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fix merge conflicts with main

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Lincoln Stein
2024-04-15 09:24:57 -04:00
parent f1e79d5a8f e93f4d632d
commit 470a39935c
47 changed files with 476 additions and 277 deletions
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4
invokeai/backend/model_manager/load/load_default.py
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@ -18,7 +18,7 @@ from invokeai.backend.model_manager.load.load_base import LoadedModel, ModelLoad
from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase, ModelLockerBase
from invokeai.backend.model_manager.load.model_util import calc_model_size_by_fs
from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init
from invokeai.backend.util.devices import choose_torch_device, torch_dtype
from invokeai.backend.util.devices import TorchDevice
# TO DO: The loader is not thread safe!
@ -37,7 +37,7 @@ class ModelLoader(ModelLoaderBase):
self._logger = logger
self._ram_cache = ram_cache
self._convert_cache = convert_cache
self._torch_dtype = torch_dtype(choose_torch_device())
self._torch_dtype = TorchDevice.choose_torch_dtype()
def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
"""

14
invokeai/backend/model_manager/load/model_cache/model_cache_default.py
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@ -31,15 +31,12 @@ import torch
from invokeai.backend.model_manager import AnyModel, SubModelType
from invokeai.backend.model_manager.load.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff
from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data
from invokeai.backend.util.devices import choose_torch_device
from invokeai.backend.util.devices import TorchDevice
from invokeai.backend.util.logging import InvokeAILogger
from .model_cache_base import CacheRecord, CacheStats, ModelCacheBase, ModelLockerBase
from .model_locker import ModelLocker
if choose_torch_device() == torch.device("mps"):
from torch import mps
# Maximum size of the cache, in gigs
# Default is roughly enough to hold three fp16 diffusers models in RAM simultaneously
DEFAULT_MAX_CACHE_SIZE = 6.0
@ -245,9 +242,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
f"Removing {cache_entry.key} from VRAM to free {(cache_entry.size/GIG):.2f}GB; vram free = {(torch.cuda.memory_allocated()/GIG):.2f}GB"
)
torch.cuda.empty_cache()
if choose_torch_device() == torch.device("mps"):
mps.empty_cache()
TorchDevice.empty_cache()
def move_model_to_device(self, cache_entry: CacheRecord[AnyModel], target_device: torch.device) -> None:
"""Move model into the indicated device.
@ -417,10 +412,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
self.stats.cleared = models_cleared
gc.collect()
torch.cuda.empty_cache()
if choose_torch_device() == torch.device("mps"):
mps.empty_cache()
TorchDevice.empty_cache()
self.logger.debug(f"After making room: cached_models={len(self._cached_models)}")
def _delete_cache_entry(self, cache_entry: CacheRecord[AnyModel]) -> None: