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https://github.com/invoke-ai/InvokeAI
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fix(model_cache): don't check model.config
in diffusers format
clean-up from recent merge.
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@ -4,29 +4,28 @@ They are moved between GPU and CPU as necessary. If CPU memory falls
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below a preset minimum, the least recently used model will be
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below a preset minimum, the least recently used model will be
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cleared and loaded from disk when next needed.
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cleared and loaded from disk when next needed.
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'''
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'''
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import gc
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import hashlib
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import io
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import os
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import sys
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import time
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import traceback
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import warnings
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import warnings
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from pathlib import Path
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from pathlib import Path
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import torch
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import torch
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import os
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import io
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import time
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import gc
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import hashlib
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import psutil
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import sys
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import transformers
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import transformers
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import traceback
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import textwrap
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import textwrap
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import contextlib
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import contextlib
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from typing import Union
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from typing import Union
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from omegaconf import OmegaConf
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from omegaconf import OmegaConf
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from omegaconf.errors import ConfigAttributeError
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from omegaconf.errors import ConfigAttributeError
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from picklescan.scanner import scan_file_path
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from ldm.invoke.generator.diffusers_pipeline import StableDiffusionGeneratorPipeline
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from ldm.invoke.generator.diffusers_pipeline import StableDiffusionGeneratorPipeline
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from ldm.util import instantiate_from_config, ask_user
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from ldm.invoke.globals import Globals
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from ldm.invoke.globals import Globals
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from picklescan.scanner import scan_file_path
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from ldm.util import instantiate_from_config, ask_user
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DEFAULT_MAX_MODELS=2
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DEFAULT_MAX_MODELS=2
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@ -240,6 +239,13 @@ class ModelCache(object):
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width = mconfig.width
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width = mconfig.width
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height = mconfig.height
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height = mconfig.height
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if not os.path.isabs(config):
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config = os.path.join(Globals.root,config)
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if not os.path.isabs(weights):
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weights = os.path.normpath(os.path.join(Globals.root,weights))
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# scan model
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self._scan_model(model_name, weights)
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c = OmegaConf.load(config)
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c = OmegaConf.load(config)
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with open(weights, 'rb') as f:
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with open(weights, 'rb') as f:
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weight_bytes = f.read()
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weight_bytes = f.read()
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