mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
mostly working
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fe318775c3
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@ -243,7 +243,7 @@ class addModelsForm(npyscreen.FormMultiPageAction):
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# URLs and the like
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self.parentApp.import_model_paths = self.import_model_paths.value.split()
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self.parentApp.convert_to_diffusers = self.convert_models.value != 0
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self.parentApp.convert_to_diffusers = self.convert_models.value == 1
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# big chunk of dead code
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# was intended to be a status area in which output of installation steps (including tqdm) was logged in real time
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@ -68,8 +68,8 @@ def install_requested_models(
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purge_deleted: bool = False,
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config_file_path: Path = None,
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):
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config_file_path =config_file_path or default_config_file()
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model_manager = ModelManager(OmegaConf.load(config_file_path),precision=precision)
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config_file_path=config_file_path or default_config_file()
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model_manager= ModelManager(OmegaConf.load(config_file_path),precision=precision)
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if remove_models and len(remove_models) > 0:
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print("== DELETING UNCHECKED STARTER MODELS ==")
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@ -92,11 +92,16 @@ def install_requested_models(
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if external_models and len(external_models)>0:
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print("== INSTALLING EXTERNAL MODELS ==")
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for path_url_or_repo in external_models:
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model_manager.heuristic_import(
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path_url_or_repo,
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convert=convert_to_diffusers,
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commit_to_conf=config_file_path
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)
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try:
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model_manager.heuristic_import(
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path_url_or_repo,
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convert=convert_to_diffusers,
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commit_to_conf=config_file_path
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)
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except KeyboardInterrupt:
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sys.exit(-1)
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except Exception:
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pass
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# -------------------------------------
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def yes_or_no(prompt: str, default_yes=True):
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@ -2,6 +2,7 @@ from __future__ import annotations
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import dataclasses
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import inspect
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import psutil
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import secrets
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import sys
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from dataclasses import dataclass, field
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@ -643,7 +643,7 @@ class ModelManager(object):
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self.add_model(model_name, new_config, True)
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if commit_to_conf:
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self.commit(commit_to_conf)
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return True
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return model_name
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def import_ckpt_model(
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self,
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@ -710,6 +710,8 @@ class ModelManager(object):
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model_path = None
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thing = path_url_or_repo # to save typing
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print(f'here i am; thing={thing}, convert={convert}')
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if thing.startswith(('http:','https:','ftp:')):
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print(f'* {thing} appears to be a URL')
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model_path = self._resolve_path(thing, 'models/ldm/stable-diffusion-v1') # _resolve_path does a download if needed
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@ -720,17 +722,23 @@ class ModelManager(object):
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elif Path(thing).is_dir() and Path(thing, 'model_index.json').exists():
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print(f'* {thing} appears to be a diffusers file on disk')
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self.import_diffusers_model(thing, commit_to_conf=commit_to_conf)
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model_name = self.import_diffusers_model(
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thing,
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vae=dict(repo_id='stabilityai/sd-vae-ft-mse'),
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commit_to_conf=commit_to_conf
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)
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elif Path(thing).is_dir():
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print(f'* {thing} appears to be a directory. Will scan for models to import')
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for m in list(Path(thing).rglob('*.ckpt')) + list(Path(thing).rglob('*.safetensors')):
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self.heuristic_import(m, convert, commit_to_conf=commit_to_conf)
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print('***',m)
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self.heuristic_import(str(m), convert, commit_to_conf=commit_to_conf)
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return
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elif re.match(r'^[\w.+-]+/[\w.+-]+$', thing):
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print(f'* {thing} appears to be a HuggingFace diffusers repo_id')
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self.import_diffuser_model(thing, commit_to_conf=commit_to_conf)
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model_name = self.import_diffuser_model(thing, commit_to_conf=commit_to_conf)
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pipeline,_,_,_ = self._load_diffusers_model(self.config[model_name])
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else:
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print(f"* {thing}: Unknown thing. Please provide a URL, file path, directory or HuggingFace repo_id")
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@ -749,7 +757,7 @@ class ModelManager(object):
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print(f'* {thing} appears to be an SD-v2 model; model will be converted to diffusers format')
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model_config_file = Path(Globals.root,'configs/stable-diffusion/v2-inference-v.yaml')
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convert = True
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elif re.search('inpaint', model_path, flags=re.IGNORECASE):
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elif re.search('inpaint', str(model_path), flags=re.IGNORECASE):
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print(f'* {thing} appears to be an SD-v1 inpainting model')
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model_config_file = Path(Globals.root,'configs/stable-diffusion/v1-inpainting-inference.yaml')
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else:
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@ -833,7 +841,7 @@ class ModelManager(object):
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return
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model_name = model_name or diffusers_path.name
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model_description = model_description or "Optimized version of {model_name}"
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model_description = model_description or f"Optimized version of {model_name}"
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print(f">> Optimizing {model_name} (30-60s)")
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try:
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# By passing the specified VAE to the conversion function, the autoencoder
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@ -318,8 +318,6 @@ def download_with_resume(url: str, dest: Path, access_token: str = None) -> Path
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else:
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dest.parent.mkdir(parents=True, exist_ok=True)
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print(f'DEBUG: after many manipulations, dest={dest}')
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header = {"Authorization": f"Bearer {access_token}"} if access_token else {}
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open_mode = "wb"
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exist_size = 0
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