Merge branch 'main' into depth_anything_v2

This commit is contained in:
blessedcoolant 2024-07-31 00:53:32 +05:30
commit f170697ebe
73 changed files with 3066 additions and 1625 deletions

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@ -55,6 +55,7 @@ RUN --mount=type=cache,target=/root/.cache/pip \
FROM node:20-slim AS web-builder
ENV PNPM_HOME="/pnpm"
ENV PATH="$PNPM_HOME:$PATH"
RUN corepack use pnpm@8.x
RUN corepack enable
WORKDIR /build

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@ -37,9 +37,9 @@ from invokeai.app.services.shared.invocation_context import InvocationContext
from invokeai.app.util.controlnet_utils import prepare_control_image
from invokeai.backend.ip_adapter.ip_adapter import IPAdapter
from invokeai.backend.lora import LoRAModelRaw
from invokeai.backend.model_manager import BaseModelType
from invokeai.backend.model_manager import BaseModelType, ModelVariantType
from invokeai.backend.model_patcher import ModelPatcher
from invokeai.backend.stable_diffusion import PipelineIntermediateState, set_seamless
from invokeai.backend.stable_diffusion import PipelineIntermediateState
from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext, DenoiseInputs
from invokeai.backend.stable_diffusion.diffusers_pipeline import (
ControlNetData,
@ -60,8 +60,12 @@ from invokeai.backend.stable_diffusion.diffusion_backend import StableDiffusionB
from invokeai.backend.stable_diffusion.extension_callback_type import ExtensionCallbackType
from invokeai.backend.stable_diffusion.extensions.controlnet import ControlNetExt
from invokeai.backend.stable_diffusion.extensions.freeu import FreeUExt
from invokeai.backend.stable_diffusion.extensions.inpaint import InpaintExt
from invokeai.backend.stable_diffusion.extensions.inpaint_model import InpaintModelExt
from invokeai.backend.stable_diffusion.extensions.preview import PreviewExt
from invokeai.backend.stable_diffusion.extensions.rescale_cfg import RescaleCFGExt
from invokeai.backend.stable_diffusion.extensions.seamless import SeamlessExt
from invokeai.backend.stable_diffusion.extensions.t2i_adapter import T2IAdapterExt
from invokeai.backend.stable_diffusion.extensions_manager import ExtensionsManager
from invokeai.backend.stable_diffusion.schedulers import SCHEDULER_MAP
from invokeai.backend.stable_diffusion.schedulers.schedulers import SCHEDULER_NAME_VALUES
@ -498,6 +502,33 @@ class DenoiseLatentsInvocation(BaseInvocation):
)
)
@staticmethod
def parse_t2i_adapter_field(
exit_stack: ExitStack,
context: InvocationContext,
t2i_adapters: Optional[Union[T2IAdapterField, list[T2IAdapterField]]],
ext_manager: ExtensionsManager,
) -> None:
if t2i_adapters is None:
return
# Handle the possibility that t2i_adapters could be a list or a single T2IAdapterField.
if isinstance(t2i_adapters, T2IAdapterField):
t2i_adapters = [t2i_adapters]
for t2i_adapter_field in t2i_adapters:
ext_manager.add_extension(
T2IAdapterExt(
node_context=context,
model_id=t2i_adapter_field.t2i_adapter_model,
image=context.images.get_pil(t2i_adapter_field.image.image_name),
weight=t2i_adapter_field.weight,
begin_step_percent=t2i_adapter_field.begin_step_percent,
end_step_percent=t2i_adapter_field.end_step_percent,
resize_mode=t2i_adapter_field.resize_mode,
)
)
def prep_ip_adapter_image_prompts(
self,
context: InvocationContext,
@ -707,7 +738,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
else:
masked_latents = torch.where(mask < 0.5, 0.0, latents)
return 1 - mask, masked_latents, self.denoise_mask.gradient
return mask, masked_latents, self.denoise_mask.gradient
@staticmethod
def prepare_noise_and_latents(
@ -765,10 +796,6 @@ class DenoiseLatentsInvocation(BaseInvocation):
dtype = TorchDevice.choose_torch_dtype()
seed, noise, latents = self.prepare_noise_and_latents(context, self.noise, self.latents)
latents = latents.to(device=device, dtype=dtype)
if noise is not None:
noise = noise.to(device=device, dtype=dtype)
_, _, latent_height, latent_width = latents.shape
conditioning_data = self.get_conditioning_data(
@ -801,21 +828,6 @@ class DenoiseLatentsInvocation(BaseInvocation):
denoising_end=self.denoising_end,
)
denoise_ctx = DenoiseContext(
inputs=DenoiseInputs(
orig_latents=latents,
timesteps=timesteps,
init_timestep=init_timestep,
noise=noise,
seed=seed,
scheduler_step_kwargs=scheduler_step_kwargs,
conditioning_data=conditioning_data,
attention_processor_cls=CustomAttnProcessor2_0,
),
unet=None,
scheduler=scheduler,
)
# get the unet's config so that we can pass the base to sd_step_callback()
unet_config = context.models.get_config(self.unet.unet.key)
@ -833,6 +845,40 @@ class DenoiseLatentsInvocation(BaseInvocation):
if self.unet.freeu_config:
ext_manager.add_extension(FreeUExt(self.unet.freeu_config))
### seamless
if self.unet.seamless_axes:
ext_manager.add_extension(SeamlessExt(self.unet.seamless_axes))
### inpaint
mask, masked_latents, is_gradient_mask = self.prep_inpaint_mask(context, latents)
# NOTE: We used to identify inpainting models by inpecting the shape of the loaded UNet model weights. Now we
# use the ModelVariantType config. During testing, there was a report of a user with models that had an
# incorrect ModelVariantType value. Re-installing the model fixed the issue. If this issue turns out to be
# prevalent, we will have to revisit how we initialize the inpainting extensions.
if unet_config.variant == ModelVariantType.Inpaint:
ext_manager.add_extension(InpaintModelExt(mask, masked_latents, is_gradient_mask))
elif mask is not None:
ext_manager.add_extension(InpaintExt(mask, is_gradient_mask))
# Initialize context for modular denoise
latents = latents.to(device=device, dtype=dtype)
if noise is not None:
noise = noise.to(device=device, dtype=dtype)
denoise_ctx = DenoiseContext(
inputs=DenoiseInputs(
orig_latents=latents,
timesteps=timesteps,
init_timestep=init_timestep,
noise=noise,
seed=seed,
scheduler_step_kwargs=scheduler_step_kwargs,
conditioning_data=conditioning_data,
attention_processor_cls=CustomAttnProcessor2_0,
),
unet=None,
scheduler=scheduler,
)
# context for loading additional models
with ExitStack() as exit_stack:
# later should be smth like:
@ -840,6 +886,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
# ext = extension_field.to_extension(exit_stack, context, ext_manager)
# ext_manager.add_extension(ext)
self.parse_controlnet_field(exit_stack, context, self.control, ext_manager)
self.parse_t2i_adapter_field(exit_stack, context, self.t2i_adapter, ext_manager)
# ext: t2i/ip adapter
ext_manager.run_callback(ExtensionCallbackType.SETUP, denoise_ctx)
@ -871,6 +918,10 @@ class DenoiseLatentsInvocation(BaseInvocation):
seed, noise, latents = self.prepare_noise_and_latents(context, self.noise, self.latents)
mask, masked_latents, gradient_mask = self.prep_inpaint_mask(context, latents)
# At this point, the mask ranges from 0 (leave unchanged) to 1 (inpaint).
# We invert the mask here for compatibility with the old backend implementation.
if mask is not None:
mask = 1 - mask
# TODO(ryand): I have hard-coded `do_classifier_free_guidance=True` to mirror the behaviour of ControlNets,
# below. Investigate whether this is appropriate.
@ -915,7 +966,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
ExitStack() as exit_stack,
unet_info.model_on_device() as (model_state_dict, unet),
ModelPatcher.apply_freeu(unet, self.unet.freeu_config),
set_seamless(unet, self.unet.seamless_axes), # FIXME
SeamlessExt.static_patch_model(unet, self.unet.seamless_axes), # FIXME
# Apply the LoRA after unet has been moved to its target device for faster patching.
ModelPatcher.apply_lora_unet(
unet,

View File

@ -24,7 +24,7 @@ from invokeai.app.invocations.fields import (
from invokeai.app.invocations.model import VAEField
from invokeai.app.invocations.primitives import ImageOutput
from invokeai.app.services.shared.invocation_context import InvocationContext
from invokeai.backend.stable_diffusion import set_seamless
from invokeai.backend.stable_diffusion.extensions.seamless import SeamlessExt
from invokeai.backend.stable_diffusion.vae_tiling import patch_vae_tiling_params
from invokeai.backend.util.devices import TorchDevice
@ -59,7 +59,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
vae_info = context.models.load(self.vae.vae)
assert isinstance(vae_info.model, (AutoencoderKL, AutoencoderTiny))
with set_seamless(vae_info.model, self.vae.seamless_axes), vae_info as vae:
with SeamlessExt.static_patch_model(vae_info.model, self.vae.seamless_axes), vae_info as vae:
assert isinstance(vae, (AutoencoderKL, AutoencoderTiny))
latents = latents.to(vae.device)
if self.fp32:

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@ -98,6 +98,9 @@ class StableDiffusionDiffusersModel(GenericDiffusersLoader):
ModelVariantType.Normal: StableDiffusionXLPipeline,
ModelVariantType.Inpaint: StableDiffusionXLInpaintPipeline,
},
BaseModelType.StableDiffusionXLRefiner: {
ModelVariantType.Normal: StableDiffusionXLPipeline,
},
}
assert isinstance(config, MainCheckpointConfig)
try:

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@ -187,164 +187,171 @@ STARTER_MODELS: list[StarterModel] = [
# endregion
# region ControlNet
StarterModel(
name="QRCode Monster",
name="QRCode Monster v2 (SD1.5)",
base=BaseModelType.StableDiffusion1,
source="monster-labs/control_v1p_sd15_qrcode_monster",
description="Controlnet model that generates scannable creative QR codes",
source="monster-labs/control_v1p_sd15_qrcode_monster::v2",
description="ControlNet model that generates scannable creative QR codes",
type=ModelType.ControlNet,
),
StarterModel(
name="QRCode Monster (SDXL)",
base=BaseModelType.StableDiffusionXL,
source="monster-labs/control_v1p_sdxl_qrcode_monster",
description="ControlNet model that generates scannable creative QR codes",
type=ModelType.ControlNet,
),
StarterModel(
name="canny",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_canny",
description="Controlnet weights trained on sd-1.5 with canny conditioning.",
description="ControlNet weights trained on sd-1.5 with canny conditioning.",
type=ModelType.ControlNet,
),
StarterModel(
name="inpaint",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_inpaint",
description="Controlnet weights trained on sd-1.5 with canny conditioning, inpaint version",
description="ControlNet weights trained on sd-1.5 with canny conditioning, inpaint version",
type=ModelType.ControlNet,
),
StarterModel(
name="mlsd",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_mlsd",
description="Controlnet weights trained on sd-1.5 with canny conditioning, MLSD version",
description="ControlNet weights trained on sd-1.5 with canny conditioning, MLSD version",
type=ModelType.ControlNet,
),
StarterModel(
name="depth",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11f1p_sd15_depth",
description="Controlnet weights trained on sd-1.5 with depth conditioning",
description="ControlNet weights trained on sd-1.5 with depth conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="normal_bae",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_normalbae",
description="Controlnet weights trained on sd-1.5 with normalbae image conditioning",
description="ControlNet weights trained on sd-1.5 with normalbae image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="seg",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_seg",
description="Controlnet weights trained on sd-1.5 with seg image conditioning",
description="ControlNet weights trained on sd-1.5 with seg image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="lineart",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_lineart",
description="Controlnet weights trained on sd-1.5 with lineart image conditioning",
description="ControlNet weights trained on sd-1.5 with lineart image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="lineart_anime",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15s2_lineart_anime",
description="Controlnet weights trained on sd-1.5 with anime image conditioning",
description="ControlNet weights trained on sd-1.5 with anime image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="openpose",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_openpose",
description="Controlnet weights trained on sd-1.5 with openpose image conditioning",
description="ControlNet weights trained on sd-1.5 with openpose image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="scribble",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_scribble",
description="Controlnet weights trained on sd-1.5 with scribble image conditioning",
description="ControlNet weights trained on sd-1.5 with scribble image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="softedge",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11p_sd15_softedge",
description="Controlnet weights trained on sd-1.5 with soft edge conditioning",
description="ControlNet weights trained on sd-1.5 with soft edge conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="shuffle",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11e_sd15_shuffle",
description="Controlnet weights trained on sd-1.5 with shuffle image conditioning",
description="ControlNet weights trained on sd-1.5 with shuffle image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="tile",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11f1e_sd15_tile",
description="Controlnet weights trained on sd-1.5 with tiled image conditioning",
description="ControlNet weights trained on sd-1.5 with tiled image conditioning",
type=ModelType.ControlNet,
),
StarterModel(
name="ip2p",
base=BaseModelType.StableDiffusion1,
source="lllyasviel/control_v11e_sd15_ip2p",
description="Controlnet weights trained on sd-1.5 with ip2p conditioning.",
description="ControlNet weights trained on sd-1.5 with ip2p conditioning.",
type=ModelType.ControlNet,
),
StarterModel(
name="canny-sdxl",
base=BaseModelType.StableDiffusionXL,
source="xinsir/controlnet-canny-sdxl-1.0",
description="Controlnet weights trained on sdxl-1.0 with canny conditioning, by Xinsir.",
source="xinsir/controlNet-canny-sdxl-1.0",
description="ControlNet weights trained on sdxl-1.0 with canny conditioning, by Xinsir.",
type=ModelType.ControlNet,
),
StarterModel(
name="depth-sdxl",
base=BaseModelType.StableDiffusionXL,
source="diffusers/controlnet-depth-sdxl-1.0",
description="Controlnet weights trained on sdxl-1.0 with depth conditioning.",
source="diffusers/controlNet-depth-sdxl-1.0",
description="ControlNet weights trained on sdxl-1.0 with depth conditioning.",
type=ModelType.ControlNet,
),
StarterModel(
name="softedge-dexined-sdxl",
base=BaseModelType.StableDiffusionXL,
source="SargeZT/controlnet-sd-xl-1.0-softedge-dexined",
description="Controlnet weights trained on sdxl-1.0 with dexined soft edge preprocessing.",
source="SargeZT/controlNet-sd-xl-1.0-softedge-dexined",
description="ControlNet weights trained on sdxl-1.0 with dexined soft edge preprocessing.",
type=ModelType.ControlNet,
),
StarterModel(
name="depth-16bit-zoe-sdxl",
base=BaseModelType.StableDiffusionXL,
source="SargeZT/controlnet-sd-xl-1.0-depth-16bit-zoe",
description="Controlnet weights trained on sdxl-1.0 with Zoe's preprocessor (16 bits).",
source="SargeZT/controlNet-sd-xl-1.0-depth-16bit-zoe",
description="ControlNet weights trained on sdxl-1.0 with Zoe's preprocessor (16 bits).",
type=ModelType.ControlNet,
),
StarterModel(
name="depth-zoe-sdxl",
base=BaseModelType.StableDiffusionXL,
source="diffusers/controlnet-zoe-depth-sdxl-1.0",
description="Controlnet weights trained on sdxl-1.0 with Zoe's preprocessor (32 bits).",
source="diffusers/controlNet-zoe-depth-sdxl-1.0",
description="ControlNet weights trained on sdxl-1.0 with Zoe's preprocessor (32 bits).",
type=ModelType.ControlNet,
),
StarterModel(
name="openpose-sdxl",
base=BaseModelType.StableDiffusionXL,
source="xinsir/controlnet-openpose-sdxl-1.0",
description="Controlnet weights trained on sdxl-1.0 compatible with the DWPose processor by Xinsir.",
source="xinsir/controlNet-openpose-sdxl-1.0",
description="ControlNet weights trained on sdxl-1.0 compatible with the DWPose processor by Xinsir.",
type=ModelType.ControlNet,
),
StarterModel(
name="scribble-sdxl",
base=BaseModelType.StableDiffusionXL,
source="xinsir/controlnet-scribble-sdxl-1.0",
description="Controlnet weights trained on sdxl-1.0 compatible with various lineart processors and black/white sketches by Xinsir.",
source="xinsir/controlNet-scribble-sdxl-1.0",
description="ControlNet weights trained on sdxl-1.0 compatible with various lineart processors and black/white sketches by Xinsir.",
type=ModelType.ControlNet,
),
StarterModel(
name="tile-sdxl",
base=BaseModelType.StableDiffusionXL,
source="xinsir/controlnet-tile-sdxl-1.0",
description="Controlnet weights trained on sdxl-1.0 with tiled image conditioning",
source="xinsir/controlNet-tile-sdxl-1.0",
description="ControlNet weights trained on sdxl-1.0 with tiled image conditioning",
type=ModelType.ControlNet,
),
# endregion

