mirror of
https://github.com/mudler/LocalAI.git
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feat(diffusers): add img2img and clip_skip, support more kernels schedulers (#906)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This commit is contained in:
Ettore Di Giacinto
GitHub
parent
ddf9bc2335
commit
2bacd0180d
@ -9,7 +9,7 @@ import (
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model "github.com/go-skynet/LocalAI/pkg/model"
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)
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func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst string, loader *model.ModelLoader, c config.Config, o *options.Option) (func() error, error) {
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func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, src, dst string, loader *model.ModelLoader, c config.Config, o *options.Option) (func() error, error) {
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opts := []model.Option{
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model.WithBackendString(c.Backend),
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@ -22,6 +22,10 @@ func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negat
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SchedulerType: c.Diffusers.SchedulerType,
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PipelineType: c.Diffusers.PipelineType,
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CFGScale: c.Diffusers.CFGScale,
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IMG2IMG: c.Diffusers.IMG2IMG,
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CLIPModel: c.Diffusers.ClipModel,
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CLIPSubfolder: c.Diffusers.ClipSubFolder,
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CLIPSkip: int32(c.Diffusers.ClipSkip),
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}),
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}
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@ -53,9 +57,11 @@ func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negat
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Mode: int32(mode),
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Step: int32(step),
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Seed: int32(seed),
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CLIPSkip: int32(c.Diffusers.ClipSkip),
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PositivePrompt: positive_prompt,
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NegativePrompt: negative_prompt,
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Dst: dst,
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Src: src,
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EnableParameters: c.Diffusers.EnableParameters,
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})
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return err
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@ -55,6 +55,10 @@ type Diffusers struct {
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CUDA bool `yaml:"cuda"`
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EnableParameters string `yaml:"enable_parameters"` // A list of comma separated parameters to specify
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CFGScale float32 `yaml:"cfg_scale"` // Classifier-Free Guidance Scale
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IMG2IMG bool `yaml:"img2img"` // Image to Image Diffuser
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ClipSkip int `yaml:"clip_skip"` // Skip every N frames
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ClipModel string `yaml:"clip_model"` // Clip model to use
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ClipSubFolder string `yaml:"clip_subfolder"` // Subfolder to use for clip model
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}
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type LLMConfig struct {
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@ -41,4 +41,7 @@ type PredictionOptions struct {
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NegativePromptScale float32 `json:"negative_prompt_scale" yaml:"negative_prompt_scale"`
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// AutoGPTQ
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UseFastTokenizer bool `json:"use_fast_tokenizer" yaml:"use_fast_tokenizer"`
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// Diffusers
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ClipSkip int `json:"clip_skip" yaml:"clip_skip"`
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}
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@ -4,7 +4,9 @@ import (
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"encoding/base64"
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"encoding/json"
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"fmt"
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"io"
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"os"
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"path"
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"path/filepath"
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"strconv"
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"strings"
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@ -49,6 +51,37 @@ func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx
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return fmt.Errorf("failed reading parameters from request:%w", err)
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}
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src := ""
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// retrieve the file data from the request
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file, err := c.FormFile("src")
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if err == nil {
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f, err := file.Open()
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if err != nil {
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return err
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}
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defer f.Close()
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dir, err := os.MkdirTemp("", "img2img")
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if err != nil {
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return err
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}
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defer os.RemoveAll(dir)
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dst := filepath.Join(dir, path.Base(file.Filename))
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dstFile, err := os.Create(dst)
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if err != nil {
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return err
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}
