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helpers.py
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98 lines (74 loc) · 2.78 KB
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import re
from collections import defaultdict
from typing import Mapping, TypeVar
import torch
from compressed_tensors.utils.match import match_name
from loguru import logger
__all__ = [
"gpu_if_available",
"find_safetensors_index_file",
"match_names_set_eager",
"MatchedNamesSet",
"invert_mapping",
]
KeyType = TypeVar("K")
ValueType = TypeVar("V")
MatchedNamesSet = dict[str, str | None]
def gpu_if_available(device: torch.device | str | None) -> torch.device:
if device is not None:
return torch.device(device)
elif torch.cuda.is_available():
return torch.device("cuda:0")
elif hasattr(torch, "xpu") and torch.xpu.is_available():
return torch.device("xpu:0")
elif hasattr(torch, "npu") and torch.npu.is_available():
return torch.device("npu:0")
else:
logger.warning(
"CUDA/XPU/NPU is not available! Compressing model on CPU instead"
)
return torch.device("cpu")
def find_safetensors_index_file(model_files: dict[str, str]) -> str | None:
for file_path, resolved_path in model_files.items():
if file_path.endswith("safetensors.index.json"):
return resolved_path
return None
def match_names_set_eager(
names: set[str] | list[str],
targets: set[str] | list[str],
return_unmatched: bool = True,
) -> list[MatchedNamesSet] | tuple[list[MatchedNamesSet], MatchedNamesSet]:
matched_sets = []
matches = dict.fromkeys(targets, None)
def natural_key(s: str) -> list[str | int]:
return [int(p) if p.isdigit() else p for p in re.split(r"(\d+)", s)]
# natural sort for consistent grouping
names = sorted(names, key=natural_key)
for name in names:
# match until we get a full set
for target in targets:
if match_name(name, target):
if matches[target] is None:
matches[target] = name
else:
# matched target twice without completing a set
raise ValueError(
f"Matched a {target} twice before "
f"completing set ({matches[target]}, {name})"
)
# once we have a full set, yield and reset
if all((matches[target] is not None for target in targets)):
matched_sets.append(matches)
matches = dict.fromkeys(targets, None)
unmatched_set = matches if any((v is not None for v in matches.values())) else None
if return_unmatched:
return matched_sets, unmatched_set
else:
return matched_sets
def invert_mapping(
mapping: Mapping[KeyType, ValueType],
) -> dict[ValueType, list[KeyType]]:
inverse = defaultdict(list)
for key, value in mapping.items():
inverse[value].append(key)
return inverse