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Merge branch 'main' into feat/compel_node

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This commit is contained in:
StAlKeR7779
2023-05-04 00:28:33 +03:00
committed by GitHub
parent 0b0068ab86 5e8c97f1ba
commit 56d3cbead0
329 changed files with 6233 additions and 5270 deletions
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4
invokeai/app/services/default_graphs.py
View File

@@ -27,10 +27,6 @@ def create_text_to_image() -> LibraryGraph:
Edge(source=EdgeConnection(node_id='width', field='a'), destination=EdgeConnection(node_id='3', field='width')),
Edge(source=EdgeConnection(node_id='height', field='a'), destination=EdgeConnection(node_id='3', field='height')),
Edge(source=EdgeConnection(node_id='seed', field='a'), destination=EdgeConnection(node_id='3', field='seed')),
# TODO: remove, when updated TextToLatents merged
Edge(source=EdgeConnection(node_id='width', field='a'), destination=EdgeConnection(node_id='5', field='width')),
Edge(source=EdgeConnection(node_id='height', field='a'), destination=EdgeConnection(node_id='5', field='height')),
Edge(source=EdgeConnection(node_id='seed', field='a'), destination=EdgeConnection(node_id='5', field='seed')),
Edge(source=EdgeConnection(node_id='3', field='noise'), destination=EdgeConnection(node_id='5', field='noise')),
Edge(source=EdgeConnection(node_id='5', field='latents'), destination=EdgeConnection(node_id='6', field='latents')),
Edge(source=EdgeConnection(node_id='4', field='positive'), destination=EdgeConnection(node_id='5', field='positive')),

6
invokeai/app/services/invocation_services.py
View File

@@ -1,4 +1,6 @@
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
from typing import types
from invokeai.app.services.metadata import MetadataServiceBase
from invokeai.backend import ModelManager
@@ -29,6 +31,7 @@ class InvocationServices:
self,
model_manager: ModelManager,
events: EventServiceBase,
logger: types.ModuleType,
latents: LatentsStorageBase,
images: ImageStorageBase,
metadata: MetadataServiceBase,
@@ -40,6 +43,7 @@ class InvocationServices:
):
self.model_manager = model_manager
self.events = events
self.logger = logger
self.latents = latents
self.images = images
self.metadata = metadata

8
invokeai/app/services/invoker.py
View File

@@ -49,7 +49,7 @@ class Invoker:
new_state = GraphExecutionState(graph=Graph() if graph is None else graph)
self.services.graph_execution_manager.set(new_state)
return new_state
def cancel(self, graph_execution_state_id: str) -> None:
"""Cancels the given execution state"""
self.services.queue.cancel(graph_execution_state_id)
@@ -71,18 +71,12 @@ class Invoker:
for service in vars(self.services):
self.__start_service(getattr(self.services, service))
for service in vars(self.services):
self.__start_service(getattr(self.services, service))
def stop(self) -> None:
"""Stops the invoker. A new invoker will have to be created to execute further."""
# First stop all services
for service in vars(self.services):
self.__stop_service(getattr(self.services, service))
for service in vars(self.services):
self.__stop_service(getattr(self.services, service))
self.services.queue.put(None)

31
invokeai/app/services/model_manager_initializer.py
View File

@@ -5,6 +5,7 @@ from argparse import Namespace
from invokeai.backend import Args
from omegaconf import OmegaConf
from pathlib import Path
from typing import types
import invokeai.version
from ...backend import ModelManager
@@ -12,16 +13,16 @@ from ...backend.util import choose_precision, choose_torch_device
from ...backend import Globals
# TODO: Replace with an abstract class base ModelManagerBase
def get_model_manager(config: Args) -> ModelManager:
def get_model_manager(config: Args, logger: types.ModuleType) -> ModelManager:
if not config.conf:
config_file = os.path.join(Globals.root, "configs", "models.yaml")
if not os.path.exists(config_file):
report_model_error(
config, FileNotFoundError(f"The file {config_file} could not be found.")
config, FileNotFoundError(f"The file {config_file} could not be found."), logger
)
print(f">> {invokeai.version.__app_name__}, version {invokeai.version.__version__}")
print(f'>> InvokeAI runtime directory is "{Globals.root}"')
logger.info(f"{invokeai.version.__app_name__}, version {invokeai.version.__version__}")
logger.info(f'InvokeAI runtime directory is "{Globals.root}"')
# these two lines prevent a horrible warning message from appearing
# when the frozen CLIP tokenizer is imported
@@ -62,11 +63,12 @@ def get_model_manager(config: Args) -> ModelManager:
device_type=device,
max_loaded_models=config.max_loaded_models,
embedding_path = Path(embedding_path),
logger = logger,
)
except (FileNotFoundError, TypeError, AssertionError) as e:
report_model_error(config, e)
report_model_error(config, e, logger)
except (IOError, KeyError) as e:
print(f"{e}. Aborting.")
logger.error(f"{e}. Aborting.")
sys.exit(-1)
# try to autoconvert new models
@@ -76,18 +78,18 @@ def get_model_manager(config: Args) -> ModelManager:
conf_path=config.conf,
weights_directory=path,
)
logger.info('Model manager initialized')
return model_manager
def report_model_error(opt: Namespace, e: Exception):
print(f'** An error occurred while attempting to initialize the model: "{str(e)}"')
print(
"** This can be caused by a missing or corrupted models file, and can sometimes be fixed by (re)installing the models."
def report_model_error(opt: Namespace, e: Exception, logger: types.ModuleType):
logger.error(f'An error occurred while attempting to initialize the model: "{str(e)}"')
logger.error(
"This can be caused by a missing or corrupted models file, and can sometimes be fixed by (re)installing the models."
)
yes_to_all = os.environ.get("INVOKE_MODEL_RECONFIGURE")
if yes_to_all:
print(
"** Reconfiguration is being forced by environment variable INVOKE_MODEL_RECONFIGURE"
logger.warning(
"Reconfiguration is being forced by environment variable INVOKE_MODEL_RECONFIGURE"
)
else:
response = input(
@@ -96,13 +98,12 @@ def report_model_error(opt: Namespace, e: Exception):
if response.startswith(("n", "N")):
return
print("invokeai-configure is launching....\n")
logger.info("invokeai-configure is launching....\n")
# Match arguments that were set on the CLI
# only the arguments accepted by the configuration script are parsed
root_dir = ["--root", opt.root_dir] if opt.root_dir is not None else []
config = ["--config", opt.conf] if opt.conf is not None else []
previous_config = sys.argv
sys.argv = ["invokeai-configure"]
sys.argv.extend(root_dir)
sys.argv.extend(config.to_dict())