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@ -7,11 +7,9 @@ from invokeai.backend.stable_diffusion.diffusers_pipeline import ( # noqa: F401
StableDiffusionGeneratorPipeline,
)
from invokeai.backend.stable_diffusion.diffusion import InvokeAIDiffuserComponent # noqa: F401
from invokeai.backend.stable_diffusion.seamless import set_seamless # noqa: F401
__all__ = [
"PipelineIntermediateState",
"StableDiffusionGeneratorPipeline",
"InvokeAIDiffuserComponent",
"set_seamless",
]

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@ -0,0 +1,120 @@
from __future__ import annotations
from typing import TYPE_CHECKING, Optional
import einops
import torch
from diffusers import UNet2DConditionModel
from invokeai.backend.stable_diffusion.extension_callback_type import ExtensionCallbackType
from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase, callback
if TYPE_CHECKING:
from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext
class InpaintExt(ExtensionBase):
"""An extension for inpainting with non-inpainting models. See `InpaintModelExt` for inpainting with inpainting
models.
"""
def __init__(
self,
mask: torch.Tensor,
is_gradient_mask: bool,
):
"""Initialize InpaintExt.
Args:
mask (torch.Tensor): The inpainting mask. Shape: (1, 1, latent_height, latent_width). Values are
expected to be in the range [0, 1]. A value of 1 means that the corresponding 'pixel' should not be
inpainted.
is_gradient_mask (bool): If True, mask is interpreted as a gradient mask meaning that the mask values range
from 0 to 1. If False, mask is interpreted as binary mask meaning that the mask values are either 0 or
1.
"""
super().__init__()
self._mask = mask
self._is_gradient_mask = is_gradient_mask
# Noise, which used to noisify unmasked part of image
# if noise provided to context, then it will be used
# if no noise provided, then noise will be generated based on seed
self._noise: Optional[torch.Tensor] = None
@staticmethod
def _is_normal_model(unet: UNet2DConditionModel):
"""Checks if the provided UNet belongs to a regular model.
The `in_channels` of a UNet vary depending on model type:
- normal - 4
- depth - 5
- inpaint - 9
"""
return unet.conv_in.in_channels == 4
def _apply_mask(self, ctx: DenoiseContext, latents: torch.Tensor, t: torch.Tensor) -> torch.Tensor:
batch_size = latents.size(0)
mask = einops.repeat(self._mask, "b c h w -> (repeat b) c h w", repeat=batch_size)
if t.dim() == 0:
# some schedulers expect t to be one-dimensional.
# TODO: file diffusers bug about inconsistency?
t = einops.repeat(t, "-> batch", batch=batch_size)
# Noise shouldn't be re-randomized between steps here. The multistep schedulers
# get very confused about what is happening from step to step when we do that.
mask_latents = ctx.scheduler.add_noise(ctx.inputs.orig_latents, self._noise, t)
# TODO: Do we need to also apply scheduler.scale_model_input? Or is add_noise appropriately scaled already?
# mask_latents = self.scheduler.scale_model_input(mask_latents, t)
mask_latents = einops.repeat(mask_latents, "b c h w -> (repeat b) c h w", repeat=batch_size)
if self._is_gradient_mask:
threshold = (t.item()) / ctx.scheduler.config.num_train_timesteps
mask_bool = mask < 1 - threshold
masked_input = torch.where(mask_bool, latents, mask_latents)
else:
masked_input = torch.lerp(latents, mask_latents.to(dtype=latents.dtype), mask.to(dtype=latents.dtype))
return masked_input
@callback(ExtensionCallbackType.PRE_DENOISE_LOOP)
def init_tensors(self, ctx: DenoiseContext):
if not self._is_normal_model(ctx.unet):
raise ValueError(
"InpaintExt should be used only on normal (non-inpainting) models. This could be caused by an "
"inpainting model that was incorrectly marked as a non-inpainting model. In some cases, this can be "
"fixed by removing and re-adding the model (so that it gets re-probed)."
)
self._mask = self._mask.to(device=ctx.latents.device, dtype=ctx.latents.dtype)
self._noise = ctx.inputs.noise
# 'noise' might be None if the latents have already been noised (e.g. when running the SDXL refiner).
# We still need noise for inpainting, so we generate it from the seed here.
if self._noise is None:
self._noise = torch.randn(
ctx.latents.shape,
dtype=torch.float32,
device="cpu",
generator=torch.Generator(device="cpu").manual_seed(ctx.seed),
).to(device=ctx.latents.device, dtype=ctx.latents.dtype)
# Use negative order to make extensions with default order work with patched latents
@callback(ExtensionCallbackType.PRE_STEP, order=-100)
def apply_mask_to_initial_latents(self, ctx: DenoiseContext):
ctx.latents = self._apply_mask(ctx, ctx.latents, ctx.timestep)
# TODO: redo this with preview events rewrite
# Use negative order to make extensions with default order work with patched latents
@callback(ExtensionCallbackType.POST_STEP, order=-100)
def apply_mask_to_step_output(self, ctx: DenoiseContext):
timestep = ctx.scheduler.timesteps[-1]
if hasattr(ctx.step_output, "denoised"):
ctx.step_output.denoised = self._apply_mask(ctx, ctx.step_output.denoised, timestep)
elif hasattr(ctx.step_output, "pred_original_sample"):
ctx.step_output.pred_original_sample = self._apply_mask(ctx, ctx.step_output.pred_original_sample, timestep)
else:
ctx.step_output.pred_original_sample = self._apply_mask(ctx, ctx.step_output.prev_sample, timestep)
# Restore unmasked part after the last step is completed
@callback(ExtensionCallbackType.POST_DENOISE_LOOP)
def restore_unmasked(self, ctx: DenoiseContext):
if self._is_gradient_mask:
ctx.latents = torch.where(self._mask < 1, ctx.latents, ctx.inputs.orig_latents)
else:
ctx.latents = torch.lerp(ctx.latents, ctx.inputs.orig_latents, self._mask)

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@ -0,0 +1,88 @@
from __future__ import annotations
from typing import TYPE_CHECKING, Optional
import torch
from diffusers import UNet2DConditionModel
from invokeai.backend.stable_diffusion.extension_callback_type import ExtensionCallbackType
from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase, callback
if TYPE_CHECKING:
from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext
class InpaintModelExt(ExtensionBase):
"""An extension for inpainting with inpainting models. See `InpaintExt` for inpainting with non-inpainting
models.
"""
def __init__(
self,
mask: Optional[torch.Tensor],
masked_latents: Optional[torch.Tensor],
is_gradient_mask: bool,
):
"""Initialize InpaintModelExt.
Args:
mask (Optional[torch.Tensor]): The inpainting mask. Shape: (1, 1, latent_height, latent_width). Values are
expected to be in the range [0, 1]. A value of 1 means that the corresponding 'pixel' should not be
inpainted.
masked_latents (Optional[torch.Tensor]): Latents of initial image, with masked out by black color inpainted area.
If mask provided, then too should be provided. Shape: (1, 1, latent_height, latent_width)
is_gradient_mask (bool): If True, mask is interpreted as a gradient mask meaning that the mask values range
from 0 to 1. If False, mask is interpreted as binary mask meaning that the mask values are either 0 or
1.
"""
super().__init__()
if mask is not None and masked_latents is None:
raise ValueError("Source image required for inpaint mask when inpaint model used!")
# Inverse mask, because inpaint models treat mask as: 0 - remain same, 1 - inpaint
self._mask = None
if mask is not None:
self._mask = 1 - mask
self._masked_latents = masked_latents
self._is_gradient_mask = is_gradient_mask
@staticmethod
def _is_inpaint_model(unet: UNet2DConditionModel):
"""Checks if the provided UNet belongs to a regular model.
The `in_channels` of a UNet vary depending on model type:
- normal - 4
- depth - 5
- inpaint - 9
"""
return unet.conv_in.in_channels == 9
@callback(ExtensionCallbackType.PRE_DENOISE_LOOP)
def init_tensors(self, ctx: DenoiseContext):
if not self._is_inpaint_model(ctx.unet):
raise ValueError("InpaintModelExt should be used only on inpaint models!")
if self._mask is None:
self._mask = torch.ones_like(ctx.latents[:1, :1])
self._mask = self._mask.to(device=ctx.latents.device, dtype=ctx.latents.dtype)
if self._masked_latents is None:
self._masked_latents = torch.zeros_like(ctx.latents[:1])
self._masked_latents = self._masked_latents.to(device=ctx.latents.device, dtype=ctx.latents.dtype)
# Do last so that other extensions works with normal latents
@callback(ExtensionCallbackType.PRE_UNET, order=1000)
def append_inpaint_layers(self, ctx: DenoiseContext):
batch_size = ctx.unet_kwargs.sample.shape[0]
b_mask = torch.cat([self._mask] * batch_size)
b_masked_latents = torch.cat([self._masked_latents] * batch_size)
ctx.unet_kwargs.sample = torch.cat(
[ctx.unet_kwargs.sample, b_mask, b_masked_latents],
dim=1,
)
# Restore unmasked part as inpaint model can change unmasked part slightly
@callback(ExtensionCallbackType.POST_DENOISE_LOOP)
def restore_unmasked(self, ctx: DenoiseContext):
if self._is_gradient_mask:
ctx.latents = torch.where(self._mask > 0, ctx.latents, ctx.inputs.orig_latents)
else:
ctx.latents = torch.lerp(ctx.inputs.orig_latents, ctx.latents, self._mask)

View File

@ -0,0 +1,71 @@
from __future__ import annotations
from contextlib import contextmanager
from typing import Callable, Dict, List, Optional, Tuple
import torch
import torch.nn as nn
from diffusers import UNet2DConditionModel
from diffusers.models.lora import LoRACompatibleConv
from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase
class SeamlessExt(ExtensionBase):
def __init__(
self,
seamless_axes: List[str],
):
super().__init__()
self._seamless_axes = seamless_axes
@contextmanager
def patch_unet(self, unet: UNet2DConditionModel, cached_weights: Optional[Dict[str, torch.Tensor]] = None):
with self.static_patch_model(
model=unet,
seamless_axes=self._seamless_axes,
):
yield
@staticmethod
@contextmanager
def static_patch_model(
model: torch.nn.Module,
seamless_axes: List[str],
):
if not seamless_axes:
yield
return
x_mode = "circular" if "x" in seamless_axes else "constant"
y_mode = "circular" if "y" in seamless_axes else "constant"
# override conv_forward
# https://github.com/huggingface/diffusers/issues/556#issuecomment-1993287019
def _conv_forward_asymmetric(
self, input: torch.Tensor, weight: torch.Tensor, bias: Optional[torch.Tensor] = None
):
self.paddingX = (self._reversed_padding_repeated_twice[0], self._reversed_padding_repeated_twice[1], 0, 0)
self.paddingY = (0, 0, self._reversed_padding_repeated_twice[2], self._reversed_padding_repeated_twice[3])
working = torch.nn.functional.pad(input, self.paddingX, mode=x_mode)
working = torch.nn.functional.pad(working, self.paddingY, mode=y_mode)
return torch.nn.functional.conv2d(
working, weight, bias, self.stride, torch.nn.modules.utils._pair(0), self.dilation, self.groups
)
original_layers: List[Tuple[nn.Conv2d, Callable]] = []
try:
for layer in model.modules():
if not isinstance(layer, torch.nn.Conv2d):
continue
if isinstance(layer, LoRACompatibleConv) and layer.lora_layer is None:
layer.lora_layer = lambda *x: 0
original_layers.append((layer, layer._conv_forward))
layer._conv_forward = _conv_forward_asymmetric.__get__(layer, torch.nn.Conv2d)
yield
finally:
for layer, orig_conv_forward in original_layers:
layer._conv_forward = orig_conv_forward

View File

@ -0,0 +1,120 @@
from __future__ import annotations
import math
from typing import TYPE_CHECKING, List, Optional, Union
import torch
from diffusers import T2IAdapter
from PIL.Image import Image
from invokeai.app.util.controlnet_utils import prepare_control_image
from invokeai.backend.model_manager import BaseModelType
from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningMode
from invokeai.backend.stable_diffusion.extension_callback_type import ExtensionCallbackType
from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase, callback
if TYPE_CHECKING:
from invokeai.app.invocations.model import ModelIdentifierField
from invokeai.app.services.shared.invocation_context import InvocationContext
from invokeai.app.util.controlnet_utils import CONTROLNET_RESIZE_VALUES
from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext
class T2IAdapterExt(ExtensionBase):
def __init__(
self,
node_context: InvocationContext,
model_id: ModelIdentifierField,
image: Image,
weight: Union[float, List[float]],
begin_step_percent: float,
end_step_percent: float,
resize_mode: CONTROLNET_RESIZE_VALUES,
):
super().__init__()
self._node_context = node_context
self._model_id = model_id
self._image = image
self._weight = weight
self._resize_mode = resize_mode
self._begin_step_percent = begin_step_percent
self._end_step_percent = end_step_percent
self._adapter_state: Optional[List[torch.Tensor]] = None
# The max_unet_downscale is the maximum amount that the UNet model downscales the latent image internally.
model_config = self._node_context.models.get_config(self._model_id.key)
if model_config.base == BaseModelType.StableDiffusion1:
self._max_unet_downscale = 8
elif model_config.base == BaseModelType.StableDiffusionXL:
self._max_unet_downscale = 4
else:
raise ValueError(f"Unexpected T2I-Adapter base model type: '{model_config.base}'.")
@callback(ExtensionCallbackType.SETUP)
def setup(self, ctx: DenoiseContext):
t2i_model: T2IAdapter
with self._node_context.models.load(self._model_id) as t2i_model:
_, _, latents_height, latents_width = ctx.inputs.orig_latents.shape
self._adapter_state = self._run_model(
model=t2i_model,
image=self._image,
latents_height=latents_height,
latents_width=latents_width,
)
def _run_model(
self,
model: T2IAdapter,
image: Image,
latents_height: int,
latents_width: int,
):
# Resize the T2I-Adapter input image.
# We select the resize dimensions so that after the T2I-Adapter's total_downscale_factor is applied, the
# result will match the latent image's dimensions after max_unet_downscale is applied.
input_height = latents_height // self._max_unet_downscale * model.total_downscale_factor
input_width = latents_width // self._max_unet_downscale * model.total_downscale_factor
# Note: We have hard-coded `do_classifier_free_guidance=False`. This is because we only want to prepare
# a single image. If CFG is enabled, we will duplicate the resultant tensor after applying the
# T2I-Adapter model.
#
# Note: We re-use the `prepare_control_image(...)` from ControlNet for T2I-Adapter, because it has many
# of the same requirements (e.g. preserving binary masks during resize).
t2i_image = prepare_control_image(
image=image,
do_classifier_free_guidance=False,
width=input_width,
height=input_height,
num_channels=model.config["in_channels"],
device=model.device,
dtype=model.dtype,
resize_mode=self._resize_mode,
)
return model(t2i_image)
@callback(ExtensionCallbackType.PRE_UNET)
def pre_unet_step(self, ctx: DenoiseContext):
# skip if model not active in current step
total_steps = len(ctx.inputs.timesteps)
first_step = math.floor(self._begin_step_percent * total_steps)
last_step = math.ceil(self._end_step_percent * total_steps)
if ctx.step_index < first_step or ctx.step_index > last_step:
return
weight = self._weight
if isinstance(weight, list):
weight = weight[ctx.step_index]
adapter_state = self._adapter_state
if ctx.conditioning_mode == ConditioningMode.Both:
adapter_state = [torch.cat([v] * 2) for v in adapter_state]
if ctx.unet_kwargs.down_intrablock_additional_residuals is None:
ctx.unet_kwargs.down_intrablock_additional_residuals = [v * weight for v in adapter_state]
else:
for i, value in enumerate(adapter_state):
ctx.unet_kwargs.down_intrablock_additional_residuals[i] += value * weight

View File

@ -1,51 +0,0 @@
from contextlib import contextmanager
from typing import Callable, List, Optional, Tuple, Union
import torch
import torch.nn as nn
from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny
from diffusers.models.lora import LoRACompatibleConv
from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
@contextmanager
def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL, AutoencoderTiny], seamless_axes: List[str]):
if not seamless_axes:
yield
return
# override conv_forward
# https://github.com/huggingface/diffusers/issues/556#issuecomment-1993287019
def _conv_forward_asymmetric(self, input: torch.Tensor, weight: torch.Tensor, bias: Optional[torch.Tensor] = None):
self.paddingX = (self._reversed_padding_repeated_twice[0], self._reversed_padding_repeated_twice[1], 0, 0)
self.paddingY = (0, 0, self._reversed_padding_repeated_twice[2], self._reversed_padding_repeated_twice[3])
working = torch.nn.functional.pad(input, self.paddingX, mode=x_mode)
working = torch.nn.functional.pad(working, self.paddingY, mode=y_mode)
return torch.nn.functional.conv2d(
working, weight, bias, self.stride, torch.nn.modules.utils._pair(0), self.dilation, self.groups
)
original_layers: List[Tuple[nn.Conv2d, Callable]] = []
try:
x_mode = "circular" if "x" in seamless_axes else "constant"
y_mode = "circular" if "y" in seamless_axes else "constant"
conv_layers: List[torch.nn.Conv2d] = []
for module in model.modules():
if isinstance(module, torch.nn.Conv2d):
conv_layers.append(module)
for layer in conv_layers:
if isinstance(layer, LoRACompatibleConv) and layer.lora_layer is None:
layer.lora_layer = lambda *x: 0
original_layers.append((layer, layer._conv_forward))
layer._conv_forward = _conv_forward_asymmetric.__get__(layer, torch.nn.Conv2d)
yield
finally:
for layer, orig_conv_forward in original_layers:
layer._conv_forward = orig_conv_forward

View File

@ -31,7 +31,8 @@
"deleteBoard": "Delete Board",
"deleteBoardAndImages": "Delete Board and Images",
"deleteBoardOnly": "Delete Board Only",
"deletedBoardsCannotbeRestored": "Deleted boards cannot be restored",
"deletedBoardsCannotbeRestored": "Deleted boards cannot be restored. Selecting 'Delete Board Only' will move images to an uncategorized state.",
"deletedPrivateBoardsCannotbeRestored": "Deleted boards cannot be restored. Selecting 'Delete Board Only' will move images to a private uncategorized state for the image's creator.",
"hideBoards": "Hide Boards",
"loading": "Loading...",
"menuItemAutoAdd": "Auto-add to this Board",
@ -105,6 +106,7 @@
"negativePrompt": "Negative Prompt",
"discordLabel": "Discord",
"dontAskMeAgain": "Don't ask me again",
"dontShowMeThese": "Don't show me these",
"editor": "Editor",
"error": "Error",
"file": "File",
@ -1099,6 +1101,8 @@
"displayInProgress": "Display Progress Images",
"enableImageDebugging": "Enable Image Debugging",
"enableInformationalPopovers": "Enable Informational Popovers",
"informationalPopoversDisabled": "Informational Popovers Disabled",
"informationalPopoversDisabledDesc": "Informational popovers have been disabled. Enable them in Settings.",
"enableInvisibleWatermark": "Enable Invisible Watermark",
"enableNSFWChecker": "Enable NSFW Checker",
"general": "General",
@ -1506,6 +1510,30 @@
"seamlessTilingYAxis": {
"heading": "Seamless Tiling Y Axis",
"paragraphs": ["Seamlessly tile an image along the vertical axis."]
},
"upscaleModel": {
"heading": "Upscale Model",
"paragraphs": [
"The upscale model scales the image to the output size before details are added. Any supported upscale model may be used, but some are specialized for different kinds of images, like photos or line drawings."
]
},
"scale": {
"heading": "Scale",
"paragraphs": [
"Scale controls the output image size, and is based on a multiple of the input image resolution. For example a 2x upscale on a 1024x1024 image would produce a 2048 x 2048 output."
]
},
"creativity": {
"heading": "Creativity",
"paragraphs": [
"Creativity controls the amount of freedom granted to the model when adding details. Low creativity stays close to the original image, while high creativity allows for more change. When using a prompt, high creativity increases the influence of the prompt."
]
},
"structure": {
"heading": "Structure",
"paragraphs": [
"Structure controls how closely the output image will keep to the layout of the original. Low structure allows major changes, while high structure strictly maintains the original composition and layout."
]
}
},
"unifiedCanvas": {

View File

@ -10,32 +10,32 @@ import {
import { boardsApi } from 'services/api/endpoints/boards';
import { imagesApi } from 'services/api/endpoints/images';
// Type inference doesn't work for this if you inline it in the listener for some reason
const matchAnyBoardDeleted = isAnyOf(
imagesApi.endpoints.deleteBoard.matchFulfilled,
imagesApi.endpoints.deleteBoardAndImages.matchFulfilled
);
export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartListening) => {
/**
* The auto-add board shouldn't be set to an archived board or deleted board. When we archive a board, delete
* a board, or change a the archived board visibility flag, we may need to reset the auto-add board.
*/
startAppListening({
matcher: isAnyOf(
// If a board is deleted, we'll need to reset the auto-add board
imagesApi.endpoints.deleteBoard.matchFulfilled,
imagesApi.endpoints.deleteBoardAndImages.matchFulfilled
),
matcher: matchAnyBoardDeleted,
effect: async (action, { dispatch, getState }) => {
const state = getState();
const queryArgs = selectListBoardsQueryArgs(state);
const queryResult = boardsApi.endpoints.listAllBoards.select(queryArgs)(state);
const deletedBoardId = action.meta.arg.originalArgs;
const { autoAddBoardId, selectedBoardId } = state.gallery;
if (!queryResult.data) {
return;
}
if (!queryResult.data.find((board) => board.board_id === selectedBoardId)) {
// If the deleted board was currently selected, we should reset the selected board to uncategorized
if (deletedBoardId === selectedBoardId) {
dispatch(boardIdSelected({ boardId: 'none' }));
dispatch(galleryViewChanged('images'));
}
if (!queryResult.data.find((board) => board.board_id === autoAddBoardId)) {
// If the deleted board was selected for auto-add, we should reset the auto-add board to uncategorized
if (deletedBoardId === autoAddBoardId) {
dispatch(autoAddBoardIdChanged('none'));
}
},
@ -46,14 +46,8 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
matcher: boardsApi.endpoints.updateBoard.matchFulfilled,
effect: async (action, { dispatch, getState }) => {
const state = getState();
const queryArgs = selectListBoardsQueryArgs(state);
const queryResult = boardsApi.endpoints.listAllBoards.select(queryArgs)(state);
const { shouldShowArchivedBoards } = state.gallery;
if (!queryResult.data) {
return;
}
const wasArchived = action.meta.arg.originalArgs.changes.archived === true;
if (wasArchived && !shouldShowArchivedBoards) {
@ -71,7 +65,7 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
const shouldShowArchivedBoards = action.payload;
// We only need to take action if we have just hidden archived boards.
if (!shouldShowArchivedBoards) {
if (shouldShowArchivedBoards) {
return;
}
@ -86,14 +80,16 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
// Handle the case where selected board is archived
const selectedBoard = queryResult.data.find((b) => b.board_id === selectedBoardId);
if (selectedBoard && selectedBoard.archived) {
if (!selectedBoard || selectedBoard.archived) {
// If we can't find the selected board or it's archived, we should reset the selected board to uncategorized
dispatch(boardIdSelected({ boardId: 'none' }));
dispatch(galleryViewChanged('images'));
}
// Handle the case where auto-add board is archived
const autoAddBoard = queryResult.data.find((b) => b.board_id === autoAddBoardId);
if (autoAddBoard && autoAddBoard.archived) {
if (!autoAddBoard || autoAddBoard.archived) {
// If we can't find the auto-add board or it's archived, we should reset the selected board to uncategorized
dispatch(autoAddBoardIdChanged('none'));
}
},

View File

@ -10,9 +10,12 @@ import {
PopoverContent,
PopoverTrigger,
Portal,
Spacer,
Text,
} from '@invoke-ai/ui-library';
import { useAppSelector } from 'app/store/storeHooks';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { setShouldEnableInformationalPopovers } from 'features/system/store/systemSlice';
import { toast } from 'features/toast/toast';
import { merge, omit } from 'lodash-es';
import type { ReactElement } from 'react';
import { memo, useCallback, useMemo } from 'react';
@ -71,7 +74,7 @@ type ContentProps = {
const Content = ({ data, feature }: ContentProps) => {
const { t } = useTranslation();
const dispatch = useAppDispatch();
const heading = useMemo<string | undefined>(() => t(`popovers.${feature}.heading`), [feature, t]);
const paragraphs = useMemo<string[]>(
@ -82,16 +85,25 @@ const Content = ({ data, feature }: ContentProps) => {
[feature, t]
);
const handleClick = useCallback(() => {
const onClickLearnMore = useCallback(() => {
if (!data?.href) {
return;
}
window.open(data.href);
}, [data?.href]);
const onClickDontShowMeThese = useCallback(() => {
dispatch(setShouldEnableInformationalPopovers(false));
toast({
title: t('settings.informationalPopoversDisabled'),
description: t('settings.informationalPopoversDisabledDesc'),
status: 'info',
});
}, [dispatch, t]);
return (
<PopoverContent w={96}>
<PopoverCloseButton />
<PopoverContent maxW={300}>
<PopoverCloseButton top={2} />
<PopoverBody>
<Flex gap={2} flexDirection="column" alignItems="flex-start">
{heading && (
@ -116,20 +128,19 @@ const Content = ({ data, feature }: ContentProps) => {
{paragraphs.map((p) => (
<Text key={p}>{p}</Text>
))}
{data?.href && (
<>
<Divider />
<Button
pt={1}
onClick={handleClick}
leftIcon={<PiArrowSquareOutBold />}
alignSelf="flex-end"
variant="link"
>
<Divider />
<Flex alignItems="center" justifyContent="space-between" w="full">
<Button onClick={onClickDontShowMeThese} variant="link" size="sm">
{t('common.dontShowMeThese')}
</Button>
<Spacer />
{data?.href && (
<Button onClick={onClickLearnMore} leftIcon={<PiArrowSquareOutBold />} variant="link" size="sm">
{t('common.learnMore') ?? heading}
</Button>
</>
)}
)}
</Flex>
</Flex>
</PopoverBody>
</PopoverContent>

View File

@ -53,7 +53,11 @@ export type Feature =
| 'refinerCfgScale'
| 'scaleBeforeProcessing'
| 'seamlessTilingXAxis'
| 'seamlessTilingYAxis';
| 'seamlessTilingYAxis'
| 'upscaleModel'
| 'scale'
| 'creativity'
| 'structure';
export type PopoverData = PopoverProps & {
image?: string;

View File

@ -120,7 +120,11 @@ const DeleteBoardModal = (props: Props) => {
bottomMessage={t('boards.bottomMessage')}
/>
)}
<Text>{t('boards.deletedBoardsCannotbeRestored')}</Text>
<Text>
{boardToDelete.is_private
? t('boards.deletedPrivateBoardsCannotbeRestored')
: t('boards.deletedBoardsCannotbeRestored')}
</Text>
<Text>
{canRestoreDeletedImagesFromBin ? t('gallery.deleteImageBin') : t('gallery.deleteImagePermanent')}
</Text>

View File

@ -1,15 +1,10 @@
import { skipToken } from '@reduxjs/toolkit/query';
import { isNil } from 'lodash-es';
import { useMemo } from 'react';
import { useGetModelConfigWithTypeGuard } from 'services/api/hooks/useGetModelConfigWithTypeGuard';
import { isControlNetOrT2IAdapterModelConfig } from 'services/api/types';
export const useControlNetOrT2IAdapterDefaultSettings = (modelKey?: string | null) => {
const { modelConfig, isLoading } = useGetModelConfigWithTypeGuard(
modelKey ?? skipToken,
isControlNetOrT2IAdapterModelConfig
);
import type { ControlNetModelConfig, T2IAdapterModelConfig } from 'services/api/types';
export const useControlNetOrT2IAdapterDefaultSettings = (
modelConfig: ControlNetModelConfig | T2IAdapterModelConfig
) => {
const defaultSettingsDefaults = useMemo(() => {
return {
preprocessor: {
@ -19,5 +14,5 @@ export const useControlNetOrT2IAdapterDefaultSettings = (modelKey?: string | nul
};
}, [modelConfig?.default_settings]);
return { defaultSettingsDefaults, isLoading };
return defaultSettingsDefaults;
};

View File

@ -1,12 +1,9 @@
import { skipToken } from '@reduxjs/toolkit/query';
import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
import { useAppSelector } from 'app/store/storeHooks';
import { getOptimalDimension } from 'features/parameters/util/optimalDimension';
import { selectConfigSlice } from 'features/system/store/configSlice';
import { isNil } from 'lodash-es';
import { useMemo } from 'react';
import { useGetModelConfigWithTypeGuard } from 'services/api/hooks/useGetModelConfigWithTypeGuard';
import { isNonRefinerMainModelConfig } from 'services/api/types';
import type { MainModelConfig } from 'services/api/types';
const initialStatesSelector = createMemoizedSelector(selectConfigSlice, (config) => {
const { steps, guidance, scheduler, cfgRescaleMultiplier, vaePrecision, width, height } = config.sd;
@ -22,9 +19,7 @@ const initialStatesSelector = createMemoizedSelector(selectConfigSlice, (config)
};
});
export const useMainModelDefaultSettings = (modelKey?: string | null) => {
const { modelConfig, isLoading } = useGetModelConfigWithTypeGuard(modelKey ?? skipToken, isNonRefinerMainModelConfig);
export const useMainModelDefaultSettings = (modelConfig: MainModelConfig) => {
const {
initialSteps,
initialCfg,
@ -81,5 +76,5 @@ export const useMainModelDefaultSettings = (modelKey?: string | null) => {
initialHeight,
]);
return { defaultSettingsDefaults, isLoading, optimalDimension: getOptimalDimension(modelConfig) };
return defaultSettingsDefaults;
};

View File

@ -1,6 +1,6 @@
import type { PayloadAction } from '@reduxjs/toolkit';
import { createSlice } from '@reduxjs/toolkit';
import type { PersistConfig } from 'app/store/store';
import type { PersistConfig, RootState } from 'app/store/store';
import type { ModelType } from 'services/api/types';
export type FilterableModelType = Exclude<ModelType, 'onnx' | 'clip_vision'> | 'refiner';
@ -50,6 +50,8 @@ export const modelManagerV2Slice = createSlice({
export const { setSelectedModelKey, setSearchTerm, setFilteredModelType, setSelectedModelMode, setScanPath } =
modelManagerV2Slice.actions;
export const selectModelManagerV2Slice = (state: RootState) => state.modelmanagerV2;
/* eslint-disable-next-line @typescript-eslint/no-explicit-any */
const migrateModelManagerState = (state: any): any => {
if (!('_version' in state)) {

View File

@ -1,13 +1,13 @@
import { Button, Flex, FormControl, FormErrorMessage, FormHelperText, FormLabel, Input } from '@invoke-ai/ui-library';
import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
import type { ChangeEventHandler } from 'react';
import { useCallback, useState } from 'react';
import { memo, useCallback, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { useLazyGetHuggingFaceModelsQuery } from 'services/api/endpoints/models';
import { HuggingFaceResults } from './HuggingFaceResults';
export const HuggingFaceForm = () => {
export const HuggingFaceForm = memo(() => {
const [huggingFaceRepo, setHuggingFaceRepo] = useState('');
const [displayResults, setDisplayResults] = useState(false);
const [errorMessage, setErrorMessage] = useState('');
@ -66,4 +66,6 @@ export const HuggingFaceForm = () => {
{data && data.urls && displayResults && <HuggingFaceResults results={data.urls} />}
</Flex>
);
};
});
HuggingFaceForm.displayName = 'HuggingFaceForm';

View File

@ -1,13 +1,13 @@
import { Flex, IconButton, Text } from '@invoke-ai/ui-library';
import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
import { useCallback } from 'react';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { PiPlusBold } from 'react-icons/pi';
type Props = {
result: string;
};
export const HuggingFaceResultItem = ({ result }: Props) => {
export const HuggingFaceResultItem = memo(({ result }: Props) => {
const { t } = useTranslation();
const [installModel] = useInstallModel();
@ -27,4 +27,6 @@ export const HuggingFaceResultItem = ({ result }: Props) => {
<IconButton aria-label={t('modelManager.install')} icon={<PiPlusBold />} onClick={onClick} size="sm" />
</Flex>
);
};
});
HuggingFaceResultItem.displayName = 'HuggingFaceResultItem';

View File

@ -11,7 +11,7 @@ import {
import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
import type { ChangeEventHandler } from 'react';
import { useCallback, useMemo, useState } from 'react';
import { memo, useCallback, useMemo, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { PiXBold } from 'react-icons/pi';
@ -21,7 +21,7 @@ type HuggingFaceResultsProps = {
results: string[];
};
export const HuggingFaceResults = ({ results }: HuggingFaceResultsProps) => {
export const HuggingFaceResults = memo(({ results }: HuggingFaceResultsProps) => {
const { t } = useTranslation();
const [searchTerm, setSearchTerm] = useState('');
@ -93,4 +93,6 @@ export const HuggingFaceResults = ({ results }: HuggingFaceResultsProps) => {
</Flex>
</>
);
};
});
HuggingFaceResults.displayName = 'HuggingFaceResults';

View File

@ -1,7 +1,7 @@
import { Button, Checkbox, Flex, FormControl, FormHelperText, FormLabel, Input } from '@invoke-ai/ui-library';
import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
import { t } from 'i18next';
import { useCallback } from 'react';
import { memo, useCallback } from 'react';
import type { SubmitHandler } from 'react-hook-form';
import { useForm } from 'react-hook-form';
@ -10,7 +10,7 @@ type SimpleImportModelConfig = {
inplace: boolean;
};
export const InstallModelForm = () => {
export const InstallModelForm = memo(() => {
const [installModel, { isLoading }] = useInstallModel();
const { register, handleSubmit, formState, reset } = useForm<SimpleImportModelConfig>({
@ -74,4 +74,6 @@ export const InstallModelForm = () => {
</Flex>
</form>
);
};
});
InstallModelForm.displayName = 'InstallModelForm';

View File

@ -2,12 +2,12 @@ import { Box, Button, Flex, Heading } from '@invoke-ai/ui-library';
import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import { useListModelInstallsQuery, usePruneCompletedModelInstallsMutation } from 'services/api/endpoints/models';
import { ModelInstallQueueItem } from './ModelInstallQueueItem';
export const ModelInstallQueue = () => {
export const ModelInstallQueue = memo(() => {
const { data } = useListModelInstallsQuery();
const [_pruneCompletedModelInstalls] = usePruneCompletedModelInstallsMutation();
@ -61,4 +61,6 @@ export const ModelInstallQueue = () => {
</Box>
</Flex>
);
};
});
ModelInstallQueue.displayName = 'ModelInstallQueue';

View File

@ -2,7 +2,7 @@ import { Flex, IconButton, Progress, Text, Tooltip } from '@invoke-ai/ui-library
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { isNil } from 'lodash-es';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import { PiXBold } from 'react-icons/pi';
import { useCancelModelInstallMutation } from 'services/api/endpoints/models';
import type { ModelInstallJob } from 'services/api/types';
@ -25,7 +25,7 @@ const formatBytes = (bytes: number) => {
return `${bytes.toFixed(2)} ${units[i]}`;
};
export const ModelInstallQueueItem = (props: ModelListItemProps) => {
export const ModelInstallQueueItem = memo((props: ModelListItemProps) => {
const { installJob } = props;
const [deleteImportModel] = useCancelModelInstallMutation();
@ -124,7 +124,9 @@ export const ModelInstallQueueItem = (props: ModelListItemProps) => {
/>
</Flex>
);
};
});
ModelInstallQueueItem.displayName = 'ModelInstallQueueItem';
type TooltipLabelProps = {
installJob: ModelInstallJob;
@ -132,7 +134,7 @@ type TooltipLabelProps = {
source: string;
};
const TooltipLabel = ({ name, source, installJob }: TooltipLabelProps) => {
const TooltipLabel = memo(({ name, source, installJob }: TooltipLabelProps) => {
const progressString = useMemo(() => {
if (installJob.status !== 'downloading' || installJob.bytes === undefined || installJob.total_bytes === undefined) {
return '';
@ -156,4 +158,6 @@ const TooltipLabel = ({ name, source, installJob }: TooltipLabelProps) => {
)}
</>
);
};
});
TooltipLabel.displayName = 'TooltipLabel';

View File

@ -2,13 +2,13 @@ import { Button, Flex, FormControl, FormErrorMessage, FormHelperText, FormLabel,
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { setScanPath } from 'features/modelManagerV2/store/modelManagerV2Slice';
import type { ChangeEventHandler } from 'react';
import { useCallback, useState } from 'react';
import { memo, useCallback, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { useLazyScanFolderQuery } from 'services/api/endpoints/models';
import { ScanModelsResults } from './ScanFolderResults';
export const ScanModelsForm = () => {
export const ScanModelsForm = memo(() => {
const scanPath = useAppSelector((state) => state.modelmanagerV2.scanPath);
const dispatch = useAppDispatch();
const [errorMessage, setErrorMessage] = useState('');
@ -56,4 +56,6 @@ export const ScanModelsForm = () => {
{data && <ScanModelsResults results={data} />}
</Flex>
);
};
});
ScanModelsForm.displayName = 'ScanModelsForm';

View File

@ -1,5 +1,5 @@
import { Badge, Box, Flex, IconButton, Text } from '@invoke-ai/ui-library';
import { useCallback } from 'react';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { PiPlusBold } from 'react-icons/pi';
import type { ScanFolderResponse } from 'services/api/endpoints/models';
@ -8,7 +8,7 @@ type Props = {
result: ScanFolderResponse[number];
installModel: (source: string) => void;
};
export const ScanModelResultItem = ({ result, installModel }: Props) => {
export const ScanModelResultItem = memo(({ result, installModel }: Props) => {
const { t } = useTranslation();
const handleInstall = useCallback(() => {
@ -30,4 +30,6 @@ export const ScanModelResultItem = ({ result, installModel }: Props) => {
</Box>
</Flex>
);
};
});
ScanModelResultItem.displayName = 'ScanModelResultItem';

View File

@ -14,7 +14,7 @@ import {
import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
import type { ChangeEvent, ChangeEventHandler } from 'react';
import { useCallback, useMemo, useState } from 'react';
import { memo, useCallback, useMemo, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { PiXBold } from 'react-icons/pi';
import type { ScanFolderResponse } from 'services/api/endpoints/models';
@ -25,7 +25,7 @@ type ScanModelResultsProps = {
results: ScanFolderResponse;
};
export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
export const ScanModelsResults = memo(({ results }: ScanModelResultsProps) => {
const { t } = useTranslation();
const [searchTerm, setSearchTerm] = useState('');
const [inplace, setInplace] = useState(true);
@ -116,4 +116,6 @@ export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
</Flex>
</>
);
};
});
ScanModelsResults.displayName = 'ScanModelsResults';

View File

@ -1,7 +1,7 @@
import { Badge, Box, Flex, IconButton, Text } from '@invoke-ai/ui-library';
import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
import ModelBaseBadge from 'features/modelManagerV2/subpanels/ModelManagerPanel/ModelBaseBadge';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import { useTranslation } from 'react-i18next';
import { PiPlusBold } from 'react-icons/pi';
import type { GetStarterModelsResponse } from 'services/api/endpoints/models';
@ -9,7 +9,7 @@ import type { GetStarterModelsResponse } from 'services/api/endpoints/models';
type Props = {
result: GetStarterModelsResponse[number];
};
export const StarterModelsResultItem = ({ result }: Props) => {
export const StarterModelsResultItem = memo(({ result }: Props) => {
const { t } = useTranslation();
const allSources = useMemo(() => {
const _allSources = [{ source: result.source, config: { name: result.name, description: result.description } }];
@ -47,4 +47,6 @@ export const StarterModelsResultItem = ({ result }: Props) => {
</Box>
</Flex>
);
};
});
StarterModelsResultItem.displayName = 'StarterModelsResultItem';

View File

@ -1,10 +1,11 @@
import { Flex } from '@invoke-ai/ui-library';
import { FetchingModelsLoader } from 'features/modelManagerV2/subpanels/ModelManagerPanel/FetchingModelsLoader';
import { memo } from 'react';
import { useGetStarterModelsQuery } from 'services/api/endpoints/models';
import { StarterModelsResults } from './StarterModelsResults';
export const StarterModelsForm = () => {
export const StarterModelsForm = memo(() => {
const { isLoading, data } = useGetStarterModelsQuery();
return (
@ -13,4 +14,6 @@ export const StarterModelsForm = () => {
{data && <StarterModelsResults results={data} />}
</Flex>
);
};
});
StarterModelsForm.displayName = 'StarterModelsForm';

View File

@ -1,7 +1,7 @@
import { Flex, IconButton, Input, InputGroup, InputRightElement } from '@invoke-ai/ui-library';
import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
import type { ChangeEventHandler } from 'react';
import { useCallback, useMemo, useState } from 'react';
import { memo, useCallback, useMemo, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { PiXBold } from 'react-icons/pi';
import type { GetStarterModelsResponse } from 'services/api/endpoints/models';
@ -12,7 +12,7 @@ type StarterModelsResultsProps = {
results: NonNullable<GetStarterModelsResponse>;
};
export const StarterModelsResults = ({ results }: StarterModelsResultsProps) => {
export const StarterModelsResults = memo(({ results }: StarterModelsResultsProps) => {
const { t } = useTranslation();
const [searchTerm, setSearchTerm] = useState('');
@ -79,4 +79,6 @@ export const StarterModelsResults = ({ results }: StarterModelsResultsProps) =>
</Flex>
</Flex>
);
};
});
StarterModelsResults.displayName = 'StarterModelsResults';

