Fix memory issues when installing models on Windows (#8652)

* Wrap GGUF loader for context managed close()

Wrap gguf.GGUFReader and then use a context manager to load memory-mapped GGUF files, so that they will automatically close properly when no longer needed. Should prevent the 'file in use in another process' errors on Windows.

* Additional check for cached state_dict

Additional check for cached state_dict as path is now optional - should solve model manager 'missing' this and the resultant memory errors.

* Appease ruff

* Further ruff appeasement

* ruff

* loaders.py fix for linux

No longer attempting to delete internal object.

* loaders.py - one more _mmap ref removed

---------

Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
This commit is contained in:
gogurtenjoyer 2025-11-16 09:25:52 -05:00 committed by GitHub
parent abcc987f6f
commit 382d85ee23
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2 changed files with 46 additions and 12 deletions

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@ -84,6 +84,9 @@ class ModelOnDisk:
path = self.resolve_weight_file(path)
if path in self._state_dict_cache:
return self._state_dict_cache[path]
with SilenceWarnings():
if path.suffix.endswith((".ckpt", ".pt", ".pth", ".bin")):
scan_result = scan_file_path(path)

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@ -1,3 +1,4 @@
import gc
from pathlib import Path
import gguf
@ -5,18 +6,48 @@ import torch
from invokeai.backend.quantization.gguf.ggml_tensor import GGMLTensor
from invokeai.backend.quantization.gguf.utils import TORCH_COMPATIBLE_QTYPES
from invokeai.backend.util.logging import InvokeAILogger
logger = InvokeAILogger.get_logger()
class WrappedGGUFReader:
"""Wrapper around GGUFReader that adds a close() method."""
def __init__(self, path: Path):
self.reader = gguf.GGUFReader(path)
def __enter__(self):
return self.reader
def __exit__(self, exc_type, exc_val, exc_tb):
self.close()
return False
def close(self):
"""Explicitly close the memory-mapped file."""
if hasattr(self.reader, "data"):
try:
self.reader.data.flush()
del self.reader.data
except (AttributeError, OSError, ValueError) as e:
logger.warning(f"Wasn't able to close GGUF memory map: {e}")
del self.reader
gc.collect()
def gguf_sd_loader(path: Path, compute_dtype: torch.dtype) -> dict[str, GGMLTensor]:
reader = gguf.GGUFReader(path)
sd: dict[str, GGMLTensor] = {}
for tensor in reader.tensors:
torch_tensor = torch.from_numpy(tensor.data)
shape = torch.Size(tuple(int(v) for v in reversed(tensor.shape)))
if tensor.tensor_type in TORCH_COMPATIBLE_QTYPES:
torch_tensor = torch_tensor.view(*shape)
sd[tensor.name] = GGMLTensor(
torch_tensor, ggml_quantization_type=tensor.tensor_type, tensor_shape=shape, compute_dtype=compute_dtype
)
return sd
with WrappedGGUFReader(path) as reader:
sd: dict[str, GGMLTensor] = {}
for tensor in reader.tensors:
torch_tensor = torch.from_numpy(tensor.data)
shape = torch.Size(tuple(int(v) for v in reversed(tensor.shape)))
if tensor.tensor_type in TORCH_COMPATIBLE_QTYPES:
torch_tensor = torch_tensor.view(*shape)
sd[tensor.name] = GGMLTensor(
torch_tensor,
ggml_quantization_type=tensor.tensor_type,
tensor_shape=shape,
compute_dtype=compute_dtype,
)
return sd