From 149784202cca8612b43629c601ee27cfda64e623 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 30 Oct 2022 09:10:22 +0300 Subject: [PATCH] rework #3722 to not introduce duplicate code --- modules/api/api.py | 43 +++++++++++++------------------------------ modules/shared.py | 22 +++++++++++++++++++--- webui.py | 17 ++--------------- 3 files changed, 34 insertions(+), 48 deletions(-) diff --git a/modules/api/api.py b/modules/api/api.py index 5c5b210f5..6c06d4499 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -9,31 +9,6 @@ from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusion from modules.sd_samplers import all_samplers from modules.extras import run_extras, run_pnginfo -# copy from wrap_gradio_gpu_call of webui.py -# because queue lock will be acquired in api handlers -# and time start needs to be set -# the function has been modified into two parts - -def before_gpu_call(): - devices.torch_gc() - - shared.state.sampling_step = 0 - shared.state.job_count = -1 - shared.state.job_no = 0 - shared.state.job_timestamp = shared.state.get_job_timestamp() - shared.state.current_latent = None - shared.state.current_image = None - shared.state.current_image_sampling_step = 0 - shared.state.skipped = False - shared.state.interrupted = False - shared.state.textinfo = None - shared.state.time_start = time.time() - -def after_gpu_call(): - shared.state.job = "" - shared.state.job_count = 0 - - devices.torch_gc() def upscaler_to_index(name: str): try: @@ -41,8 +16,10 @@ def upscaler_to_index(name: str): except: raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be on of these: {' , '.join([x.name for x in sd_upscalers])}") + sampler_to_index = lambda name: next(filter(lambda row: name.lower() == row[1].name.lower(), enumerate(all_samplers)), None) + def setUpscalers(req: dict): reqDict = vars(req) reqDict['extras_upscaler_1'] = upscaler_to_index(req.upscaler_1) @@ -51,6 +28,7 @@ def setUpscalers(req: dict): reqDict.pop('upscaler_2') return reqDict + class Api: def __init__(self, app, queue_lock): self.router = APIRouter() @@ -78,10 +56,13 @@ class Api: ) p = StableDiffusionProcessingTxt2Img(**vars(populate)) # Override object param - before_gpu_call() + + shared.state.begin() + with self.queue_lock: processed = process_images(p) - after_gpu_call() + + shared.state.end() b64images = list(map(encode_pil_to_base64, processed.images)) @@ -119,11 +100,13 @@ class Api: imgs = [img] * p.batch_size p.init_images = imgs - # Override object param - before_gpu_call() + + shared.state.begin() + with self.queue_lock: processed = process_images(p) - after_gpu_call() + + shared.state.end() b64images = list(map(encode_pil_to_base64, processed.images)) diff --git a/modules/shared.py b/modules/shared.py index f7b0990c5..e4f163c11 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -144,9 +144,6 @@ class State: self.sampling_step = 0 self.current_image_sampling_step = 0 - def get_job_timestamp(self): - return datetime.datetime.now().strftime("%Y%m%d%H%M%S") # shouldn't this return job_timestamp? - def dict(self): obj = { "skipped": self.skipped, @@ -160,6 +157,25 @@ class State: return obj + def begin(self): + self.sampling_step = 0 + self.job_count = -1 + self.job_no = 0 + self.job_timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S") + self.current_latent = None + self.current_image = None + self.current_image_sampling_step = 0 + self.skipped = False + self.interrupted = False + self.textinfo = None + + devices.torch_gc() + + def end(self): + self.job = "" + self.job_count = 0 + + devices.torch_gc() state = State() diff --git a/webui.py b/webui.py index ade7334bf..29530872c 100644 --- a/webui.py +++ b/webui.py @@ -46,26 +46,13 @@ def wrap_queued_call(func): def wrap_gradio_gpu_call(func, extra_outputs=None): def f(*args, **kwargs): - devices.torch_gc() - shared.state.sampling_step = 0 - shared.state.job_count = -1 - shared.state.job_no = 0 - shared.state.job_timestamp = shared.state.get_job_timestamp() - shared.state.current_latent = None - shared.state.current_image = None - shared.state.current_image_sampling_step = 0 - shared.state.skipped = False - shared.state.interrupted = False - shared.state.textinfo = None + shared.state.begin() with queue_lock: res = func(*args, **kwargs) - shared.state.job = "" - shared.state.job_count = 0 - - devices.torch_gc() + shared.state.end() return res