View File

@ -2,7 +2,7 @@ import { Box, Flex, Heading, Tab, TabList, TabPanel, TabPanels, Tabs } from '@in
import { useStore } from '@nanostores/react';
import { StarterModelsForm } from 'features/modelManagerV2/subpanels/AddModelPanel/StarterModels/StarterModelsForm';
import { atom } from 'nanostores';
import { useCallback } from 'react';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { HuggingFaceForm } from './AddModelPanel/HuggingFaceFolder/HuggingFaceForm';
@ -12,7 +12,7 @@ import { ScanModelsForm } from './AddModelPanel/ScanFolder/ScanFolderForm';
export const $installModelsTab = atom(0);
export const InstallModels = () => {
export const InstallModels = memo(() => {
const { t } = useTranslation();
const index = useStore($installModelsTab);
const onChange = useCallback((index: number) => {
@ -49,4 +49,6 @@ export const InstallModels = () => {
</Box>
</Flex>
);
};
});
InstallModels.displayName = 'InstallModels';

View File

@ -1,14 +1,14 @@
import { Button, Flex, Heading } from '@invoke-ai/ui-library';
import { useAppDispatch } from 'app/store/storeHooks';
import { setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
import { useCallback } from 'react';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { PiPlusBold } from 'react-icons/pi';
import ModelList from './ModelManagerPanel/ModelList';
import { ModelListNavigation } from './ModelManagerPanel/ModelListNavigation';
export const ModelManager = () => {
export const ModelManager = memo(() => {
const { t } = useTranslation();
const dispatch = useAppDispatch();
const handleClickAddModel = useCallback(() => {
@ -29,4 +29,6 @@ export const ModelManager = () => {
</Flex>
</Flex>
);
};
});
ModelManager.displayName = 'ModelManager';

View File

@ -21,7 +21,8 @@ import { FetchingModelsLoader } from './FetchingModelsLoader';
import { ModelListWrapper } from './ModelListWrapper';
const ModelList = () => {
const { searchTerm, filteredModelType } = useAppSelector((s) => s.modelmanagerV2);
const filteredModelType = useAppSelector((s) => s.modelmanagerV2.filteredModelType);
const searchTerm = useAppSelector((s) => s.modelmanagerV2.searchTerm);
const { t } = useTranslation();
const [mainModels, { isLoading: isLoadingMainModels }] = useMainModels();

View File

@ -1,7 +1,8 @@
import type { SystemStyleObject } from '@invoke-ai/ui-library';
import { ConfirmationAlertDialog, Flex, IconButton, Spacer, Text, useDisclosure } from '@invoke-ai/ui-library';
import { createSelector } from '@reduxjs/toolkit';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
import { selectModelManagerV2Slice, setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
import ModelBaseBadge from 'features/modelManagerV2/subpanels/ModelManagerPanel/ModelBaseBadge';
import ModelFormatBadge from 'features/modelManagerV2/subpanels/ModelManagerPanel/ModelFormatBadge';
import { toast } from 'features/toast/toast';
@ -23,15 +24,21 @@ const sx: SystemStyleObject = {
"&[aria-selected='true']": { bg: 'base.700' },
};
const ModelListItem = (props: ModelListItemProps) => {
const ModelListItem = ({ model }: ModelListItemProps) => {
const { t } = useTranslation();
const dispatch = useAppDispatch();
const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
const selectIsSelected = useMemo(
() =>
createSelector(
selectModelManagerV2Slice,
(modelManagerV2Slice) => modelManagerV2Slice.selectedModelKey === model.key
),
[model.key]
);
const isSelected = useAppSelector(selectIsSelected);
const [deleteModel] = useDeleteModelsMutation();
const { isOpen, onOpen, onClose } = useDisclosure();
const { model } = props;
const handleSelectModel = useCallback(() => {
dispatch(setSelectedModelKey(model.key));
}, [model.key, dispatch]);
@ -43,11 +50,6 @@ const ModelListItem = (props: ModelListItemProps) => {
},
[onOpen]
);
const isSelected = useMemo(() => {
return selectedModelKey === model.key;
}, [selectedModelKey, model.key]);
const handleModelDelete = useCallback(() => {
deleteModel({ key: model.key })
.unwrap()

View File

@ -3,12 +3,12 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { setSearchTerm } from 'features/modelManagerV2/store/modelManagerV2Slice';
import { t } from 'i18next';
import type { ChangeEventHandler } from 'react';
import { useCallback } from 'react';
import { memo, useCallback } from 'react';
import { PiXBold } from 'react-icons/pi';
import { ModelTypeFilter } from './ModelTypeFilter';
export const ModelListNavigation = () => {
export const ModelListNavigation = memo(() => {
const dispatch = useAppDispatch();
const searchTerm = useAppSelector((s) => s.modelmanagerV2.searchTerm);
@ -49,4 +49,6 @@ export const ModelListNavigation = () => {
</InputGroup>
</Flex>
);
};
});
ModelListNavigation.displayName = 'ModelListNavigation';

View File

@ -1,4 +1,5 @@
import { StickyScrollable } from 'features/system/components/StickyScrollable';
import { memo } from 'react';
import type { AnyModelConfig } from 'services/api/types';
import ModelListItem from './ModelListItem';
@ -8,7 +9,7 @@ type ModelListWrapperProps = {
modelList: AnyModelConfig[];
};
export const ModelListWrapper = (props: ModelListWrapperProps) => {
export const ModelListWrapper = memo((props: ModelListWrapperProps) => {
const { title, modelList } = props;
return (
<StickyScrollable title={title} contentSx={{ gap: 1, p: 2 }}>
@ -17,4 +18,6 @@ export const ModelListWrapper = (props: ModelListWrapperProps) => {
))}
</StickyScrollable>
);
};
});
ModelListWrapper.displayName = 'ModelListWrapper';

View File

@ -2,12 +2,12 @@ import { Button, Menu, MenuButton, MenuItem, MenuList } from '@invoke-ai/ui-libr
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import type { FilterableModelType } from 'features/modelManagerV2/store/modelManagerV2Slice';
import { setFilteredModelType } from 'features/modelManagerV2/store/modelManagerV2Slice';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import { useTranslation } from 'react-i18next';
import { PiFunnelBold } from 'react-icons/pi';
import { objectKeys } from 'tsafe';
export const ModelTypeFilter = () => {
export const ModelTypeFilter = memo(() => {
const { t } = useTranslation();
const dispatch = useAppDispatch();
const MODEL_TYPE_LABELS: Record<FilterableModelType, string> = useMemo(
@ -57,4 +57,6 @@ export const ModelTypeFilter = () => {
</MenuList>
</Menu>
);
};
});
ModelTypeFilter.displayName = 'ModelTypeFilter';

View File

@ -1,14 +1,17 @@
import { Box } from '@invoke-ai/ui-library';
import { useAppSelector } from 'app/store/storeHooks';
import { memo } from 'react';
import { InstallModels } from './InstallModels';
import { Model } from './ModelPanel/Model';
export const ModelPane = () => {
export const ModelPane = memo(() => {
const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
return (
<Box layerStyle="first" p={4} borderRadius="base" w="50%" h="full">
{selectedModelKey ? <Model key={selectedModelKey} /> : <InstallModels />}
</Box>
);
};
});
ModelPane.displayName = 'ModelPane';

View File

@ -1,26 +1,28 @@
import { Button, Flex, Heading, SimpleGrid, Text } from '@invoke-ai/ui-library';
import { useAppSelector } from 'app/store/storeHooks';
import { Button, Flex, Heading, SimpleGrid } from '@invoke-ai/ui-library';
import { useControlNetOrT2IAdapterDefaultSettings } from 'features/modelManagerV2/hooks/useControlNetOrT2IAdapterDefaultSettings';
import { DefaultPreprocessor } from 'features/modelManagerV2/subpanels/ModelPanel/ControlNetOrT2IAdapterDefaultSettings/DefaultPreprocessor';
import type { FormField } from 'features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/MainModelDefaultSettings';
import { toast } from 'features/toast/toast';
import { useCallback } from 'react';
import { memo, useCallback } from 'react';
import type { SubmitHandler } from 'react-hook-form';
import { useForm } from 'react-hook-form';
import { useTranslation } from 'react-i18next';
import { PiCheckBold } from 'react-icons/pi';
import { useUpdateModelMutation } from 'services/api/endpoints/models';
import type { ControlNetModelConfig, T2IAdapterModelConfig } from 'services/api/types';
export type ControlNetOrT2IAdapterDefaultSettingsFormData = {
preprocessor: FormField<string>;
};
export const ControlNetOrT2IAdapterDefaultSettings = () => {
const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
type Props = {
modelConfig: ControlNetModelConfig | T2IAdapterModelConfig;
};
export const ControlNetOrT2IAdapterDefaultSettings = memo(({ modelConfig }: Props) => {
const { t } = useTranslation();
const { defaultSettingsDefaults, isLoading: isLoadingDefaultSettings } =
useControlNetOrT2IAdapterDefaultSettings(selectedModelKey);
const defaultSettingsDefaults = useControlNetOrT2IAdapterDefaultSettings(modelConfig);
const [updateModel, { isLoading: isLoadingUpdateModel }] = useUpdateModelMutation();
@ -30,16 +32,12 @@ export const ControlNetOrT2IAdapterDefaultSettings = () => {
const onSubmit = useCallback<SubmitHandler<ControlNetOrT2IAdapterDefaultSettingsFormData>>(
(data) => {
if (!selectedModelKey) {
return;
}
const body = {
preprocessor: data.preprocessor.isEnabled ? data.preprocessor.value : null,
};
updateModel({
key: selectedModelKey,
key: modelConfig.key,
body: { default_settings: body },
})
.unwrap()
@ -61,13 +59,9 @@ export const ControlNetOrT2IAdapterDefaultSettings = () => {
}
});
},
[selectedModelKey, reset, updateModel, t]
[updateModel, modelConfig.key, t, reset]
);
if (isLoadingDefaultSettings) {
return <Text>{t('common.loading')}</Text>;
}
return (
<>
<Flex gap="4" justifyContent="space-between" w="full" pb={4}>
@ -89,4 +83,6 @@ export const ControlNetOrT2IAdapterDefaultSettings = () => {
</SimpleGrid>
</>
);
};
});
ControlNetOrT2IAdapterDefaultSettings.displayName = 'ControlNetOrT2IAdapterDefaultSettings';

View File

@ -4,7 +4,7 @@ import { InformationalPopover } from 'common/components/InformationalPopover/Inf
import type { ControlNetOrT2IAdapterDefaultSettingsFormData } from 'features/modelManagerV2/subpanels/ModelPanel/ControlNetOrT2IAdapterDefaultSettings/ControlNetOrT2IAdapterDefaultSettings';
import type { FormField } from 'features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/MainModelDefaultSettings';
import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import type { UseControllerProps } from 'react-hook-form';
import { useController } from 'react-hook-form';
import { useTranslation } from 'react-i18next';
@ -28,7 +28,7 @@ const OPTIONS = [
type DefaultSchedulerType = ControlNetOrT2IAdapterDefaultSettingsFormData['preprocessor'];
export function DefaultPreprocessor(props: UseControllerProps<ControlNetOrT2IAdapterDefaultSettingsFormData>) {
export const DefaultPreprocessor = memo((props: UseControllerProps<ControlNetOrT2IAdapterDefaultSettingsFormData>) => {
const { t } = useTranslation();
const { field } = useController(props);
@ -63,4 +63,6 @@ export function DefaultPreprocessor(props: UseControllerProps<ControlNetOrT2IAda
<Combobox isDisabled={isDisabled} value={value} options={OPTIONS} onChange={onChange} />
</FormControl>
);
}
});
DefaultPreprocessor.displayName = 'DefaultPreprocessor';

View File

@ -2,7 +2,7 @@ import { CompositeNumberInput, CompositeSlider, Flex, FormControl, FormLabel } f
import { useAppSelector } from 'app/store/storeHooks';
import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import type { UseControllerProps } from 'react-hook-form';
import { useController } from 'react-hook-form';
import { useTranslation } from 'react-i18next';
@ -11,7 +11,7 @@ import type { MainModelDefaultSettingsFormData } from './MainModelDefaultSetting
type DefaultCfgRescaleMultiplierType = MainModelDefaultSettingsFormData['cfgRescaleMultiplier'];
export function DefaultCfgRescaleMultiplier(props: UseControllerProps<MainModelDefaultSettingsFormData>) {
export const DefaultCfgRescaleMultiplier = memo((props: UseControllerProps<MainModelDefaultSettingsFormData>) => {
const { field } = useController(props);
const sliderMin = useAppSelector((s) => s.config.sd.cfgRescaleMultiplier.sliderMin);
@ -74,4 +74,6 @@ export function DefaultCfgRescaleMultiplier(props: UseControllerProps<MainModelD
</Flex>
</FormControl>
);
}
});
DefaultCfgRescaleMultiplier.displayName = 'DefaultCfgRescaleMultiplier';

View File

@ -2,7 +2,7 @@ import { CompositeNumberInput, CompositeSlider, Flex, FormControl, FormLabel } f
import { useAppSelector } from 'app/store/storeHooks';
import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import type { UseControllerProps } from 'react-hook-form';
import { useController } from 'react-hook-form';
import { useTranslation } from 'react-i18next';
@ -11,7 +11,7 @@ import type { MainModelDefaultSettingsFormData } from './MainModelDefaultSetting
type DefaultCfgType = MainModelDefaultSettingsFormData['cfgScale'];
export function DefaultCfgScale(props: UseControllerProps<MainModelDefaultSettingsFormData>) {
export const DefaultCfgScale = memo((props: UseControllerProps<MainModelDefaultSettingsFormData>) => {
const { field } = useController(props);
const sliderMin = useAppSelector((s) => s.config.sd.guidance.sliderMin);
@ -74,4 +74,6 @@ export function DefaultCfgScale(props: UseControllerProps<MainModelDefaultSettin
</Flex>
</FormControl>
);
}
});
DefaultCfgScale.displayName = 'DefaultCfgScale';

View File

@ -2,7 +2,7 @@ import { CompositeNumberInput, CompositeSlider, Flex, FormControl, FormLabel } f
import { useAppSelector } from 'app/store/storeHooks';
import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import type { UseControllerProps } from 'react-hook-form';
import { useController } from 'react-hook-form';
import { useTranslation } from 'react-i18next';
@ -16,7 +16,7 @@ type Props = {
optimalDimension: number;
};
export function DefaultHeight({ control, optimalDimension }: Props) {
export const DefaultHeight = memo(({ control, optimalDimension }: Props) => {
const { field } = useController({ control, name: 'height' });
const sliderMin = useAppSelector((s) => s.config.sd.height.sliderMin);
const sliderMax = useAppSelector((s) => s.config.sd.height.sliderMax);
@ -78,4 +78,6 @@ export function DefaultHeight({ control, optimalDimension }: Props) {
</Flex>
</FormControl>
);
}
});
DefaultHeight.displayName = 'DefaultHeight';

