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Merge branch 'main' into lstein/feat/simple-mm2-api

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This commit is contained in:
Lincoln Stein
2024-04-17 17:18:13 -04:00
committed by GitHub
parent 470a39935c 5295a398f3
commit 34cdfc61ab
28 changed files with 396 additions and 79 deletions
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42
invokeai/app/invocations/ip_adapter.py
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@ -4,20 +4,8 @@ from typing import List, Literal, Optional, Union
from pydantic import BaseModel, Field, field_validator, model_validator
from typing_extensions import Self
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import (
FieldDescriptions,
Input,
InputField,
OutputField,
TensorField,
UIType,
)
from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, TensorField, UIType
from invokeai.app.invocations.model import ModelIdentifierField
from invokeai.app.invocations.primitives import ImageField
from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
@ -36,6 +24,7 @@ class IPAdapterField(BaseModel):
ip_adapter_model: ModelIdentifierField = Field(description="The IP-Adapter model to use.")
image_encoder_model: ModelIdentifierField = Field(description="The name of the CLIP image encoder model.")
weight: Union[float, List[float]] = Field(default=1, description="The weight given to the IP-Adapter.")
target_blocks: List[str] = Field(default=[], description="The IP Adapter blocks to apply")
begin_step_percent: float = Field(
default=0, ge=0, le=1, description="When the IP-Adapter is first applied (% of total steps)"
)
@ -69,7 +58,7 @@ class IPAdapterOutput(BaseInvocationOutput):
CLIP_VISION_MODEL_MAP = {"ViT-H": "ip_adapter_sd_image_encoder", "ViT-G": "ip_adapter_sdxl_image_encoder"}
@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.3.0")
@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.4.0")
class IPAdapterInvocation(BaseInvocation):
"""Collects IP-Adapter info to pass to other nodes."""
@ -90,6 +79,9 @@ class IPAdapterInvocation(BaseInvocation):
weight: Union[float, List[float]] = InputField(
default=1, description="The weight given to the IP-Adapter", title="Weight"
)
method: Literal["full", "style", "composition"] = InputField(
default="full", description="The method to apply the IP-Adapter"
)
begin_step_percent: float = InputField(
default=0, ge=0, le=1, description="When the IP-Adapter is first applied (% of total steps)"
)
@ -124,12 +116,32 @@ class IPAdapterInvocation(BaseInvocation):
image_encoder_model = self._get_image_encoder(context, image_encoder_model_name)
if self.method == "style":
if ip_adapter_info.base == "sd-1":
target_blocks = ["up_blocks.1"]
elif ip_adapter_info.base == "sdxl":
target_blocks = ["up_blocks.0.attentions.1"]
else:
raise ValueError(f"Unsupported IP-Adapter base type: '{ip_adapter_info.base}'.")
elif self.method == "composition":
if ip_adapter_info.base == "sd-1":
target_blocks = ["down_blocks.2", "mid_block"]
elif ip_adapter_info.base == "sdxl":
target_blocks = ["down_blocks.2.attentions.1"]
else:
raise ValueError(f"Unsupported IP-Adapter base type: '{ip_adapter_info.base}'.")
elif self.method == "full":
target_blocks = ["block"]
else:
raise ValueError(f"Unexpected IP-Adapter method: '{self.method}'.")
return IPAdapterOutput(
ip_adapter=IPAdapterField(
image=self.image,
ip_adapter_model=self.ip_adapter_model,
image_encoder_model=ModelIdentifierField.from_config(image_encoder_model),
weight=self.weight,
target_blocks=target_blocks,
begin_step_percent=self.begin_step_percent,
end_step_percent=self.end_step_percent,
mask=self.mask,

1
invokeai/app/invocations/latent.py
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@ -679,6 +679,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
IPAdapterData(
ip_adapter_model=ip_adapter_model,
weight=single_ip_adapter.weight,
target_blocks=single_ip_adapter.target_blocks,
begin_step_percent=single_ip_adapter.begin_step_percent,
end_step_percent=single_ip_adapter.end_step_percent,
ip_adapter_conditioning=IPAdapterConditioningInfo(image_prompt_embeds, uncond_image_prompt_embeds),

1
invokeai/app/invocations/metadata.py
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@ -36,6 +36,7 @@ class IPAdapterMetadataField(BaseModel):
image: ImageField = Field(description="The IP-Adapter image prompt.")
ip_adapter_model: ModelIdentifierField = Field(description="The IP-Adapter model.")
clip_vision_model: Literal["ViT-H", "ViT-G"] = Field(description="The CLIP Vision model")
method: Literal["full", "style", "composition"] = Field(description="Method to apply IP Weights with")
weight: Union[float, list[float]] = Field(description="The weight given to the IP-Adapter")
begin_step_percent: float = Field(description="When the IP-Adapter is first applied (% of total steps)")
end_step_percent: float = Field(description="When the IP-Adapter is last applied (% of total steps)")

3
invokeai/app/services/model_install/model_install_default.py
View File

@ -763,6 +763,8 @@ class ModelInstallService(ModelInstallServiceBase):
self._download_cache[download_job.source] = install_job # matches a download job to an install job
install_job.download_parts.add(download_job)
# only start the jobs once install_job.download_parts is fully populated
for download_job in install_job.download_parts:
self._download_queue.submit_download_job(
download_job,
on_start=self._download_started_callback,
@ -771,6 +773,7 @@ class ModelInstallService(ModelInstallServiceBase):
on_error=self._download_error_callback,
on_cancelled=self._download_cancelled_callback,
)
return install_job
def _stat_size(self, path: Path) -> int: