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feat(config): dynamic ram cache size

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Use the util function to calculate ram cache size on startup. This way, the `ram` setting will always be optimized for a system, even if they add or remove RAM. In other words, the default value is now dynamic.
This commit is contained in:
psychedelicious 2024-03-19 12:41:42 +11:00
parent fabef8b45b
commit 6e882d3fd6
1 changed files with 20 additions and 1 deletions
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21
invokeai/app/services/config/config_default.py
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@ -10,6 +10,7 @@ from functools import lru_cache
from pathlib import Path from pathlib import Path
from typing import Any, Literal, Optional from typing import Any, Literal, Optional
import psutil
import yaml import yaml
from pydantic import BaseModel, Field, PrivateAttr, field_validator from pydantic import BaseModel, Field, PrivateAttr, field_validator
from pydantic_settings import BaseSettings, SettingsConfigDict from pydantic_settings import BaseSettings, SettingsConfigDict
@ -32,6 +33,24 @@ LOG_LEVEL = Literal["debug", "info", "warning", "error", "critical"]
CONFIG_SCHEMA_VERSION = 4 CONFIG_SCHEMA_VERSION = 4
def get_default_ram_cache_size() -> float:
"""Run a heuristic for the default RAM cache based on installed RAM."""
# On some machines, psutil.virtual_memory().total gives a value that is slightly less than the actual RAM, so the
# limits are set slightly lower than than what we expect the actual RAM to be.
GB = 1024**3
max_ram = psutil.virtual_memory().total / GB
if max_ram >= 60:
return 15.0
if max_ram >= 30:
return 7.5
if max_ram >= 14:
return 4.0
return 2.1 # 2.1 is just large enough for sd 1.5 ;-)
class URLRegexTokenPair(BaseModel): class URLRegexTokenPair(BaseModel):
url_regex: str = Field(description="Regular expression to match against the URL") url_regex: str = Field(description="Regular expression to match against the URL")
token: str = Field(description="Token to use when the URL matches the regex") token: str = Field(description="Token to use when the URL matches the regex")
@ -147,7 +166,7 @@ class InvokeAIAppConfig(BaseSettings):
profiles_dir: Path = Field(default=Path("profiles"), description="Path to profiles output directory.") profiles_dir: Path = Field(default=Path("profiles"), description="Path to profiles output directory.")
# CACHE # CACHE
ram: float = Field(default=DEFAULT_RAM_CACHE, gt=0, description="Maximum memory amount used by memory model cache for rapid switching (GB).") ram: float = Field(default_factory=get_default_ram_cache_size, gt=0, description="Maximum memory amount used by memory model cache for rapid switching (GB).")
vram: float = Field(default=DEFAULT_VRAM_CACHE, ge=0, description="Amount of VRAM reserved for model storage (GB).") vram: float = Field(default=DEFAULT_VRAM_CACHE, ge=0, description="Amount of VRAM reserved for model storage (GB).")
convert_cache: float = Field(default=DEFAULT_CONVERT_CACHE, ge=0, description="Maximum size of on-disk converted models cache (GB).") convert_cache: float = Field(default=DEFAULT_CONVERT_CACHE, ge=0, description="Maximum size of on-disk converted models cache (GB).")
lazy_offload: bool = Field(default=True, description="Keep models in VRAM until their space is needed.") lazy_offload: bool = Field(default=True, description="Keep models in VRAM until their space is needed.")