View File

@ -4,7 +4,7 @@ import { InformationalPopover } from 'common/components/InformationalPopover/Inf
import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
import { SCHEDULER_OPTIONS } from 'features/parameters/types/constants';
import { isParameterScheduler } from 'features/parameters/types/parameterSchemas';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import type { UseControllerProps } from 'react-hook-form';
import { useController } from 'react-hook-form';
import { useTranslation } from 'react-i18next';
@ -13,7 +13,7 @@ import type { MainModelDefaultSettingsFormData } from './MainModelDefaultSetting
type DefaultSchedulerType = MainModelDefaultSettingsFormData['scheduler'];
export function DefaultScheduler(props: UseControllerProps<MainModelDefaultSettingsFormData>) {
export const DefaultScheduler = memo((props: UseControllerProps<MainModelDefaultSettingsFormData>) => {
const { t } = useTranslation();
const { field } = useController(props);
@ -51,4 +51,6 @@ export function DefaultScheduler(props: UseControllerProps<MainModelDefaultSetti
<Combobox isDisabled={isDisabled} value={value} options={SCHEDULER_OPTIONS} onChange={onChange} />
</FormControl>
);
}
});
DefaultScheduler.displayName = 'DefaultScheduler';

View File

@ -2,7 +2,7 @@ import { CompositeNumberInput, CompositeSlider, Flex, FormControl, FormLabel } f
import { useAppSelector } from 'app/store/storeHooks';
import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import type { UseControllerProps } from 'react-hook-form';
import { useController } from 'react-hook-form';
import { useTranslation } from 'react-i18next';
@ -11,7 +11,7 @@ import type { MainModelDefaultSettingsFormData } from './MainModelDefaultSetting
type DefaultSteps = MainModelDefaultSettingsFormData['steps'];
export function DefaultSteps(props: UseControllerProps<MainModelDefaultSettingsFormData>) {
export const DefaultSteps = memo((props: UseControllerProps<MainModelDefaultSettingsFormData>) => {
const { field } = useController(props);
const sliderMin = useAppSelector((s) => s.config.sd.steps.sliderMin);
@ -74,4 +74,6 @@ export function DefaultSteps(props: UseControllerProps<MainModelDefaultSettingsF
</Flex>
</FormControl>
);
}
});
DefaultSteps.displayName = 'DefaultSteps';

View File

@ -4,7 +4,7 @@ import { skipToken } from '@reduxjs/toolkit/query';
import { useAppSelector } from 'app/store/storeHooks';
import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import type { UseControllerProps } from 'react-hook-form';
import { useController } from 'react-hook-form';
import { useTranslation } from 'react-i18next';
@ -15,7 +15,7 @@ import type { MainModelDefaultSettingsFormData } from './MainModelDefaultSetting
type DefaultVaeType = MainModelDefaultSettingsFormData['vae'];
export function DefaultVae(props: UseControllerProps<MainModelDefaultSettingsFormData>) {
export const DefaultVae = memo((props: UseControllerProps<MainModelDefaultSettingsFormData>) => {
const { t } = useTranslation();
const { field } = useController(props);
const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
@ -64,4 +64,6 @@ export function DefaultVae(props: UseControllerProps<MainModelDefaultSettingsFor
<Combobox isDisabled={isDisabled} value={value} options={compatibleOptions} onChange={onChange} />
</FormControl>
);
}
});
DefaultVae.displayName = 'DefaultVae';

View File

@ -3,7 +3,7 @@ import { Combobox, Flex, FormControl, FormLabel } from '@invoke-ai/ui-library';
import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
import { isParameterPrecision } from 'features/parameters/types/parameterSchemas';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import type { UseControllerProps } from 'react-hook-form';
import { useController } from 'react-hook-form';
import { useTranslation } from 'react-i18next';
@ -17,7 +17,7 @@ const options = [
type DefaultVaePrecisionType = MainModelDefaultSettingsFormData['vaePrecision'];
export function DefaultVaePrecision(props: UseControllerProps<MainModelDefaultSettingsFormData>) {
export const DefaultVaePrecision = memo((props: UseControllerProps<MainModelDefaultSettingsFormData>) => {
const { t } = useTranslation();
const { field } = useController(props);
@ -52,4 +52,6 @@ export function DefaultVaePrecision(props: UseControllerProps<MainModelDefaultSe
<Combobox isDisabled={isDisabled} value={value} options={options} onChange={onChange} />
</FormControl>
);
}
});
DefaultVaePrecision.displayName = 'DefaultVaePrecision';

View File

@ -2,7 +2,7 @@ import { CompositeNumberInput, CompositeSlider, Flex, FormControl, FormLabel } f
import { useAppSelector } from 'app/store/storeHooks';
import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
import { useCallback, useMemo } from 'react';
import { memo, useCallback, useMemo } from 'react';
import type { UseControllerProps } from 'react-hook-form';
import { useController } from 'react-hook-form';
import { useTranslation } from 'react-i18next';
@ -16,7 +16,7 @@ type Props = {
optimalDimension: number;
};
export function DefaultWidth({ control, optimalDimension }: Props) {
export const DefaultWidth = memo(({ control, optimalDimension }: Props) => {
const { field } = useController({ control, name: 'width' });
const sliderMin = useAppSelector((s) => s.config.sd.width.sliderMin);
const sliderMax = useAppSelector((s) => s.config.sd.width.sliderMax);
@ -78,4 +78,6 @@ export function DefaultWidth({ control, optimalDimension }: Props) {
</Flex>
</FormControl>
);
}
});
DefaultWidth.displayName = 'DefaultWidth';

View File

@ -1,16 +1,18 @@
import { Button, Flex, Heading, SimpleGrid, Text } from '@invoke-ai/ui-library';
import { Button, Flex, Heading, SimpleGrid } from '@invoke-ai/ui-library';
import { useAppSelector } from 'app/store/storeHooks';
import { useMainModelDefaultSettings } from 'features/modelManagerV2/hooks/useMainModelDefaultSettings';
import { DefaultHeight } from 'features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultHeight';
import { DefaultWidth } from 'features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultWidth';
import type { ParameterScheduler } from 'features/parameters/types/parameterSchemas';
import { getOptimalDimension } from 'features/parameters/util/optimalDimension';
import { toast } from 'features/toast/toast';
import { useCallback } from 'react';
import { memo, useCallback, useMemo } from 'react';
import type { SubmitHandler } from 'react-hook-form';
import { useForm } from 'react-hook-form';
import { useTranslation } from 'react-i18next';
import { PiCheckBold } from 'react-icons/pi';
import { useUpdateModelMutation } from 'services/api/endpoints/models';
import type { MainModelConfig } from 'services/api/types';
import { DefaultCfgRescaleMultiplier } from './DefaultCfgRescaleMultiplier';
import { DefaultCfgScale } from './DefaultCfgScale';
@ -35,16 +37,16 @@ export type MainModelDefaultSettingsFormData = {
height: FormField<number>;
};
export const MainModelDefaultSettings = () => {
type Props = {
modelConfig: MainModelConfig;
};
export const MainModelDefaultSettings = memo(({ modelConfig }: Props) => {
const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
const { t } = useTranslation();
const {
defaultSettingsDefaults,
isLoading: isLoadingDefaultSettings,
optimalDimension,
} = useMainModelDefaultSettings(selectedModelKey);
const defaultSettingsDefaults = useMainModelDefaultSettings(modelConfig);
const optimalDimension = useMemo(() => getOptimalDimension(modelConfig), [modelConfig]);
const [updateModel, { isLoading: isLoadingUpdateModel }] = useUpdateModelMutation();
const { handleSubmit, control, formState, reset } = useForm<MainModelDefaultSettingsFormData>({
@ -94,10 +96,6 @@ export const MainModelDefaultSettings = () => {
[selectedModelKey, reset, updateModel, t]
);
if (isLoadingDefaultSettings) {
return <Text>{t('common.loading')}</Text>;
}
return (
<>
<Flex gap="4" justifyContent="space-between" w="full" pb={4}>
@ -126,4 +124,6 @@ export const MainModelDefaultSettings = () => {
</SimpleGrid>
</>
);
};
});
MainModelDefaultSettings.displayName = 'MainModelDefaultSettings';

View File

@ -1,120 +1,47 @@
import { Button, Flex, Heading, Spacer, Text } from '@invoke-ai/ui-library';
import { skipToken } from '@reduxjs/toolkit/query';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { setSelectedModelMode } from 'features/modelManagerV2/store/modelManagerV2Slice';
import { ModelConvertButton } from 'features/modelManagerV2/subpanels/ModelPanel/ModelConvertButton';
import { ModelEditButton } from 'features/modelManagerV2/subpanels/ModelPanel/ModelEditButton';
import { toast } from 'features/toast/toast';
import { useCallback } from 'react';
import type { SubmitHandler } from 'react-hook-form';
import { useForm } from 'react-hook-form';
import { useAppSelector } from 'app/store/storeHooks';
import { IAINoContentFallback, IAINoContentFallbackWithSpinner } from 'common/components/IAIImageFallback';
import { memo, useMemo } from 'react';
import { useTranslation } from 'react-i18next';
import { PiCheckBold, PiXBold } from 'react-icons/pi';
import type { UpdateModelArg } from 'services/api/endpoints/models';
import { useGetModelConfigQuery, useUpdateModelMutation } from 'services/api/endpoints/models';
import { PiExclamationMarkBold } from 'react-icons/pi';
import { modelConfigsAdapterSelectors, useGetModelConfigsQuery } from 'services/api/endpoints/models';
import ModelImageUpload from './Fields/ModelImageUpload';
import { ModelEdit } from './ModelEdit';
import { ModelView } from './ModelView';
export const Model = () => {
export const Model = memo(() => {
const { t } = useTranslation();
const selectedModelMode = useAppSelector((s) => s.modelmanagerV2.selectedModelMode);
const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
const { data, isLoading } = useGetModelConfigQuery(selectedModelKey ?? skipToken);
const [updateModel, { isLoading: isSubmitting }] = useUpdateModelMutation();
const dispatch = useAppDispatch();
const { data: modelConfigs, isLoading } = useGetModelConfigsQuery();
const modelConfig = useMemo(() => {
if (!modelConfigs) {
return null;
}
if (selectedModelKey === null) {
return null;
}
const modelConfig = modelConfigsAdapterSelectors.selectById(modelConfigs, selectedModelKey);
const form = useForm<UpdateModelArg['body']>({
defaultValues: data,
mode: 'onChange',
});
if (!modelConfig) {
return null;
}
const onSubmit = useCallback<SubmitHandler<UpdateModelArg['body']>>(
(values) => {
if (!data?.key) {
return;
}
const responseBody: UpdateModelArg = {
key: data.key,
body: values,
};
updateModel(responseBody)
.unwrap()
.then((payload) => {
form.reset(payload, { keepDefaultValues: true });
dispatch(setSelectedModelMode('view'));
toast({
id: 'MODEL_UPDATED',
title: t('modelManager.modelUpdated'),
status: 'success',
});
})
.catch((_) => {
form.reset();
toast({
id: 'MODEL_UPDATE_FAILED',
title: t('modelManager.modelUpdateFailed'),
status: 'error',
});
});
},
[dispatch, data?.key, form, t, updateModel]
);
const handleClickCancel = useCallback(() => {
dispatch(setSelectedModelMode('view'));
}, [dispatch]);
return modelConfig;
}, [modelConfigs, selectedModelKey]);
if (isLoading) {
return <Text>{t('common.loading')}</Text>;
return <IAINoContentFallbackWithSpinner label={t('common.loading')} />;
}
if (!data) {
return <Text>{t('common.somethingWentWrong')}</Text>;
if (!modelConfig) {
return <IAINoContentFallback label={t('common.somethingWentWrong')} icon={PiExclamationMarkBold} />;
}
return (
<Flex flexDir="column" gap={4}>
<Flex alignItems="flex-start" gap={4}>
<ModelImageUpload model_key={selectedModelKey} model_image={data.cover_image} />
<Flex flexDir="column" gap={1} flexGrow={1} minW={0}>
<Flex gap={2}>
<Heading as="h2" fontSize="lg" noOfLines={1} wordBreak="break-all">
{data.name}
</Heading>
<Spacer />
{selectedModelMode === 'view' && <ModelConvertButton modelKey={selectedModelKey} />}
{selectedModelMode === 'view' && <ModelEditButton />}
{selectedModelMode === 'edit' && (
<Button size="sm" onClick={handleClickCancel} leftIcon={<PiXBold />}>
{t('common.cancel')}
</Button>
)}
{selectedModelMode === 'edit' && (
<Button
size="sm"
colorScheme="invokeYellow"
leftIcon={<PiCheckBold />}
onClick={form.handleSubmit(onSubmit)}
isLoading={isSubmitting}
isDisabled={Boolean(Object.keys(form.formState.errors).length)}
>
{t('common.save')}
</Button>
)}
</Flex>
{data.source && (
<Text variant="subtext" noOfLines={1} wordBreak="break-all">
{t('modelManager.source')}: {data?.source}
</Text>
)}
<Text noOfLines={3}>{data.description}</Text>
</Flex>
</Flex>
{selectedModelMode === 'view' ? <ModelView /> : <ModelEdit form={form} onSubmit={onSubmit} />}
</Flex>
);
};
if (selectedModelMode === 'view') {
return <ModelView modelConfig={modelConfig} />;
}
return <ModelEdit modelConfig={modelConfig} />;
});
Model.displayName = 'Model';

View File

@ -1,11 +1,12 @@
import { FormControl, FormLabel, Text } from '@invoke-ai/ui-library';
import { memo } from 'react';
interface Props {
label: string;
value: string | null | undefined;
}
export const ModelAttrView = ({ label, value }: Props) => {
export const ModelAttrView = memo(({ label, value }: Props) => {
return (
<FormControl flexDir="column" alignItems="flex-start" gap={0}>
<FormLabel>{label}</FormLabel>
@ -14,4 +15,6 @@ export const ModelAttrView = ({ label, value }: Props) => {
</Text>
</FormControl>
);
};
});
ModelAttrView.displayName = 'ModelAttrView';

