Merge pull request #3722 from evshiron/feat/progress-api
prototype progress api
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commit
060ee5d3a7
@ -1,12 +1,40 @@
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import time
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import uvicorn
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from gradio.processing_utils import encode_pil_to_base64, decode_base64_to_file, decode_base64_to_image
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from fastapi import APIRouter, HTTPException
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from fastapi import APIRouter, Depends, HTTPException
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import modules.shared as shared
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from modules import devices
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from modules.api.models import *
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from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
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from modules.sd_samplers import all_samplers
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from modules.extras import run_extras, run_pnginfo
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# copy from wrap_gradio_gpu_call of webui.py
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# because queue lock will be acquired in api handlers
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# and time start needs to be set
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# the function has been modified into two parts
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def before_gpu_call():
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devices.torch_gc()
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shared.state.sampling_step = 0
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shared.state.job_count = -1
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shared.state.job_no = 0
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shared.state.job_timestamp = shared.state.get_job_timestamp()
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shared.state.current_latent = None
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shared.state.current_image = None
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shared.state.current_image_sampling_step = 0
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shared.state.skipped = False
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shared.state.interrupted = False
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shared.state.textinfo = None
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shared.state.time_start = time.time()
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def after_gpu_call():
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shared.state.job = ""
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shared.state.job_count = 0
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devices.torch_gc()
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def upscaler_to_index(name: str):
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try:
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return [x.name.lower() for x in shared.sd_upscalers].index(name.lower())
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@ -33,6 +61,7 @@ class Api:
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self.app.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=ExtrasSingleImageResponse)
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self.app.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=ExtrasBatchImagesResponse)
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self.app.add_api_route("/sdapi/v1/png-info", self.pnginfoapi, methods=["POST"], response_model=PNGInfoResponse)
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self.app.add_api_route("/sdapi/v1/progress", self.progressapi, methods=["GET"], response_model=ProgressResponse)
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def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
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sampler_index = sampler_to_index(txt2imgreq.sampler_index)
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@ -49,8 +78,10 @@ class Api:
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)
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p = StableDiffusionProcessingTxt2Img(**vars(populate))
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# Override object param
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before_gpu_call()
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with self.queue_lock:
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processed = process_images(p)
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after_gpu_call()
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b64images = list(map(encode_pil_to_base64, processed.images))
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@ -89,8 +120,10 @@ class Api:
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p.init_images = imgs
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# Override object param
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before_gpu_call()
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with self.queue_lock:
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processed = process_images(p)
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after_gpu_call()
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b64images = list(map(encode_pil_to_base64, processed.images))
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@ -134,6 +167,32 @@ class Api:
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return PNGInfoResponse(info=result[1])
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def progressapi(self, req: ProgressRequest = Depends()):
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# copy from check_progress_call of ui.py
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if shared.state.job_count == 0:
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return ProgressResponse(progress=0, eta_relative=0, state=shared.state.dict())
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# avoid dividing zero
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progress = 0.01
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if shared.state.job_count > 0:
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progress += shared.state.job_no / shared.state.job_count
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if shared.state.sampling_steps > 0:
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progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps
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time_since_start = time.time() - shared.state.time_start
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eta = (time_since_start/progress)
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eta_relative = eta-time_since_start
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progress = min(progress, 1)
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current_image = None
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if shared.state.current_image and not req.skip_current_image:
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current_image = encode_pil_to_base64(shared.state.current_image)
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return ProgressResponse(progress=progress, eta_relative=eta_relative, state=shared.state.dict(), current_image=current_image)
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def launch(self, server_name, port):
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self.app.include_router(self.router)
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uvicorn.run(self.app, host=server_name, port=port)
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@ -156,3 +156,12 @@ class PNGInfoRequest(BaseModel):
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class PNGInfoResponse(BaseModel):
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info: str = Field(title="Image info", description="A string with all the info the image had")
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class ProgressRequest(BaseModel):
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skip_current_image: bool = Field(default=False, title="Skip current image", description="Skip current image serialization")
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class ProgressResponse(BaseModel):
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progress: float = Field(title="Progress", description="The progress with a range of 0 to 1")
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eta_relative: float = Field(title="ETA in secs")
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state: dict = Field(title="State", description="The current state snapshot")
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current_image: str = Field(default=None, title="Current image", description="The current image in base64 format. opts.show_progress_every_n_steps is required for this to work.")
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@ -147,6 +147,19 @@ class State:
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def get_job_timestamp(self):
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return datetime.datetime.now().strftime("%Y%m%d%H%M%S") # shouldn't this return job_timestamp?
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def dict(self):
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obj = {
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"skipped": self.skipped,
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"interrupted": self.skipped,
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"job": self.job,
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"job_count": self.job_count,
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"job_no": self.job_no,
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"sampling_step": self.sampling_step,
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"sampling_steps": self.sampling_steps,
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}
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return obj
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state = State()
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