from argparse import Namespace import os import sys import traceback from ...model_manager import ModelManager from ...globals import Globals from ....generate import Generate import ldm.invoke # TODO: most of this code should be split into individual services as the Generate.py code is deprecated def get_generate(args, config) -> Generate: if not args.conf: config_file = os.path.join(Globals.root,'configs','models.yaml') if not os.path.exists(config_file): report_model_error(args, FileNotFoundError(f"The file {config_file} could not be found.")) print(f'>> {ldm.invoke.__app_name__}, version {ldm.invoke.__version__}') print(f'>> InvokeAI runtime directory is "{Globals.root}"') # these two lines prevent a horrible warning message from appearing # when the frozen CLIP tokenizer is imported import transformers # type: ignore transformers.logging.set_verbosity_error() import diffusers diffusers.logging.set_verbosity_error() # Loading Face Restoration and ESRGAN Modules gfpgan,codeformer,esrgan = load_face_restoration(args) # normalize the config directory relative to root if not os.path.isabs(args.conf): args.conf = os.path.normpath(os.path.join(Globals.root,args.conf)) if args.embeddings: if not os.path.isabs(args.embedding_path): embedding_path = os.path.normpath(os.path.join(Globals.root,args.embedding_path)) else: embedding_path = args.embedding_path else: embedding_path = None # migrate legacy models ModelManager.migrate_models() # load the infile as a list of lines if args.infile: try: if os.path.isfile(args.infile): infile = open(args.infile, 'r', encoding='utf-8') elif args.infile == '-': # stdin infile = sys.stdin else: raise FileNotFoundError(f'{args.infile} not found.') except (FileNotFoundError, IOError) as e: print(f'{e}. Aborting.') sys.exit(-1) # creating a Generate object: try: gen = Generate( conf = args.conf, model = args.model, sampler_name = args.sampler_name, embedding_path = embedding_path, full_precision = args.full_precision, precision = args.precision, gfpgan = gfpgan, codeformer = codeformer, esrgan = esrgan, free_gpu_mem = args.free_gpu_mem, safety_checker = args.safety_checker, max_loaded_models = args.max_loaded_models, ) except (FileNotFoundError, TypeError, AssertionError) as e: report_model_error(opt,e) except (IOError, KeyError) as e: print(f'{e}. Aborting.') sys.exit(-1) if args.seamless: print(">> changed to seamless tiling mode") # preload the model try: gen.load_model() except KeyError: pass except Exception as e: report_model_error(args, e) # try to autoconvert new models # autoimport new .ckpt files if path := args.autoconvert: gen.model_manager.autoconvert_weights( conf_path=args.conf, weights_directory=path, ) return gen def load_face_restoration(opt): try: gfpgan, codeformer, esrgan = None, None, None if opt.restore or opt.esrgan: from ldm.invoke.restoration import Restoration restoration = Restoration() if opt.restore: gfpgan, codeformer = restoration.load_face_restore_models(opt.gfpgan_model_path) else: print('>> Face restoration disabled') if opt.esrgan: esrgan = restoration.load_esrgan(opt.esrgan_bg_tile) else: print('>> Upscaling disabled') else: print('>> 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') return gfpgan,codeformer,esrgan 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.') yes_to_all = os.environ.get('INVOKE_MODEL_RECONFIGURE') if yes_to_all: print('** Reconfiguration is being forced by environment variable INVOKE_MODEL_RECONFIGURE') else: response = input('Do you want to run invokeai-configure script to select and/or reinstall models? [y] ') if response.startswith(('n', 'N')): return print('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_args = sys.argv sys.argv = [ 'invokeai-configure' ] sys.argv.extend(root_dir) sys.argv.extend(config) if yes_to_all is not None: for arg in yes_to_all.split(): sys.argv.append(arg) from ldm.invoke.config import invokeai_configure invokeai_configure.main() # TODO: Figure out how to restart # print('** InvokeAI will now restart') # sys.argv = previous_args # main() # would rather do a os.exec(), but doesn't exist? # sys.exit(0) # Temporary initializer for Generate until we migrate off of it def old_get_generate(args, config) -> Generate: # TODO: Remove the need for globals from ldm.invoke.globals import Globals # alert - setting globals here Globals.root = os.path.expanduser(args.root_dir or os.environ.get('INVOKEAI_ROOT') or os.path.abspath('.')) Globals.try_patchmatch = args.patchmatch print(f'>> InvokeAI runtime directory is "{Globals.root}"') # these two lines prevent a horrible warning message from appearing # when the frozen CLIP tokenizer is imported import transformers transformers.logging.set_verbosity_error() # Loading Face Restoration and ESRGAN Modules gfpgan, codeformer, esrgan = None, None, None try: if config.restore or config.esrgan: from ldm.invoke.restoration import Restoration restoration = Restoration() if config.restore: gfpgan, codeformer = restoration.load_face_restore_models(config.gfpgan_model_path) else: print('>> Face restoration disabled') if config.esrgan: esrgan = restoration.load_esrgan(config.esrgan_bg_tile) else: print('>> Upscaling disabled') else: print('>> 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') # normalize the config directory relative to root if not os.path.isabs(config.conf): config.conf = os.path.normpath(os.path.join(Globals.root,config.conf)) if config.embeddings: if not os.path.isabs(config.embedding_path): embedding_path = os.path.normpath(os.path.join(Globals.root,config.embedding_path)) else: embedding_path = None # TODO: lazy-initialize this by wrapping it try: generate = Generate( conf = config.conf, model = config.model, sampler_name = config.sampler_name, embedding_path = embedding_path, full_precision = config.full_precision, precision = config.precision, gfpgan = gfpgan, codeformer = codeformer, esrgan = esrgan, free_gpu_mem = config.free_gpu_mem, safety_checker = config.safety_checker, max_loaded_models = config.max_loaded_models, ) except (FileNotFoundError, TypeError, AssertionError): #emergency_model_reconfigure() # TODO? sys.exit(-1) except (IOError, KeyError) as e: print(f'{e}. Aborting.') sys.exit(-1) generate.free_gpu_mem = config.free_gpu_mem return generate