View File

@ -8,52 +8,46 @@ import {
UnorderedList,
useDisclosure,
} from '@invoke-ai/ui-library';
import { skipToken } from '@reduxjs/toolkit/query';
import { toast } from 'features/toast/toast';
import { useCallback } from 'react';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { useConvertModelMutation, useGetModelConfigQuery } from 'services/api/endpoints/models';
import { useConvertModelMutation } from 'services/api/endpoints/models';
import type { CheckpointModelConfig } from 'services/api/types';
interface ModelConvertProps {
modelKey: string | null;
modelConfig: CheckpointModelConfig;
}
export const ModelConvertButton = (props: ModelConvertProps) => {
const { modelKey } = props;
export const ModelConvertButton = memo(({ modelConfig }: ModelConvertProps) => {
const { t } = useTranslation();
const { data } = useGetModelConfigQuery(modelKey ?? skipToken);
const [convertModel, { isLoading }] = useConvertModelMutation();
const { isOpen, onOpen, onClose } = useDisclosure();
const modelConvertHandler = useCallback(() => {
if (!data || isLoading) {
if (!modelConfig || isLoading) {
return;
}
const toastId = `CONVERTING_MODEL_${data.key}`;
const toastId = `CONVERTING_MODEL_${modelConfig.key}`;
toast({
id: toastId,
title: `${t('modelManager.convertingModelBegin')}: ${data?.name}`,
title: `${t('modelManager.convertingModelBegin')}: ${modelConfig.name}`,
status: 'info',
});
convertModel(data?.key)
convertModel(modelConfig.key)
.unwrap()
.then(() => {
toast({ id: toastId, title: `${t('modelManager.modelConverted')}: ${data?.name}`, status: 'success' });
toast({ id: toastId, title: `${t('modelManager.modelConverted')}: ${modelConfig.name}`, status: 'success' });
})
.catch(() => {
toast({
id: toastId,
title: `${t('modelManager.modelConversionFailed')}: ${data?.name}`,
title: `${t('modelManager.modelConversionFailed')}: ${modelConfig.name}`,
status: 'error',
});
});
}, [data, isLoading, t, convertModel]);
if (data?.format !== 'checkpoint') {
return;
}
}, [modelConfig, isLoading, t, convertModel]);
return (
<>
@ -68,7 +62,7 @@ export const ModelConvertButton = (props: ModelConvertProps) => {
🧨 {t('modelManager.convert')}
</Button>
<ConfirmationAlertDialog
title={`${t('modelManager.convert')} ${data?.name}`}
title={`${t('modelManager.convert')} ${modelConfig.name}`}
acceptCallback={modelConvertHandler}
acceptButtonText={`${t('modelManager.convert')}`}
isOpen={isOpen}
@ -96,4 +90,6 @@ export const ModelConvertButton = (props: ModelConvertProps) => {
</ConfirmationAlertDialog>
</>
);
};
});
ModelConvertButton.displayName = 'ModelConvertButton';

View File

@ -1,4 +1,5 @@
import {
Button,
Checkbox,
Flex,
FormControl,
@ -7,96 +8,154 @@ import {
Heading,
Input,
SimpleGrid,
Text,
Textarea,
} from '@invoke-ai/ui-library';
import { skipToken } from '@reduxjs/toolkit/query';
import { useAppSelector } from 'app/store/storeHooks';
import type { SubmitHandler, UseFormReturn } from 'react-hook-form';
import { useAppDispatch } from 'app/store/storeHooks';
import { setSelectedModelMode } from 'features/modelManagerV2/store/modelManagerV2Slice';
import { ModelHeader } from 'features/modelManagerV2/subpanels/ModelPanel/ModelHeader';
import { toast } from 'features/toast/toast';
import { memo, useCallback } from 'react';
import { type SubmitHandler, useForm } from 'react-hook-form';
import { useTranslation } from 'react-i18next';
import type { UpdateModelArg } from 'services/api/endpoints/models';
import { useGetModelConfigQuery } from 'services/api/endpoints/models';
import { PiCheckBold, PiXBold } from 'react-icons/pi';
import { type UpdateModelArg, useUpdateModelMutation } from 'services/api/endpoints/models';
import type { AnyModelConfig } from 'services/api/types';
import BaseModelSelect from './Fields/BaseModelSelect';
import ModelVariantSelect from './Fields/ModelVariantSelect';
import PredictionTypeSelect from './Fields/PredictionTypeSelect';
type Props = {
form: UseFormReturn<UpdateModelArg['body']>;
onSubmit: SubmitHandler<UpdateModelArg['body']>;
modelConfig: AnyModelConfig;
};
const stringFieldOptions = {
validate: (value?: string | null) => (value && value.trim().length > 3) || 'Must be at least 3 characters',
};
export const ModelEdit = ({ form }: Props) => {
const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
const { data, isLoading } = useGetModelConfigQuery(selectedModelKey ?? skipToken);
export const ModelEdit = memo(({ modelConfig }: Props) => {
const { t } = useTranslation();
const [updateModel, { isLoading: isSubmitting }] = useUpdateModelMutation();
const dispatch = useAppDispatch();
if (isLoading) {
return <Text>{t('common.loading')}</Text>;
}
const form = useForm<UpdateModelArg['body']>({
defaultValues: modelConfig,
mode: 'onChange',
});
if (!data) {
return <Text>{t('common.somethingWentWrong')}</Text>;
}
const onSubmit = useCallback<SubmitHandler<UpdateModelArg['body']>>(
(values) => {
const responseBody: UpdateModelArg = {
key: modelConfig.key,
body: values,
};
updateModel(responseBody)
.unwrap()
.then((payload) => {
form.reset(payload, { keepDefaultValues: true });
dispatch(setSelectedModelMode('view'));
toast({
id: 'MODEL_UPDATED',
title: t('modelManager.modelUpdated'),
status: 'success',
});
})
.catch((_) => {
form.reset();
toast({
id: 'MODEL_UPDATE_FAILED',
title: t('modelManager.modelUpdateFailed'),
status: 'error',
});
});
},
[dispatch, modelConfig.key, form, t, updateModel]
);
const handleClickCancel = useCallback(() => {
dispatch(setSelectedModelMode('view'));
}, [dispatch]);
return (
<Flex flexDir="column" h="full">
<form>
<Flex w="full" justifyContent="space-between" gap={4} alignItems="center">
<FormControl flexDir="column" alignItems="flex-start" gap={1} isInvalid={Boolean(form.formState.errors.name)}>
<FormLabel>{t('modelManager.modelName')}</FormLabel>
<Input {...form.register('name', stringFieldOptions)} size="md" />
<Flex flexDir="column" gap={4}>
<ModelHeader modelConfig={modelConfig}>
<Button flexShrink={0} size="sm" onClick={handleClickCancel} leftIcon={<PiXBold />}>
{t('common.cancel')}
</Button>
<Button
flexShrink={0}
size="sm"
colorScheme="invokeYellow"
leftIcon={<PiCheckBold />}
onClick={form.handleSubmit(onSubmit)}
isLoading={isSubmitting}
isDisabled={Boolean(Object.keys(form.formState.errors).length)}
>
{t('common.save')}
</Button>
</ModelHeader>
<Flex flexDir="column" h="full">
<form>
<Flex w="full" justifyContent="space-between" gap={4} alignItems="center">
<FormControl
flexDir="column"
alignItems="flex-start"
gap={1}
isInvalid={Boolean(form.formState.errors.name)}
>
<FormLabel>{t('modelManager.modelName')}</FormLabel>
<Input {...form.register('name', stringFieldOptions)} size="md" />
{form.formState.errors.name?.message && (
<FormErrorMessage>{form.formState.errors.name?.message}</FormErrorMessage>
)}
</FormControl>
</Flex>
<Flex flexDir="column" gap={3} mt="4">
<Flex gap="4" alignItems="center">
<FormControl flexDir="column" alignItems="flex-start" gap={1}>
<FormLabel>{t('modelManager.description')}</FormLabel>
<Textarea {...form.register('description')} minH={32} />
{form.formState.errors.name?.message && (
<FormErrorMessage>{form.formState.errors.name?.message}</FormErrorMessage>
)}
</FormControl>
</Flex>
<Heading as="h3" fontSize="md" mt="4">
{t('modelManager.modelSettings')}
</Heading>
<SimpleGrid columns={2} gap={4}>
<FormControl flexDir="column" alignItems="flex-start" gap={1}>
<FormLabel>{t('modelManager.baseModel')}</FormLabel>
<BaseModelSelect control={form.control} />
</FormControl>
{data.type === 'main' && (
<Flex flexDir="column" gap={3} mt="4">
<Flex gap="4" alignItems="center">
<FormControl flexDir="column" alignItems="flex-start" gap={1}>
<FormLabel>{t('modelManager.variant')}</FormLabel>
<ModelVariantSelect control={form.control} />
<FormLabel>{t('modelManager.description')}</FormLabel>
<Textarea {...form.register('description')} minH={32} />
</FormControl>
)}
{data.type === 'main' && data.format === 'checkpoint' && (
<>
</Flex>
<Heading as="h3" fontSize="md" mt="4">
{t('modelManager.modelSettings')}
</Heading>
<SimpleGrid columns={2} gap={4}>
<FormControl flexDir="column" alignItems="flex-start" gap={1}>
<FormLabel>{t('modelManager.baseModel')}</FormLabel>
<BaseModelSelect control={form.control} />
</FormControl>
{modelConfig.type === 'main' && (
<FormControl flexDir="column" alignItems="flex-start" gap={1}>
<FormLabel>{t('modelManager.pathToConfig')}</FormLabel>
<Input {...form.register('config_path', stringFieldOptions)} />
<FormLabel>{t('modelManager.variant')}</FormLabel>
<ModelVariantSelect control={form.control} />
</FormControl>
<FormControl flexDir="column" alignItems="flex-start" gap={1}>
<FormLabel>{t('modelManager.predictionType')}</FormLabel>
<PredictionTypeSelect control={form.control} />
</FormControl>
<FormControl flexDir="column" alignItems="flex-start" gap={1}>
<FormLabel>{t('modelManager.upcastAttention')}</FormLabel>
<Checkbox {...form.register('upcast_attention')} />
</FormControl>
</>
)}
</SimpleGrid>
</Flex>
</form>
)}
{modelConfig.type === 'main' && modelConfig.format === 'checkpoint' && (
<>
<FormControl flexDir="column" alignItems="flex-start" gap={1}>
<FormLabel>{t('modelManager.pathToConfig')}</FormLabel>
<Input {...form.register('config_path', stringFieldOptions)} />
</FormControl>
<FormControl flexDir="column" alignItems="flex-start" gap={1}>
<FormLabel>{t('modelManager.predictionType')}</FormLabel>
<PredictionTypeSelect control={form.control} />
</FormControl>
<FormControl flexDir="column" alignItems="flex-start" gap={1}>
<FormLabel>{t('modelManager.upcastAttention')}</FormLabel>
<Checkbox {...form.register('upcast_attention')} />
</FormControl>
</>
)}
</SimpleGrid>
</Flex>
</form>
</Flex>
</Flex>
);
};
});
ModelEdit.displayName = 'ModelEdit';

View File

@ -1,11 +1,11 @@
import { Button } from '@invoke-ai/ui-library';
import { useAppDispatch } from 'app/store/storeHooks';
import { setSelectedModelMode } from 'features/modelManagerV2/store/modelManagerV2Slice';
import { useCallback } from 'react';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
import { IoPencil } from 'react-icons/io5';
export const ModelEditButton = () => {
export const ModelEditButton = memo(() => {
const { t } = useTranslation();
const dispatch = useAppDispatch();
@ -18,4 +18,6 @@ export const ModelEditButton = () => {
{t('modelManager.edit')}
</Button>
);
};
});
ModelEditButton.displayName = 'ModelEditButton';

View File

@ -0,0 +1,36 @@
import { Flex, Heading, Spacer, Text } from '@invoke-ai/ui-library';
import ModelImageUpload from 'features/modelManagerV2/subpanels/ModelPanel/Fields/ModelImageUpload';
import type { PropsWithChildren } from 'react';
import { memo } from 'react';
import { useTranslation } from 'react-i18next';
import type { AnyModelConfig } from 'services/api/types';
type Props = PropsWithChildren<{
modelConfig: AnyModelConfig;
}>;
export const ModelHeader = memo(({ modelConfig, children }: Props) => {
const { t } = useTranslation();
return (
<Flex alignItems="flex-start" gap={4}>
<ModelImageUpload model_key={modelConfig.key} model_image={modelConfig.cover_image} />
<Flex flexDir="column" gap={1} flexGrow={1} minW={0}>
<Flex gap={2}>
<Heading as="h2" fontSize="lg" noOfLines={1} wordBreak="break-all">
{modelConfig.name}
</Heading>
<Spacer />
{children}
</Flex>
{modelConfig.source && (
<Text variant="subtext" noOfLines={1} wordBreak="break-all">
{t('modelManager.source')}: {modelConfig.source}
</Text>
)}
<Text noOfLines={3}>{modelConfig.description}</Text>
</Flex>
</Flex>
);
});
ModelHeader.displayName = 'ModelHeader';