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if _, err := io.Copy(dstFile, f); err != nil {
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log.Debug().Msgf("Image file copying error %+v - %+v - err %+v", file.Filename, dst, err)
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return err
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}
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src = dst
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}
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log.Debug().Msgf("Parameter Config: %+v", config)
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// XXX: Only stablediffusion is supported for now
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@ -73,7 +106,7 @@ func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx
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if input.ResponseFormat == "b64_json" {
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b64JSON = true
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}
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// src and clip_skip
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var result []Item
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for _, i := range config.PromptStrings {
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n := input.N
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@ -121,7 +154,7 @@ func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx
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baseURL := c.BaseURL()
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fn, err := backend.ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, output, o.Loader, *config, o)
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fn, err := backend.ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, src, output, o.Loader, *config, o)
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if err != nil {
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return err
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}
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@ -75,6 +75,10 @@ func updateConfig(config *config.Config, input *OpenAIRequest) {
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config.Backend = input.Backend
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}
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if input.ClipSkip != 0 {
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config.Diffusers.ClipSkip = input.ClipSkip
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}
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if input.ModelBaseName != "" {
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config.AutoGPTQ.ModelBaseName = input.ModelBaseName
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}
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File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@ -15,15 +15,108 @@ from torch import autocast
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from diffusers import StableDiffusionXLPipeline, DPMSolverMultistepScheduler, StableDiffusionPipeline, DiffusionPipeline, EulerAncestralDiscreteScheduler
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from diffusers.pipelines.stable_diffusion import safety_checker
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from compel import Compel
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from PIL import Image
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from io import BytesIO
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from diffusers import StableDiffusionImg2ImgPipeline
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from transformers import CLIPTextModel
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from enum import Enum
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_ONE_DAY_IN_SECONDS = 60 * 60 * 24
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COMPEL=os.environ.get("COMPEL", "1") == "1"
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CLIPSKIP=os.environ.get("CLIPSKIP", "1") == "1"
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# https://github.com/CompVis/stable-diffusion/issues/239#issuecomment-1627615287
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def sc(self, clip_input, images) : return images, [False for i in images]
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# edit the StableDiffusionSafetyChecker class so that, when called, it just returns the images and an array of True values
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safety_checker.StableDiffusionSafetyChecker.forward = sc
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from diffusers.schedulers import (
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DDIMScheduler,
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DPMSolverMultistepScheduler,
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DPMSolverSinglestepScheduler,
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EulerAncestralDiscreteScheduler,
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EulerDiscreteScheduler,
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HeunDiscreteScheduler,
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KDPM2AncestralDiscreteScheduler,
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KDPM2DiscreteScheduler,
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LMSDiscreteScheduler,
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PNDMScheduler,
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UniPCMultistepScheduler,
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)
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# The scheduler list mapping was taken from here: https://github.com/neggles/animatediff-cli/blob/6f336f5f4b5e38e85d7f06f1744ef42d0a45f2a7/src/animatediff/schedulers.py#L39
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# Credits to https://github.com/neggles
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# See https://github.com/huggingface/diffusers/issues/4167 for more details on sched mapping from A1111
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class DiffusionScheduler(str, Enum):
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ddim = "ddim" # DDIM
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pndm = "pndm" # PNDM
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heun = "heun" # Heun
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unipc = "unipc" # UniPC
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euler = "euler" # Euler
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euler_a = "euler_a" # Euler a
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lms = "lms" # LMS
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k_lms = "k_lms" # LMS Karras
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dpm_2 = "dpm_2" # DPM2
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k_dpm_2 = "k_dpm_2" # DPM2 Karras
