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https://github.com/invoke-ai/InvokeAI
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remove deprecated options from config
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13347f6aec
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@ -286,14 +286,10 @@ class InvokeAISettings(BaseSettings):
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return [
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"type",
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"initconf",
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"gpu_mem_reserved",
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"max_loaded_models",
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"version",
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"from_file",
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"model",
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"restore",
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"root",
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"nsfw_checker",
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]
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class Config:
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@ -392,15 +388,11 @@ class InvokeAIAppConfig(InvokeAISettings):
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internet_available : bool = Field(default=True, description="If true, attempt to download models on the fly; otherwise only use local models", category='Features')
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log_tokenization : bool = Field(default=False, description="Enable logging of parsed prompt tokens.", category='Features')
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patchmatch : bool = Field(default=True, description="Enable/disable patchmatch inpaint code", category='Features')
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restore : bool = Field(default=True, description="Enable/disable face restoration code (DEPRECATED)", category='DEPRECATED')
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always_use_cpu : bool = Field(default=False, description="If true, use the CPU for rendering even if a GPU is available.", category='Memory/Performance')
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free_gpu_mem : bool = Field(default=False, description="If true, purge model from GPU after each generation.", category='Memory/Performance')
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max_loaded_models : int = Field(default=3, gt=0, description="(DEPRECATED: use max_cache_size) Maximum number of models to keep in memory for rapid switching", category='DEPRECATED')
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max_cache_size : float = Field(default=6.0, gt=0, description="Maximum memory amount used by model cache for rapid switching", category='Memory/Performance')
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max_vram_cache_size : float = Field(default=2.75, ge=0, description="Amount of VRAM reserved for model storage", category='Memory/Performance')
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gpu_mem_reserved : float = Field(default=2.75, ge=0, description="DEPRECATED: use max_vram_cache_size. Amount of VRAM reserved for model storage", category='DEPRECATED')
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nsfw_checker : bool = Field(default=True, description="DEPRECATED: use Web settings to enable/disable", category='DEPRECATED')
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precision : Literal[tuple(['auto','float16','float32','autocast'])] = Field(default='auto',description='Floating point precision', category='Memory/Performance')
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sequential_guidance : bool = Field(default=False, description="Whether to calculate guidance in serial instead of in parallel, lowering memory requirements", category='Memory/Performance')
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xformers_enabled : bool = Field(default=True, description="Enable/disable memory-efficient attention", category='Memory/Performance')
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@ -418,9 +410,7 @@ class InvokeAIAppConfig(InvokeAISettings):
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outdir : Path = Field(default='outputs', description='Default folder for output images', category='Paths')
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from_file : Path = Field(default=None, description='Take command input from the indicated file (command-line client only)', category='Paths')
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use_memory_db : bool = Field(default=False, description='Use in-memory database for storing image metadata', category='Paths')
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ignore_missing_core_models : bool = Field(default=False, description='Ignore missing models in models/core/convert')
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model : str = Field(default='stable-diffusion-1.5', description='Initial model name', category='Models')
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ignore_missing_core_models : bool = Field(default=False, description='Ignore missing models in models/core/convert', category='Features')
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log_handlers : List[str] = Field(default=["console"], description='Log handler. Valid options are "console", "file=<path>", "syslog=path|address:host:port", "http=<url>"', category="Logging")
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# note - would be better to read the log_format values from logging.py, but this creates circular dependencies issues
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