View File

@ -1,55 +1,67 @@
import { Box, Flex, SimpleGrid, Text } from '@invoke-ai/ui-library';
import { skipToken } from '@reduxjs/toolkit/query';
import { useAppSelector } from 'app/store/storeHooks';
import { Box, Flex, SimpleGrid } from '@invoke-ai/ui-library';
import { ControlNetOrT2IAdapterDefaultSettings } from 'features/modelManagerV2/subpanels/ModelPanel/ControlNetOrT2IAdapterDefaultSettings/ControlNetOrT2IAdapterDefaultSettings';
import { ModelConvertButton } from 'features/modelManagerV2/subpanels/ModelPanel/ModelConvertButton';
import { ModelEditButton } from 'features/modelManagerV2/subpanels/ModelPanel/ModelEditButton';
import { ModelHeader } from 'features/modelManagerV2/subpanels/ModelPanel/ModelHeader';
import { TriggerPhrases } from 'features/modelManagerV2/subpanels/ModelPanel/TriggerPhrases';
import { memo } from 'react';
import { useTranslation } from 'react-i18next';
import { useGetModelConfigQuery } from 'services/api/endpoints/models';
import type { AnyModelConfig } from 'services/api/types';
import { MainModelDefaultSettings } from './MainModelDefaultSettings/MainModelDefaultSettings';
import { ModelAttrView } from './ModelAttrView';
export const ModelView = () => {
type Props = {
modelConfig: AnyModelConfig;
};
export const ModelView = memo(({ modelConfig }: Props) => {
const { t } = useTranslation();
const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
const { data, isLoading } = useGetModelConfigQuery(selectedModelKey ?? skipToken);
if (isLoading) {
return <Text>{t('common.loading')}</Text>;
}
if (!data) {
return <Text>{t('common.somethingWentWrong')}</Text>;
}
return (
<Flex flexDir="column" h="full" gap={4}>
<Box layerStyle="second" borderRadius="base" p={4}>
<SimpleGrid columns={2} gap={4}>
<ModelAttrView label={t('modelManager.baseModel')} value={data.base} />
<ModelAttrView label={t('modelManager.modelType')} value={data.type} />
<ModelAttrView label={t('common.format')} value={data.format} />
<ModelAttrView label={t('modelManager.path')} value={data.path} />
{data.type === 'main' && <ModelAttrView label={t('modelManager.variant')} value={data.variant} />}
{data.type === 'main' && data.format === 'diffusers' && data.repo_variant && (
<ModelAttrView label={t('modelManager.repoVariant')} value={data.repo_variant} />
<Flex flexDir="column" gap={4}>
<ModelHeader modelConfig={modelConfig}>
{modelConfig.format === 'checkpoint' && modelConfig.type === 'main' && (
<ModelConvertButton modelConfig={modelConfig} />
)}
<ModelEditButton />
</ModelHeader>
<Flex flexDir="column" h="full" gap={4}>
<Box layerStyle="second" borderRadius="base" p={4}>
<SimpleGrid columns={2} gap={4}>
<ModelAttrView label={t('modelManager.baseModel')} value={modelConfig.base} />
<ModelAttrView label={t('modelManager.modelType')} value={modelConfig.type} />
<ModelAttrView label={t('common.format')} value={modelConfig.format} />
<ModelAttrView label={t('modelManager.path')} value={modelConfig.path} />
{modelConfig.type === 'main' && (
<ModelAttrView label={t('modelManager.variant')} value={modelConfig.variant} />
)}
{modelConfig.type === 'main' && modelConfig.format === 'diffusers' && modelConfig.repo_variant && (
<ModelAttrView label={t('modelManager.repoVariant')} value={modelConfig.repo_variant} />
)}
{modelConfig.type === 'main' && modelConfig.format === 'checkpoint' && (
<>
<ModelAttrView label={t('modelManager.pathToConfig')} value={modelConfig.config_path} />
<ModelAttrView label={t('modelManager.predictionType')} value={modelConfig.prediction_type} />
<ModelAttrView label={t('modelManager.upcastAttention')} value={`${modelConfig.upcast_attention}`} />
</>
)}
{modelConfig.type === 'ip_adapter' && modelConfig.format === 'invokeai' && (
<ModelAttrView label={t('modelManager.imageEncoderModelId')} value={modelConfig.image_encoder_model_id} />
)}
</SimpleGrid>
</Box>
<Box layerStyle="second" borderRadius="base" p={4}>
{modelConfig.type === 'main' && modelConfig.base !== 'sdxl-refiner' && (
<MainModelDefaultSettings modelConfig={modelConfig} />
)}
{data.type === 'main' && data.format === 'checkpoint' && (
<>
<ModelAttrView label={t('modelManager.pathToConfig')} value={data.config_path} />
<ModelAttrView label={t('modelManager.predictionType')} value={data.prediction_type} />
<ModelAttrView label={t('modelManager.upcastAttention')} value={`${data.upcast_attention}`} />
</>
{(modelConfig.type === 'controlnet' || modelConfig.type === 't2i_adapter') && (
<ControlNetOrT2IAdapterDefaultSettings modelConfig={modelConfig} />
)}
{data.type === 'ip_adapter' && data.format === 'invokeai' && (
<ModelAttrView label={t('modelManager.imageEncoderModelId')} value={data.image_encoder_model_id} />
)}
</SimpleGrid>
</Box>
<Box layerStyle="second" borderRadius="base" p={4}>
{data.type === 'main' && data.base !== 'sdxl-refiner' && <MainModelDefaultSettings />}
{(data.type === 'controlnet' || data.type === 't2i_adapter') && <ControlNetOrT2IAdapterDefaultSettings />}
{(data.type === 'main' || data.type === 'lora') && <TriggerPhrases />}
</Box>
{(modelConfig.type === 'main' || modelConfig.type === 'lora') && <TriggerPhrases modelConfig={modelConfig} />}
</Box>
</Flex>
</Flex>
);
};
});
ModelView.displayName = 'ModelView';

View File

@ -1,4 +1,4 @@
import { Switch } from '@invoke-ai/ui-library';
import { Switch, typedMemo } from '@invoke-ai/ui-library';
import type { ChangeEvent } from 'react';
import { useCallback, useMemo } from 'react';
import type { UseControllerProps } from 'react-hook-form';
@ -6,7 +6,7 @@ import { useController } from 'react-hook-form';
import type { FormField } from './MainModelDefaultSettings/MainModelDefaultSettings';
export function SettingToggle<T, F extends Record<string, FormField<T>>>(props: UseControllerProps<F>) {
export const SettingToggle = typedMemo(<T, F extends Record<string, FormField<T>>>(props: UseControllerProps<F>) => {
const { field } = useController(props);
const value = useMemo(() => {
@ -25,4 +25,6 @@ export function SettingToggle<T, F extends Record<string, FormField<T>>>(props:
);
return <Switch size="sm" isChecked={value} onChange={onChange} />;
}
});
SettingToggle.displayName = 'SettingToggle';

View File

@ -9,19 +9,19 @@ import {
TagCloseButton,
TagLabel,
} from '@invoke-ai/ui-library';
import { skipToken } from '@reduxjs/toolkit/query';
import { useAppSelector } from 'app/store/storeHooks';
import type { ChangeEvent } from 'react';
import { useCallback, useMemo, useState } from 'react';
import { memo, useCallback, useMemo, useState } from 'react';
import { useTranslation } from 'react-i18next';
import { PiPlusBold } from 'react-icons/pi';
import { useGetModelConfigQuery, useUpdateModelMutation } from 'services/api/endpoints/models';
import { isLoRAModelConfig, isNonRefinerMainModelConfig } from 'services/api/types';
import { useUpdateModelMutation } from 'services/api/endpoints/models';
import type { LoRAModelConfig, MainModelConfig } from 'services/api/types';
export const TriggerPhrases = () => {
type Props = {
modelConfig: MainModelConfig | LoRAModelConfig;
};
export const TriggerPhrases = memo(({ modelConfig }: Props) => {
const { t } = useTranslation();
const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
const { currentData: modelConfig } = useGetModelConfigQuery(selectedModelKey ?? skipToken);
const [phrase, setPhrase] = useState('');
const [updateModel, { isLoading }] = useUpdateModelMutation();
@ -31,9 +31,6 @@ export const TriggerPhrases = () => {
}, []);
const triggerPhrases = useMemo(() => {
if (!modelConfig || (!isNonRefinerMainModelConfig(modelConfig) && !isLoRAModelConfig(modelConfig))) {
return [];
}
return modelConfig?.trigger_phrases || [];
}, [modelConfig]);
@ -48,10 +45,6 @@ export const TriggerPhrases = () => {
}, [phrase, triggerPhrases]);
const addTriggerPhrase = useCallback(async () => {
if (!selectedModelKey) {
return;
}
if (!phrase.length || triggerPhrases.includes(phrase)) {
return;
}
@ -59,22 +52,18 @@ export const TriggerPhrases = () => {
setPhrase('');
await updateModel({
key: selectedModelKey,
key: modelConfig.key,
body: { trigger_phrases: [...triggerPhrases, phrase] },
}).unwrap();
}, [updateModel, selectedModelKey, phrase, triggerPhrases]);
}, [phrase, triggerPhrases, updateModel, modelConfig.key]);
const removeTriggerPhrase = useCallback(
async (phraseToRemove: string) => {
if (!selectedModelKey) {
return;
}
const filteredPhrases = triggerPhrases.filter((p) => p !== phraseToRemove);
await updateModel({ key: selectedModelKey, body: { trigger_phrases: filteredPhrases } }).unwrap();
await updateModel({ key: modelConfig.key, body: { trigger_phrases: filteredPhrases } }).unwrap();
},
[updateModel, selectedModelKey, triggerPhrases]
[triggerPhrases, updateModel, modelConfig]
);
const onTriggerPhraseAddFormSubmit = useCallback(
@ -103,7 +92,9 @@ export const TriggerPhrases = () => {
{t('common.add')}
</Button>
</Flex>
{!!errors.length && errors.map((error) => <FormErrorMessage key={error}>{error}</FormErrorMessage>)}
{errors.map((error) => (
<FormErrorMessage key={error}>{error}</FormErrorMessage>
))}
</Flex>
</FormControl>
</form>
@ -118,4 +109,6 @@ export const TriggerPhrases = () => {
</Flex>
</Flex>
);
};
});
TriggerPhrases.displayName = 'TriggerPhrases';

View File

@ -59,17 +59,19 @@ const pasteSelection = (withEdgesToCopiedNodes?: boolean) => {
for (const edge of copiedEdges) {
if (edge.source === node.id) {
edge.source = id;
edge.id = edge.id.replace(node.data.id, id);
}
if (edge.target === node.id) {
} else if (edge.target === node.id) {
edge.target = id;
edge.id = edge.id.replace(node.data.id, id);
}
}
node.id = id;
node.data.id = id;
});
copiedEdges.forEach((edge) => {
// Copied edges need a fresh id too
edge.id = uuidv4();
});
const nodeChanges: NodeChange[] = [];
const edgeChanges: EdgeChange[] = [];
// Deselect existing nodes

View File

@ -1,5 +1,6 @@
import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
import { creativityChanged } from 'features/parameters/store/upscaleSlice';
import { memo, useCallback, useMemo } from 'react';
import { useTranslation } from 'react-i18next';
@ -25,7 +26,9 @@ const ParamCreativity = () => {
return (
<FormControl>
<FormLabel>{t('upscaling.creativity')}</FormLabel>
<InformationalPopover feature="creativity">
<FormLabel>{t('upscaling.creativity')}</FormLabel>
</InformationalPopover>
<CompositeSlider
value={creativity}
defaultValue={initial}

View File

@ -1,5 +1,6 @@
import { Box, Combobox, FormControl, FormLabel, Tooltip } from '@invoke-ai/ui-library';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
import { useModelCombobox } from 'common/hooks/useModelCombobox';
import { upscaleModelChanged } from 'features/parameters/store/upscaleSlice';
import { memo, useCallback, useMemo } from 'react';
@ -37,7 +38,9 @@ const ParamSpandrelModel = () => {
return (
<FormControl orientation="vertical">
<FormLabel>{t('upscaling.upscaleModel')}</FormLabel>
<InformationalPopover feature="upscaleModel">
<FormLabel>{t('upscaling.upscaleModel')}</FormLabel>
</InformationalPopover>
<Tooltip label={tooltipLabel}>
<Box w="full">
<Combobox

View File

@ -1,5 +1,6 @@
import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
import { structureChanged } from 'features/parameters/store/upscaleSlice';
import { memo, useCallback, useMemo } from 'react';
import { useTranslation } from 'react-i18next';
@ -25,7 +26,9 @@ const ParamStructure = () => {
return (
<FormControl>
<FormLabel>{t('upscaling.structure')}</FormLabel>
<InformationalPopover feature="structure">
<FormLabel>{t('upscaling.structure')}</FormLabel>
</InformationalPopover>
<CompositeSlider
value={structure}
defaultValue={initial}

View File

@ -64,7 +64,7 @@ export const AdvancedSettingsAccordion = memo(() => {
const badges = useAppSelector(selectBadges);
const { t } = useTranslation();
const { isOpen, onToggle } = useStandaloneAccordionToggle({
id: 'advanced-settings',
id: `'advanced-settings-${activeTabName}`,
defaultIsOpen: false,
});

View File

@ -14,6 +14,7 @@ import ParamMainModelSelect from 'features/parameters/components/MainModel/Param
import { UseDefaultSettingsButton } from 'features/parameters/components/MainModel/UseDefaultSettingsButton';
import { useExpanderToggle } from 'features/settingsAccordions/hooks/useExpanderToggle';
import { useStandaloneAccordionToggle } from 'features/settingsAccordions/hooks/useStandaloneAccordionToggle';
import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
import { filter } from 'lodash-es';
import { memo, useMemo } from 'react';
import { useTranslation } from 'react-i18next';
@ -26,6 +27,7 @@ const formLabelProps: FormLabelProps = {
export const GenerationSettingsAccordion = memo(() => {
const { t } = useTranslation();
const modelConfig = useSelectedModelConfig();
const activeTabName = useAppSelector(activeTabNameSelector);
const selectBadges = useMemo(
() =>
createMemoizedSelector(selectLoraSlice, (lora) => {
@ -42,8 +44,8 @@ export const GenerationSettingsAccordion = memo(() => {
defaultIsOpen: false,
});
const { isOpen: isOpenAccordion, onToggle: onToggleAccordion } = useStandaloneAccordionToggle({
id: 'generation-settings',
defaultIsOpen: true,
id: `generation-settings-${activeTabName}`,
defaultIsOpen: activeTabName !== 'upscaling',
});
return (

View File

@ -1,5 +1,6 @@
import { CompositeNumberInput, CompositeSlider, Flex, FormControl, FormLabel } from '@invoke-ai/ui-library';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
import { scaleChanged } from 'features/parameters/store/upscaleSlice';
import { memo, useCallback } from 'react';
import { useTranslation } from 'react-i18next';
@ -22,7 +23,9 @@ export const UpscaleScaleSlider = memo(() => {
return (
<FormControl orientation="vertical" gap={0}>
<FormLabel m={0}>{t('upscaling.scale')}</FormLabel>
<InformationalPopover feature="scale">
<FormLabel m={0}>{t('upscaling.scale')}</FormLabel>
</InformationalPopover>
<Flex w="full" gap={4}>
<CompositeSlider
min={2}

View File

@ -18,5 +18,6 @@ export const useStandaloneAccordionToggle = (arg: UseStandaloneAccordionToggleAr
const onToggle = useCallback(() => {
dispatch(accordionStateChanged({ id: arg.id, isOpen: !isOpen }));
}, [arg.id, dispatch, isOpen]);
return { isOpen, onToggle };
};

View File

@ -27,7 +27,7 @@ const initialSystemState: SystemState = {
language: 'en',
shouldUseNSFWChecker: false,
shouldUseWatermarker: false,
shouldEnableInformationalPopovers: false,
shouldEnableInformationalPopovers: true,
status: 'DISCONNECTED',
cancellations: [],
};

View File

@ -242,7 +242,6 @@ export const modelsApi = api.injectEndpoints({
}
return tags;
},
keepUnusedDataFor: 60 * 60 * 1000 * 24, // 1 day (infinite)
transformResponse: (response: GetModelConfigsResponse) => {
return modelConfigsAdapter.setAll(modelConfigsAdapter.getInitialState(), response.models);
},

View File

@ -54,7 +54,7 @@ export type T2IAdapterModelConfig = S['T2IAdapterConfig'];
export type SpandrelImageToImageModelConfig = S['SpandrelImageToImageConfig'];
type TextualInversionModelConfig = S['TextualInversionFileConfig'] | S['TextualInversionFolderConfig'];
type DiffusersModelConfig = S['MainDiffusersConfig'];
type CheckpointModelConfig = S['MainCheckpointConfig'];
export type CheckpointModelConfig = S['MainCheckpointConfig'];
type CLIPVisionDiffusersConfig = S['CLIPVisionDiffusersConfig'];
export type MainModelConfig = DiffusersModelConfig | CheckpointModelConfig;
export type AnyModelConfig =

View File

@ -1 +1 @@
__version__ = "4.2.7rc1"
__version__ = "4.2.7"