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refactor InvokeAIAppConfig

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This commit is contained in:
Lincoln Stein
2023-08-17 13:47:26 -04:00
parent 503e3bca54
commit ed38eaa10c
10 changed files with 498 additions and 393 deletions
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177
invokeai/backend/install/invokeai_configure.py
View File

@ -21,6 +21,7 @@ from argparse import Namespace
from enum import Enum
from pathlib import Path
from shutil import get_terminal_size
from typing import get_type_hints, get_args, Any
from urllib import request
import npyscreen
@ -50,6 +51,7 @@ from invokeai.frontend.install.model_install import addModelsForm, process_and_e
# TO DO - Move all the frontend code into invokeai.frontend.install
from invokeai.frontend.install.widgets import (
SingleSelectColumns,
MultiSelectColumns,
CenteredButtonPress,
FileBox,
IntTitleSlider,
@ -72,6 +74,10 @@ warnings.filterwarnings("ignore")
transformers.logging.set_verbosity_error()
def get_literal_fields(field) -> list[Any]:
return get_args(get_type_hints(InvokeAIAppConfig).get(field))
# --------------------------globals-----------------------
config = InvokeAIAppConfig.get_config()
@ -81,7 +87,11 @@ Model_dir = "models"
Default_config_file = config.model_conf_path
SD_Configs = config.legacy_conf_path
PRECISION_CHOICES = ["auto", "float16", "float32"]
PRECISION_CHOICES = get_literal_fields("precision")
DEVICE_CHOICES = get_literal_fields("device")
ATTENTION_CHOICES = get_literal_fields("attention_type")
ATTENTION_SLICE_CHOICES = get_literal_fields("attention_slice_size")
GENERATION_OPT_CHOICES = ["sequential_guidance", "force_tiled_decode", "lazy_offload"]
GB = 1073741824 # GB in bytes
HAS_CUDA = torch.cuda.is_available()
_, MAX_VRAM = torch.cuda.mem_get_info() if HAS_CUDA else (0, 0)
@ -312,6 +322,7 @@ class editOptsForm(CyclingForm, npyscreen.FormMultiPage):
Use ctrl-N and ctrl-P to move to the <N>ext and <P>revious fields.
Use cursor arrows to make a checkbox selection, and space to toggle.
"""
self.nextrely -= 1
for i in textwrap.wrap(label, width=window_width - 6):
self.add_widget_intelligent(
npyscreen.FixedText,
@ -338,76 +349,130 @@ Use cursor arrows to make a checkbox selection, and space to toggle.
use_two_lines=False,
scroll_exit=True,
)
self.nextrely += 1
self.add_widget_intelligent(
npyscreen.TitleFixedText,
name="GPU Management",
begin_entry_at=0,
editable=False,
color="CONTROL",
scroll_exit=True,
)
self.nextrely -= 1
self.free_gpu_mem = self.add_widget_intelligent(
npyscreen.Checkbox,
name="Free GPU memory after each generation",
value=old_opts.free_gpu_mem,
max_width=45,
relx=5,
scroll_exit=True,
)
self.nextrely -= 1
self.xformers_enabled = self.add_widget_intelligent(
npyscreen.Checkbox,
name="Enable xformers support",
value=old_opts.xformers_enabled,
max_width=30,
relx=50,
scroll_exit=True,
)
self.nextrely -= 1
self.always_use_cpu = self.add_widget_intelligent(
npyscreen.Checkbox,
name="Force CPU to be used on GPU systems",
value=old_opts.always_use_cpu,
relx=80,
scroll_exit=True,
)
# old settings for defaults
precision = old_opts.precision or ("float32" if program_opts.full_precision else "auto")
device = old_opts.device
attention_type = "xformers" if old_opts.xformers_enabled else old_opts.attention_type
