llama.cpp/convert_legacy_imatrix_to_gguf.py
2024-09-08 10:04:01 -04:00

123 lines
3.8 KiB
Python

#!/usr/bin/env python3
from __future__ import annotations
import os
import sys
import logging
import argparse
from typing import Any
from pathlib import Path
from dataclasses import dataclass
import numpy as np
import numpy.typing as npt
if 'NO_LOCAL_GGUF' not in os.environ:
sys.path.insert(1, str(Path(__file__).parent / 'gguf-py'))
import gguf
logger = logging.getLogger("imatrix-to-gguf")
class IMatrixWriter(gguf.GGUFWriter):
def add_architecture(self) -> None:
# no arch is stored in imatrix files
pass
@dataclass
class IMatrixEntry:
values: np.ndarray[Any, np.dtype[np.float32]]
counts: np.ndarray[Any, np.dtype[np.float32]]
class IMatrixReader:
chunk_size: int = 512 # guess
offset: int = 0
data: np.ndarray[Any, np.dtype[np.uint8]]
n_enties: int
entries: dict[str, IMatrixEntry]
chunk_count: int
dataset: str
def _get(self, dtype: npt.DTypeLike, count: int = 1) -> npt.NDArray[Any]:
count = int(count)
itemsize = int(np.empty([], dtype=dtype).itemsize)
offset = self.offset
self.offset = offset + itemsize * count
return self.data[offset:self.offset].view(dtype=dtype)[:count]
def __init__(self, imatrix: Path):
self.offset = 0
self.entries = {}
self.data = np.memmap(imatrix)
n_entries = self._get(np.int32).item()
assert n_entries >= 0
for _ in range(n_entries):
len = self._get(np.int32).item()
name = self._get(np.uint8, len).tobytes().decode("utf-8")
ncall = self._get(np.int32).item()
nval = self._get(np.int32).item()
data = self._get(np.float32, nval)
assert name not in self.entries, f"duplicated name: {name!r}"
self.entries[name] = IMatrixEntry(data * np.float32(self.chunk_size), np.array([ncall * self.chunk_size], dtype=np.float32))
self.chunk_count = self._get(np.int32).item()
dataset_len = self._get(np.int32).item()
self.dataset = self._get(np.uint8, dataset_len).tobytes().decode("utf-8")
def to_writer(self, outfile: Path) -> IMatrixWriter:
writer = IMatrixWriter(path=outfile, arch="")
writer.add_type(gguf.GGUFType.IMATRIX)
writer.add_key_value(gguf.Keys.IMatrix.CHUNK_COUNT, self.chunk_count, gguf.GGUFValueType.UINT32)
writer.add_key_value(gguf.Keys.IMatrix.CHUNK_SIZE, self.chunk_size, gguf.GGUFValueType.UINT32)
writer.add_key_value(gguf.Keys.IMatrix.DATASET, self.dataset, gguf.GGUFValueType.STRING)
for name, entry in self.entries.items():
writer.add_tensor(name + ".sums", entry.values)
writer.add_tensor(name + ".counts", entry.counts)
return writer
def parse_args():
parser = argparse.ArgumentParser(
description="Convert an old imatrix.dat file to a GGUF compatible file")
parser.add_argument(
"--outfile", type=Path,
help="path to write to; default: based on input.",
)
parser.add_argument(
"--verbose", action="store_true",
help="increase output verbosity",
)
parser.add_argument(
"imatrix", type=Path,
help="path to an imatrix file",
)
return parser.parse_args()
if __name__ == "__main__":
args = parse_args()
logging.basicConfig(level=logging.DEBUG if args.verbose else logging.INFO)
if args.outfile is None:
input_file: Path = args.imatrix
if input_file.suffix != ".gguf":
args.outfile = input_file.with_suffix(".gguf")
if args.outfile.exists():
logger.error(f"default file exists, specify with --outfile to overwrite: {args.outfile}")
exit(1)
writer = IMatrixReader(args.imatrix).to_writer(args.outfile)
writer.write_header_to_file(args.outfile)
writer.write_kv_data_to_file()
writer.write_tensors_to_file()