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reorder options in help text

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Lincoln Stein 2023-05-17 15:22:58 -04:00
parent 7593dc19d6
commit ffaadb9d05
1 changed files with 48 additions and 29 deletions
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77
invokeai/app/services/config.py
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@ -143,6 +143,7 @@ two configs are kept in separate sections of the config file:
...
'''
import argparse
import pydoc
import typing
import os
import sys
@ -232,7 +233,7 @@ class InvokeAISettings(BaseSettings):
@classmethod
def get_parser(cls)->ArgumentParser:
parser = ArgumentParser(
parser = PagingArgumentParser(
prog=cls.cmd_name(),
description=cls.__doc__,
)
@ -316,38 +317,46 @@ def _find_root()->Path:
class InvokeAIAppConfig(InvokeAISettings):
'''
Application-wide settings.
'''
Generate images using Stable Diffusion. Use "invokeai" to launch
the command-line client (recommended for experts only), or
"invokeai-web" to launch the web server. Global options
can be changed by editing the file "INVOKEAI_ROOT/invokeai.yaml" or by
setting environment variables INVOKEAI_<setting>.
'''
#fmt: off
type: Literal["InvokeAI"] = "InvokeAI"
root : Path = Field(default=_find_root(), description='InvokeAI runtime root directory', category='Paths')
conf_path : Path = Field(default='configs/models.yaml', description='Path to models definition file', category='Paths')
legacy_conf_dir : Path = Field(default='configs/stable-diffusion', description='Path to directory of legacy checkpoint config files', category='Paths')
model : str = Field(default='stable-diffusion-1.5', description='Initial model name', category='Models')
outdir : Path = Field(default='outputs', description='Default folder for output images', category='Paths')
embedding_dir : Path = Field(default='embeddings', description='Path to InvokeAI textual inversion aembeddings directory', category='Paths')
lora_dir : Path = Field(default='loras', description='Path to InvokeAI LoRA model directory', category='Paths')
autoconvert_dir : Path = Field(default=None, description='Path to a directory of ckpt files to be converted into diffusers and imported on startup.', category='Paths')
gfpgan_model_dir : Path = Field(default="./models/gfpgan/GFPGANv1.4.pth", description='Path to GFPGAN models directory.', category='Paths')
embeddings : bool = Field(default=True, description='Load contents of embeddings directory', category='Models')
xformers_enabled : bool = Field(default=True, description="Enable/disable memory-efficient attention", category='Memory/Performance')
sequential_guidance : bool = Field(default=False, description="Whether to calculate guidance in serial instead of in parallel, lowering memory requirements", category='Memory/Performance')
precision : Literal[tuple(['auto','float16','float32','autocast'])] = Field(default='float16',description='Floating point precision', category='Memory/Performance')
max_loaded_models : int = Field(default=2, gt=0, description="Maximum number of models to keep in memory for rapid switching", category='Memory/Performance')
always_use_cpu : bool = Field(default=False, description="If true, use the CPU for rendering even if a GPU is available.", category='Memory/Performance')
free_gpu_mem : bool = Field(default=False, description="If true, purge model from GPU after each generation.", category='Memory/Performance')
nsfw_checker : bool = Field(default=True, description="Enable/disable the NSFW checker", category='Features')
restore : bool = Field(default=True, description="Enable/disable face restoration code", category='Features')
esrgan : bool = Field(default=True, description="Enable/disable upscaling code", category='Features')
patchmatch : bool = Field(default=True, description="Enable/disable patchmatch inpaint code", category='Features')
internet_available : bool = Field(default=True, description="If true, attempt to download models on the fly; otherwise only use local models", category='Features')
log_tokenization : bool = Field(default=False, description="Enable logging of parsed prompt tokens.", category='Features')
allow_origins : List[str] = Field(default=[], description="Allowed CORS origins", category='Cross-Origin Resource Sharing')
allow_credentials : bool = Field(default=True, description="Allow CORS credentials", category='Cross-Origin Resource Sharing')
allow_methods : List[str] = Field(default=["*"], description="Methods allowed for CORS", category='Cross-Origin Resource Sharing')
allow_headers : List[str] = Field(default=["*"], description="Headers allowed for CORS", category='Cross-Origin Resource Sharing')
host : str = Field(default="127.0.0.1", description="IP address to bind to", category='Web Server')
port : int = Field(default=9090, description="Port to bind to", category='Web Server')
allow_origins : List[str] = Field(default=[], description="Allowed CORS origins", category='Web Server')
allow_credentials : bool = Field(default=True, description="Allow CORS credentials", category='Web Server')
allow_methods : List[str] = Field(default=["*"], description="Methods allowed for CORS", category='Web Server')
allow_headers : List[str] = Field(default=["*"], description="Headers allowed for CORS", category='Web Server')
esrgan : bool = Field(default=True, description="Enable/disable upscaling code", category='Features')
internet_available : bool = Field(default=True, description="If true, attempt to download models on the fly; otherwise only use local models", category='Features')
log_tokenization : bool = Field(default=False, description="Enable logging of parsed prompt tokens.", category='Features')
nsfw_checker : bool = Field(default=True, description="Enable/disable the NSFW checker", category='Features')
patchmatch : bool = Field(default=True, description="Enable/disable patchmatch inpaint code", category='Features')
restore : bool = Field(default=True, description="Enable/disable face restoration code", category='Features')
always_use_cpu : bool = Field(default=False, description="If true, use the CPU for rendering even if a GPU is available.", category='Memory/Performance')
free_gpu_mem : bool = Field(default=False, description="If true, purge model from GPU after each generation.", category='Memory/Performance')
max_loaded_models : int = Field(default=2, gt=0, description="Maximum number of models to keep in memory for rapid switching", category='Memory/Performance')
precision : Literal[tuple(['auto','float16','float32','autocast'])] = Field(default='float16',description='Floating point precision', category='Memory/Performance')
sequential_guidance : bool = Field(default=False, description="Whether to calculate guidance in serial instead of in parallel, lowering memory requirements", category='Memory/Performance')
xformers_enabled : bool = Field(default=True, description="Enable/disable memory-efficient attention", category='Memory/Performance')
root : Path = Field(default=_find_root(), description='InvokeAI runtime root directory', category='Paths')
autoconvert_dir : Path = Field(default=None, description='Path to a directory of ckpt files to be converted into diffusers and imported on startup.', category='Paths')
conf_path : Path = Field(default='configs/models.yaml', description='Path to models definition file', category='Paths')
embedding_dir : Path = Field(default='embeddings', description='Path to InvokeAI textual inversion aembeddings directory', category='Paths')
gfpgan_model_dir : Path = Field(default="./models/gfpgan/GFPGANv1.4.pth", description='Path to GFPGAN models directory.', category='Paths')
legacy_conf_dir : Path = Field(default='configs/stable-diffusion', description='Path to directory of legacy checkpoint config files', category='Paths')
lora_dir : Path = Field(default='loras', description='Path to InvokeAI LoRA model directory', category='Paths')
outdir : Path = Field(default='outputs', description='Default folder for output images', category='Paths')
model : str = Field(default='stable-diffusion-1.5', description='Initial model name', category='Models')
embeddings : bool = Field(default=True, description='Load contents of embeddings directory', category='Models')
#fmt: on
def __init__(self, conf: DictConfig = None, argv: List[str]=None, **kwargs):
@ -484,6 +493,16 @@ class InvokeAIAppConfig(InvokeAISettings):
'''
return _find_root()
class PagingArgumentParser(argparse.ArgumentParser):
'''
A custom ArgumentParser that uses pydoc to page its output.
It also supports reading defaults from an init file.
'''
def print_help(self, file=None):
text = self.format_help()
pydoc.pager(text)
def get_invokeai_config(cls:Type[InvokeAISettings]=InvokeAIAppConfig)->InvokeAISettings:
'''
This returns a singleton InvokeAIAppConfig configuration object.