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dpm_2_a = "dpm_2_a" # DPM2 a
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k_dpm_2_a = "k_dpm_2_a" # DPM2 a Karras
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dpmpp_2m = "dpmpp_2m" # DPM++ 2M
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k_dpmpp_2m = "k_dpmpp_2m" # DPM++ 2M Karras
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dpmpp_sde = "dpmpp_sde" # DPM++ SDE
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k_dpmpp_sde = "k_dpmpp_sde" # DPM++ SDE Karras
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dpmpp_2m_sde = "dpmpp_2m_sde" # DPM++ 2M SDE
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k_dpmpp_2m_sde = "k_dpmpp_2m_sde" # DPM++ 2M SDE Karras
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def get_scheduler(name: str, config: dict = {}):
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is_karras = name.startswith("k_")
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if is_karras:
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# strip the k_ prefix and add the karras sigma flag to config
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name = name.lstrip("k_")
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config["use_karras_sigmas"] = True
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if name == DiffusionScheduler.ddim:
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sched_class = DDIMScheduler
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elif name == DiffusionScheduler.pndm:
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sched_class = PNDMScheduler
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elif name == DiffusionScheduler.heun:
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sched_class = HeunDiscreteScheduler
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elif name == DiffusionScheduler.unipc:
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sched_class = UniPCMultistepScheduler
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elif name == DiffusionScheduler.euler:
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sched_class = EulerDiscreteScheduler
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elif name == DiffusionScheduler.euler_a:
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sched_class = EulerAncestralDiscreteScheduler
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elif name == DiffusionScheduler.lms:
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sched_class = LMSDiscreteScheduler
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elif name == DiffusionScheduler.dpm_2:
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# Equivalent to DPM2 in K-Diffusion
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sched_class = KDPM2DiscreteScheduler
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elif name == DiffusionScheduler.dpm_2_a:
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# Equivalent to `DPM2 a`` in K-Diffusion
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sched_class = KDPM2AncestralDiscreteScheduler
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elif name == DiffusionScheduler.dpmpp_2m:
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# Equivalent to `DPM++ 2M` in K-Diffusion
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sched_class = DPMSolverMultistepScheduler
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config["algorithm_type"] = "dpmsolver++"
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config["solver_order"] = 2
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elif name == DiffusionScheduler.dpmpp_sde:
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# Equivalent to `DPM++ SDE` in K-Diffusion
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sched_class = DPMSolverSinglestepScheduler
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elif name == DiffusionScheduler.dpmpp_2m_sde:
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# Equivalent to `DPM++ 2M SDE` in K-Diffusion
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sched_class = DPMSolverMultistepScheduler
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config["algorithm_type"] = "sde-dpmsolver++"
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else:
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raise ValueError(f"Invalid scheduler '{'k_' if is_karras else ''}{name}'")
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return sched_class.from_config(config)
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# Implement the BackendServicer class with the service methods
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class BackendServicer(backend_pb2_grpc.BackendServicer):
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def Health(self, request, context):
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@ -42,39 +135,55 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
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cfg_scale = 7
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if request.CFGScale != 0:
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cfg_scale = request.CFGScale
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clipmodel = "runwayml/stable-diffusion-v1-5"
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if request.CLIPModel != "":
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clipmodel = request.CLIPModel
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clipsubfolder = "text_encoder"
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if request.CLIPSubfolder != "":
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clipsubfolder = request.CLIPSubfolder
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# Check if ModelFile exists
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if request.ModelFile != "":
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if os.path.exists(request.ModelFile):
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local = True
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modelFile = request.ModelFile
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fromSingleFile = request.Model.startswith("http") or request.Model.startswith("/") or local
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# If request.Model is a URL, use from_single_file
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if request.PipelineType == "":
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request.PipelineType == "StableDiffusionPipeline"
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if request.PipelineType == "StableDiffusionPipeline":
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if fromSingleFile:
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self.pipe = StableDiffusionPipeline.from_single_file(modelFile,
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torch_dtype=torchType,
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guidance_scale=cfg_scale)
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if request.IMG2IMG:
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self.pipe = StableDiffusionImg2ImgPipeline.from_single_file(modelFile,
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torch_dtype=torchType,
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guidance_scale=cfg_scale)
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else:
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self.pipe = StableDiffusionPipeline.from_single_file(modelFile,
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torch_dtype=torchType,
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guidance_scale=cfg_scale)
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else:
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self.pipe = StableDiffusionPipeline.from_pretrained(request.Model,
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torch_dtype=torchType,
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guidance_scale=cfg_scale)
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if request.IMG2IMG:
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self.pipe = StableDiffusionImg2ImgPipeline.from_pretrained(request.Model,
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torch_dtype=torchType,
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guidance_scale=cfg_scale)
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else:
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self.pipe = StableDiffusionPipeline.from_pretrained(request.Model,
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torch_dtype=torchType,
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guidance_scale=cfg_scale)
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# https://github.com/huggingface/diffusers/issues/4446
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# do not use text_encoder in the constructor since then
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# https://github.com/huggingface/diffusers/issues/3212#issuecomment-1521841481
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if CLIPSKIP and request.CLIPSkip != 0:
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text_encoder = CLIPTextModel.from_pretrained(clipmodel, num_hidden_layers=request.CLIPSkip, subfolder=clipsubfolder, torch_dtype=torchType)
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self.pipe.text_encoder=text_encoder
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if request.PipelineType == "DiffusionPipeline":
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if fromSingleFile:
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self.pipe = DiffusionPipeline.from_single_file(modelFile,
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torch_dtype=torchType,
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guidance_scale=cfg_scale)
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else:
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self.pipe = DiffusionPipeline.from_pretrained(request.Model,
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torch_dtype=torchType,
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guidance_scale=cfg_scale)
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self.pipe = DiffusionPipeline.from_pretrained(request.Model,
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torch_dtype=torchType,
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guidance_scale=cfg_scale)
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if request.PipelineType == "StableDiffusionXLPipeline":
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if fromSingleFile:
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@ -91,17 +200,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
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# torch_dtype needs to be customized. float16 for GPU, float32 for CPU
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# TODO: this needs to be customized
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if request.SchedulerType == "EulerAncestralDiscreteScheduler":
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self.pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(self.pipe.scheduler.config)
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if request.SchedulerType == "DPMSolverMultistepScheduler":
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self.pipe.scheduler = DPMSolverMultistepScheduler.from_config(self.pipe.scheduler.config)
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if request.SchedulerType == "DPMSolverMultistepScheduler++":
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self.pipe.scheduler = DPMSolverMultistepScheduler.from_config(self.pipe.scheduler.config,algorithm_type="dpmsolver++")
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if request.SchedulerType == "DPMSolverMultistepSchedulerSDE++":
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self.pipe.scheduler = DPMSolverMultistepScheduler.from_config(self.pipe.scheduler.config, algorithm_type="sde-dpmsolver++")
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if request.CUDA:
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self.pipe.to('cuda')
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self.pipe.scheduler = get_scheduler(request.SchedulerType, self.pipe.scheduler.config)
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self.compel = Compel(tokenizer=self.pipe.tokenizer, text_encoder=self.pipe.text_encoder)
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except Exception as err:
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return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
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@ -117,9 +216,17 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
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"negative_prompt": request.negative_prompt,
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"width": request.width,
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"height": request.height,
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"num_inference_steps": request.step
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"num_inference_steps": request.step,
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}
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if request.src != "":
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# open the image with Image.open
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# convert the image to RGB
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# resize the image to the request width and height
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# XXX: untested
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image = Image.open(request.src).convert("RGB").resize((request.width, request.height))
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options["image"] = image