14
invokeai/app/services/processor.py
View File

@@ -1,5 +1,5 @@
import traceback
from threading import Event, Thread
from threading import Event, Thread, BoundedSemaphore
from ..invocations.baseinvocation import InvocationContext
from .invocation_queue import InvocationQueueItem
@@ -10,8 +10,11 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
__invoker_thread: Thread
__stop_event: Event
__invoker: Invoker
__threadLimit: BoundedSemaphore
def start(self, invoker) -> None:
# if we do want multithreading at some point, we could make this configurable
self.__threadLimit = BoundedSemaphore(1)
self.__invoker = invoker
self.__stop_event = Event()
self.__invoker_thread = Thread(
@@ -20,7 +23,7 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
kwargs=dict(stop_event=self.__stop_event),
)
self.__invoker_thread.daemon = (
True # TODO: probably better to just not use threads?
True # TODO: make async and do not use threads
)
self.__invoker_thread.start()
@@ -29,6 +32,7 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
def __process(self, stop_event: Event):
try:
self.__threadLimit.acquire()
while not stop_event.is_set():
queue_item: InvocationQueueItem = self.__invoker.services.queue.get()
if not queue_item: # Probably stopping
@@ -110,7 +114,7 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
)
pass
# Check queue to see if this is canceled, and skip if so
if self.__invoker.services.queue.is_canceled(
graph_execution_state.id
@@ -127,4 +131,6 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
)
except KeyboardInterrupt:
... # Log something?
pass # Log something? KeyboardInterrupt is probably not going to be seen by the processor
finally:
self.__threadLimit.release()

29
invokeai/app/services/restoration_services.py
View File

@@ -1,6 +1,7 @@
import sys
import traceback
import torch
from typing import types
from ...backend.restoration import Restoration
from ...backend.util import choose_torch_device, CPU_DEVICE, MPS_DEVICE
@@ -10,7 +11,7 @@ from ...backend.util import choose_torch_device, CPU_DEVICE, MPS_DEVICE
class RestorationServices:
'''Face restoration and upscaling'''
def __init__(self,args):
def __init__(self,args,logger:types.ModuleType):
try:
gfpgan, codeformer, esrgan = None, None, None
if args.restore or args.esrgan:
@@ -20,20 +21,22 @@ class RestorationServices:
args.gfpgan_model_path
)
else:
print(">> Face restoration disabled")
logger.info("Face restoration disabled")
if args.esrgan:
esrgan = restoration.load_esrgan(args.esrgan_bg_tile)
else:
print(">> Upscaling disabled")
logger.info("Upscaling disabled")
else:
print(">> Face restoration and upscaling disabled")
logger.info("Face restoration and upscaling disabled")
except (ModuleNotFoundError, ImportError):
print(traceback.format_exc(), file=sys.stderr)
print(">> You may need to install the ESRGAN and/or GFPGAN modules")
logger.info("You may need to install the ESRGAN and/or GFPGAN modules")
self.device = torch.device(choose_torch_device())
self.gfpgan = gfpgan
self.codeformer = codeformer
self.esrgan = esrgan
self.logger = logger
self.logger.info('Face restoration initialized')
# note that this one method does gfpgan and codepath reconstruction, as well as
# esrgan upscaling
@@ -58,15 +61,15 @@ class RestorationServices:
if self.gfpgan is not None or self.codeformer is not None:
if facetool == "gfpgan":
if self.gfpgan is None:
print(
">> GFPGAN not found. Face restoration is disabled."
self.logger.info(
"GFPGAN not found. Face restoration is disabled."
)
else:
image = self.gfpgan.process(image, strength, seed)
if facetool == "codeformer":
if self.codeformer is None:
print(
">> CodeFormer not found. Face restoration is disabled."
self.logger.info(
"CodeFormer not found. Face restoration is disabled."
)
else:
cf_device = (
@@ -80,7 +83,7 @@ class RestorationServices:
fidelity=codeformer_fidelity,
)
else:
print(">> Face Restoration is disabled.")
self.logger.info("Face Restoration is disabled.")
if upscale is not None:
if self.esrgan is not None:
if len(upscale) < 2:
@@ -93,10 +96,10 @@ class RestorationServices:
denoise_str=upscale_denoise_str,
)
else:
print(">> ESRGAN is disabled. Image not upscaled.")
self.logger.info("ESRGAN is disabled. Image not upscaled.")
except Exception as e:
print(
f">> Error running RealESRGAN or GFPGAN. Your image was not upscaled.\n{e}"
self.logger.info(
f"Error running RealESRGAN or GFPGAN. Your image was not upscaled.\n{e}"
)
if image_callback is not None: