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fix default vram cache size calculation

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This commit is contained in:
Lincoln Stein 2023-08-02 09:43:52 -04:00
parent 77c5c18542
commit 880727436c
2 changed files with 7 additions and 5 deletions
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4
invokeai/app/services/config.py
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@ -173,7 +173,7 @@ from typing import ClassVar, Dict, List, Set, Literal, Union, get_origin, get_ty
INIT_FILE = Path("invokeai.yaml") INIT_FILE = Path("invokeai.yaml")
DB_FILE = Path("invokeai.db") DB_FILE = Path("invokeai.db")
LEGACY_INIT_FILE = Path("invokeai.init") LEGACY_INIT_FILE = Path("invokeai.init")
DEFAULT_MAX_VRAM = 2.75
class InvokeAISettings(BaseSettings): class InvokeAISettings(BaseSettings):
""" """
@ -395,7 +395,7 @@ class InvokeAIAppConfig(InvokeAISettings):
free_gpu_mem : bool = Field(default=False, description="If true, purge model from GPU after each generation.", 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=3, gt=0, description="(DEPRECATED: use max_cache_size) Maximum number of models to keep in memory for rapid switching", category='DEPRECATED') 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')
max_cache_size : float = Field(default=6.0, gt=0, description="Maximum memory amount used by model cache for rapid switching", category='Memory/Performance') max_cache_size : float = Field(default=6.0, gt=0, description="Maximum memory amount used by model cache for rapid switching", category='Memory/Performance')
max_vram_cache_size : float = Field(default=2.75, ge=0, description="Amount of VRAM reserved for model storage", category='Memory/Performance') max_vram_cache_size : float = Field(default=DEFAULT_MAX_VRAM, ge=0, description="Amount of VRAM reserved for model storage", category='Memory/Performance')
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') 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')
nsfw_checker : bool = Field(default=True, description="DEPRECATED: use Web settings to enable/disable", category='DEPRECATED') nsfw_checker : bool = Field(default=True, description="DEPRECATED: use Web settings to enable/disable", category='DEPRECATED')
precision : Literal[tuple(['auto','float16','float32','autocast'])] = Field(default='auto',description='Floating point precision', category='Memory/Performance') precision : Literal[tuple(['auto','float16','float32','autocast'])] = Field(default='auto',description='Floating point precision', category='Memory/Performance')

8
invokeai/backend/install/invokeai_configure.py
View File

@ -82,6 +82,7 @@ PRECISION_CHOICES = ["auto", "float16", "float32"]
HAS_CUDA = torch.cuda.is_available() HAS_CUDA = torch.cuda.is_available()
_, MAX_VRAM = torch.cuda.mem_get_info() if HAS_CUDA else (0, 0) _, MAX_VRAM = torch.cuda.mem_get_info() if HAS_CUDA else (0, 0)
MAX_VRAM /= 1073741824 # GB in bytes MAX_VRAM /= 1073741824 # GB in bytes
MAX_VRAM_CACHE_RATIO = 0.55 # first guess of optimal vram cache based on total available
INIT_FILE_PREAMBLE = """# InvokeAI initialization file INIT_FILE_PREAMBLE = """# InvokeAI initialization file
# This is the InvokeAI initialization file, which contains command-line default values. # This is the InvokeAI initialization file, which contains command-line default values.
@ -568,9 +569,11 @@ def edit_opts(program_opts: Namespace, invokeai_opts: Namespace) -> argparse.Nam
def default_startup_options(init_file: Path) -> Namespace: def default_startup_options(init_file: Path) -> Namespace:
opts = InvokeAIAppConfig.get_config() opts = InvokeAIAppConfig.get_config()
# dynamically adust vram for memory size
if not init_file.exists():
opts.max_vram_cache_size = round((MAX_VRAM * MAX_VRAM_CACHE_RATIO)*4) / 4
return opts return opts
def default_user_selections(program_opts: Namespace) -> InstallSelections: def default_user_selections(program_opts: Namespace) -> InstallSelections:
try: try:
installer = ModelInstall(config) installer = ModelInstall(config)
@ -628,7 +631,6 @@ def maybe_create_models_yaml(root: Path):
# ------------------------------------- # -------------------------------------
def run_console_ui(program_opts: Namespace, initfile: Path = None) -> (Namespace, Namespace): def run_console_ui(program_opts: Namespace, initfile: Path = None) -> (Namespace, Namespace):
# parse_args() will read from init file if present
invokeai_opts = default_startup_options(initfile) invokeai_opts = default_startup_options(initfile)
invokeai_opts.root = program_opts.root invokeai_opts.root = program_opts.root
@ -711,7 +713,6 @@ def migrate_init_file(legacy_format: Path):
# ------------------------------------- # -------------------------------------
def migrate_models(root: Path): def migrate_models(root: Path):
from invokeai.backend.install.migrate_to_3 import do_migrate from invokeai.backend.install.migrate_to_3 import do_migrate
do_migrate(root, root) do_migrate(root, root)
@ -813,6 +814,7 @@ def main():
models_to_download = default_user_selections(opt) models_to_download = default_user_selections(opt)
new_init_file = config.root_path / "invokeai.yaml" new_init_file = config.root_path / "invokeai.yaml"
if opt.yes_to_all: if opt.yes_to_all:
write_default_options(opt, new_init_file) write_default_options(opt, new_init_file)
init_options = Namespace(precision="float32" if opt.full_precision else "float16") init_options = Namespace(precision="float32" if opt.full_precision else "float16")