attention_slice_size = old_opts.attention_slice_size
self.nextrely += 1
self.add_widget_intelligent(
npyscreen.TitleFixedText,
name="Floating Point Precision",
name="Image Generation Options:",
editable=False,
color="CONTROL",
scroll_exit=True,
)
self.nextrely -= 2
self.generation_options = self.add_widget_intelligent(
MultiSelectColumns,
columns=3,
values=GENERATION_OPT_CHOICES,
value=[GENERATION_OPT_CHOICES.index(x) for x in GENERATION_OPT_CHOICES if getattr(old_opts, x)],
relx=30,
max_height=2,
max_width=80,
scroll_exit=True,
)
self.add_widget_intelligent(
npyscreen.TitleFixedText,
name="Floating Point Precision:",
begin_entry_at=0,
editable=False,
color="CONTROL",
scroll_exit=True,
)
self.nextrely -= 1
self.nextrely -= 2
self.precision = self.add_widget_intelligent(
SingleSelectColumns,
columns=3,
columns=len(PRECISION_CHOICES),
name="Precision",
values=PRECISION_CHOICES,
value=PRECISION_CHOICES.index(precision),
begin_entry_at=3,
max_height=2,
relx=30,
max_width=56,
scroll_exit=True,
)
self.add_widget_intelligent(
npyscreen.TitleFixedText,
name="Generation Device:",
begin_entry_at=0,
editable=False,
color="CONTROL",
scroll_exit=True,
)
self.nextrely -= 2
self.device = self.add_widget_intelligent(
SingleSelectColumns,
columns=len(DEVICE_CHOICES),
values=DEVICE_CHOICES,
value=DEVICE_CHOICES.index(device),
begin_entry_at=3,
relx=30,
max_height=2,
max_width=60,
scroll_exit=True,
)
self.add_widget_intelligent(
npyscreen.TitleFixedText,
name="Attention Type:",
begin_entry_at=0,
editable=False,
color="CONTROL",
scroll_exit=True,
)
self.nextrely -= 2
self.attention_type = self.add_widget_intelligent(
SingleSelectColumns,
columns=len(ATTENTION_CHOICES),
values=ATTENTION_CHOICES,
value=ATTENTION_CHOICES.index(attention_type),
begin_entry_at=3,
max_height=2,
relx=30,
max_width=80,
scroll_exit=True,
)
self.nextrely += 1
self.attention_type.on_changed = self.show_hide_slice_sizes
self.attention_slice_label = self.add_widget_intelligent(
npyscreen.TitleFixedText,
name="Attention Slice Size:",
relx=5,
editable=False,
hidden=True,
color="CONTROL",
scroll_exit=True,
)
self.nextrely -= 2
self.attention_slice_size = self.add_widget_intelligent(
SingleSelectColumns,
columns=len(ATTENTION_SLICE_CHOICES),
values=ATTENTION_SLICE_CHOICES,
value=ATTENTION_SLICE_CHOICES.index(attention_slice_size),
begin_entry_at=2,
relx=30,
hidden=True,
max_height=2,
max_width=100,
scroll_exit=True,
)
self.add_widget_intelligent(
npyscreen.TitleFixedText,
name="RAM cache size (GB). Make this at least large enough to hold a single full model.",
name="Model RAM cache size (GB). Make this at least large enough to hold a single full model.",
begin_entry_at=0,
editable=False,
color="CONTROL",
scroll_exit=True,
)
self.nextrely -= 1
self.max_cache_size = self.add_widget_intelligent(
self.ram = self.add_widget_intelligent(
npyscreen.Slider,
value=clip(old_opts.max_cache_size, range=(3.0, MAX_RAM), step=0.5),
value=clip(old_opts.ram_cache_size, range=(3.0, MAX_RAM), step=0.5),
out_of=round(MAX_RAM),
lowest=0.0,
step=0.5,
@ -418,16 +483,16 @@ Use cursor arrows to make a checkbox selection, and space to toggle.
self.nextrely += 1
self.add_widget_intelligent(
npyscreen.TitleFixedText,
name="VRAM cache size (GB). Reserving a small amount of VRAM will modestly speed up the start of image generation.",