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# Get the keys that we will build the args for our pipe for
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keys = options.keys()
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@ -131,6 +238,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
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# create a dictionary of parameters by using the keys from EnableParameters and the values from defaults
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kwargs = {key: options[key] for key in keys}
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image = {}
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if COMPEL:
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conditioning = self.compel.build_conditioning_tensor(prompt)
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File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@ -494,6 +494,10 @@ type ModelOptions struct {
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SchedulerType string `protobuf:"bytes,27,opt,name=SchedulerType,proto3" json:"SchedulerType,omitempty"`
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CUDA bool `protobuf:"varint,28,opt,name=CUDA,proto3" json:"CUDA,omitempty"`
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CFGScale float32 `protobuf:"fixed32,29,opt,name=CFGScale,proto3" json:"CFGScale,omitempty"`
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IMG2IMG bool `protobuf:"varint,30,opt,name=IMG2IMG,proto3" json:"IMG2IMG,omitempty"`
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CLIPModel string `protobuf:"bytes,31,opt,name=CLIPModel,proto3" json:"CLIPModel,omitempty"`
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CLIPSubfolder string `protobuf:"bytes,32,opt,name=CLIPSubfolder,proto3" json:"CLIPSubfolder,omitempty"`
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CLIPSkip int32 `protobuf:"varint,33,opt,name=CLIPSkip,proto3" json:"CLIPSkip,omitempty"`
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}
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func (x *ModelOptions) Reset() {
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@ -731,6 +735,34 @@ func (x *ModelOptions) GetCFGScale() float32 {
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return 0
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}
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func (x *ModelOptions) GetIMG2IMG() bool {
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if x != nil {
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return x.IMG2IMG
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}
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return false
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}
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func (x *ModelOptions) GetCLIPModel() string {
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if x != nil {
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return x.CLIPModel
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}
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return ""
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}
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func (x *ModelOptions) GetCLIPSubfolder() string {
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if x != nil {
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return x.CLIPSubfolder
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}
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return ""
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}
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func (x *ModelOptions) GetCLIPSkip() int32 {
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if x != nil {
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return x.CLIPSkip
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}
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return 0
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}
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type Result struct {
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state protoimpl.MessageState
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sizeCache protoimpl.SizeCache
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||||
@ -1043,8 +1075,10 @@ type GenerateImageRequest struct {
|
||||
PositivePrompt string `protobuf:"bytes,6,opt,name=positive_prompt,json=positivePrompt,proto3" json:"positive_prompt,omitempty"`
|
||||
NegativePrompt string `protobuf:"bytes,7,opt,name=negative_prompt,json=negativePrompt,proto3" json:"negative_prompt,omitempty"`
|
||||
Dst string `protobuf:"bytes,8,opt,name=dst,proto3" json:"dst,omitempty"`
|
||||
Src string `protobuf:"bytes,9,opt,name=src,proto3" json:"src,omitempty"`
|
||||
// Diffusers
|
||||
EnableParameters string `protobuf:"bytes,9,opt,name=EnableParameters,proto3" json:"EnableParameters,omitempty"`
|
||||
EnableParameters string `protobuf:"bytes,10,opt,name=EnableParameters,proto3" json:"EnableParameters,omitempty"`
|
||||
CLIPSkip int32 `protobuf:"varint,11,opt,name=CLIPSkip,proto3" json:"CLIPSkip,omitempty"`
|
||||
}
|
||||
|
||||
func (x *GenerateImageRequest) Reset() {
|
||||
@ -1135,6 +1169,13 @@ func (x *GenerateImageRequest) GetDst() string {
|
||||
return ""
|
||||
}
|
||||
|
||||
func (x *GenerateImageRequest) GetSrc() string {
|
||||
if x != nil {
|
||||
return x.Src
|
||||
}
|
||||
return ""
|
||||
}
|
||||
|
||||
func (x *GenerateImageRequest) GetEnableParameters() string {
|
||||
if x != nil {
|
||||
return x.EnableParameters
|
||||
@ -1142,6 +1183,13 @@ func (x *GenerateImageRequest) GetEnableParameters() string {
|
||||
return ""
|
||||
}
|
||||
|
||||
func (x *GenerateImageRequest) GetCLIPSkip() int32 {
|
||||
if x != nil {
|
||||
return x.CLIPSkip
|
||||
}
|
||||
return 0
|
||||
}
|
||||
|
||||
type TTSRequest struct {
|
||||
state protoimpl.MessageState
|
||||
sizeCache protoimpl.SizeCache
|
||||
@ -1290,7 +1338,7 @@ var file_pkg_grpc_proto_backend_proto_rawDesc = []byte{
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@ -1344,93 +1392,103 @@ var file_pkg_grpc_proto_backend_proto_rawDesc = []byte{
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}
|
||||
|
||||
var (
|
||||
|
||||
@ -102,6 +102,10 @@ message ModelOptions {
|
||||
string SchedulerType = 27;
|
||||
bool CUDA = 28;
|
||||
float CFGScale = 29;
|
||||
bool IMG2IMG = 30;
|
||||
string CLIPModel = 31;
|
||||
string CLIPSubfolder = 32;
|
||||
int32 CLIPSkip = 33;
|
||||
}
|
||||
|
||||
message Result {
|
||||
@ -141,9 +145,11 @@ message GenerateImageRequest {
|
||||
string positive_prompt = 6;
|
||||
string negative_prompt = 7;
|
||||
string dst = 8;
|
||||
string src = 9;
|
||||
|
||||
// Diffusers
|
||||
string EnableParameters = 9;
|
||||
string EnableParameters = 10;
|
||||
int32 CLIPSkip = 11;
|
||||
}
|
||||
|
||||
message TTSRequest {
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user