scale: float = Field(default=7.5, ge=1, description="The Classifier-Free Guidance, higher values may result in a result closer to the prompt", )
cfg_scale: Union[float, List[float]] = Field(default=7.5, ge=1, description="The Classifier-Free Guidance, higher values may result in a result closer to the prompt", )
scheduler: SAMPLER_NAME_VALUES = Field(default="euler", description="The scheduler to use" )
model: str = Field(default="", description="The model to use (currently ignored)")
control: Union[ControlField, list[ControlField]] = Field(default=None, description="The control to use")
control: Union[ControlField, List[ControlField]] = Field(default=None, description="The control to use")
# seamless: bool = Field(default=False, description="Whether or not to generate an image that can tile without seams", )
# seamless_axes: str = Field(default="", description="The axes to tile the image on, 'x' and/or 'y'")
# fmt: on
@validator("cfg_scale")
def ge_one(cls, v):
"""validate that all cfg_scale values are >= 1"""
if isinstance(v, list):
for i in v:
if i < 1:
raise ValueError('cfg_scale must be greater than 1')
else:
if v < 1:
raise ValueError('cfg_scale must be greater than 1')
return v
# Schema customisation
class Config(InvocationConfig):
schema_extra = {
"ui": {
"tags": ["latents", "image"],
"tags": ["latents"],
"type_hints": {
"model": "model",
"control": "control",
# "cfg_scale": "float",
"cfg_scale": "number"
}
},
}
@ -244,10 +258,10 @@ class TextToLatentsInvocation(BaseInvocation):
[c, uc] = compel.pad_conditioning_tensors_to_same_length([c, uc])
conditioning_data = ConditioningData(
uc,
c,
self.cfg_scale,
extra_conditioning_info,
unconditioned_embeddings=uc,
text_embeddings=c,
guidance_scale=self.cfg_scale,
extra=extra_conditioning_info,
postprocessing_settings=PostprocessingSettings(
threshold=0.0,#threshold,
warmup=0.2,#warmup,
@ -348,7 +362,8 @@ class TextToLatentsInvocation(BaseInvocation):
control_data = self.prep_control_data(model=model, context=context, control_input=self.control,
latents_shape=noise.shape,
do_classifier_free_guidance=(self.cfg_scale >= 1.0))
# do_classifier_free_guidance=(self.cfg_scale >= 1.0))
do_classifier_free_guidance=True,)
# TODO: Verify the noise is the right size
result_latents, result_attention_map_saver = model.latents_from_embeddings(
@ -385,6 +400,7 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
"type_hints": {
"model": "model",
"control": "control",
"cfg_scale": "number",
}
},
}
@ -403,10 +419,11 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
model = self.get_model(context.services.model_manager)
conditioning_data = self.get_conditioning_data(context, model)
print("type of control input: ", type(self.control))
control_data = self.prep_control_data(model=model, context=context, control_input=self.control,
latents_shape=noise.shape,
do_classifier_free_guidance=(self.cfg_scale >= 1.0))
# do_classifier_free_guidance=(self.cfg_scale >= 1.0))
do_classifier_free_guidance=True,
)
# TODO: Verify the noise is the right size