name="Model VRAM cache size (GB). Reserving a small amount of VRAM will modestly speed up the start of image generation.",
begin_entry_at=0,
editable=False,
color="CONTROL",
scroll_exit=True,
)
self.nextrely -= 1
self.max_vram_cache_size = self.add_widget_intelligent(
self.vram = self.add_widget_intelligent(
npyscreen.Slider,
value=clip(old_opts.max_vram_cache_size, range=(0, MAX_VRAM), step=0.25),
value=clip(old_opts.vram_cache_size, range=(0, MAX_VRAM), step=0.25),
out_of=round(MAX_VRAM * 2) / 2,
lowest=0.0,
relx=8,
@ -435,7 +500,7 @@ Use cursor arrows to make a checkbox selection, and space to toggle.
scroll_exit=True,
)
else:
self.max_vram_cache_size = DummyWidgetValue.zero
self.vram_cache_size = DummyWidgetValue.zero
self.nextrely += 1
self.outdir = self.add_widget_intelligent(
FileBox,
@ -491,6 +556,11 @@ https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENS
when_pressed_function=self.on_ok,
)
def show_hide_slice_sizes(self, value):
show = ATTENTION_CHOICES[value[0]] == "sliced"
self.attention_slice_label.hidden = not show
self.attention_slice_size.hidden = not show
def on_ok(self):
options = self.marshall_arguments()
if self.validate_field_values(options):
@ -524,12 +594,9 @@ https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENS
new_opts = Namespace()
for attr in [
"ram",
"vram",
"outdir",
"free_gpu_mem",
"max_cache_size",
"max_vram_cache_size",
"xformers_enabled",
"always_use_cpu",
]:
setattr(new_opts, attr, getattr(self, attr).value)
@ -542,6 +609,12 @@ https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENS
new_opts.hf_token = self.hf_token.value
new_opts.license_acceptance = self.license_acceptance.value
new_opts.precision = PRECISION_CHOICES[self.precision.value[0]]
new_opts.device = DEVICE_CHOICES[self.device.value[0]]
new_opts.attention_type = ATTENTION_CHOICES[self.attention_type.value[0]]
new_opts.attention_slice_size = ATTENTION_SLICE_CHOICES[self.attention_slice_size.value]
generation_options = [GENERATION_OPT_CHOICES[x] for x in self.generation_options.value]
for v in GENERATION_OPT_CHOICES:
setattr(new_opts, v, v in generation_options)
return new_opts

2
invokeai/backend/model_management/model_manager.py
View File

@ -341,7 +341,7 @@ class ModelManager(object):
self.logger = logger
self.cache = ModelCache(
max_cache_size=max_cache_size,
max_vram_cache_size=self.app_config.max_vram_cache_size,
max_vram_cache_size=self.app_config.vram_cache_size,
execution_device=device_type,
precision=precision,
sequential_offload=sequential_offload,

16
invokeai/backend/util/devices.py
View File

@ -17,13 +17,17 @@ config = InvokeAIAppConfig.get_config()
def choose_torch_device() -> torch.device:
"""Convenience routine for guessing which GPU device to run model on"""
if config.always_use_cpu:
if config.use_cpu: # legacy setting - force CPU
return CPU_DEVICE
if torch.cuda.is_available():
return torch.device("cuda")
if hasattr(torch.backends, "mps") and torch.backends.mps.is_available():
return torch.device("mps")
return CPU_DEVICE
elif config.device == "auto":
if torch.cuda.is_available():
return torch.device("cuda")
if hasattr(torch.backends, "mps") and torch.backends.mps.is_available():
return torch.device("mps")
else:
return CPU_DEVICE
else:
return torch.device(config.device)
def choose_precision(device: torch.device) -> str: