Vibe coded script + constants from mainline + pip requirements (#1405)

This commit is contained in:
saood06
2026-03-11 09:41:17 -05:00
committed by GitHub
parent 4d09e04501
commit 2161ee01cb
4 changed files with 217 additions and 0 deletions

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@@ -0,0 +1,209 @@
from __future__ import annotations
import os
import sys
import logging
import argparse
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("gguf-to-imatrix")
def _key_names(attr: str, fallback: str) -> set[str]:
"""Get possible GGUF key names, tolerating missing attributes."""
names = {fallback}
try:
names.add(getattr(gguf.Keys.IMatrix, attr))
except AttributeError:
pass
return names
CHUNK_COUNT_KEYS = _key_names('CHUNK_COUNT', 'imatrix.chunk_count')
CHUNK_SIZE_KEYS = _key_names('CHUNK_SIZE', 'imatrix.chunk_size')
DATASET_KEYS = _key_names('DATASETS', 'imatrix.datasets')
@dataclass
class IMatrixEntry:
values: npt.NDArray[np.float32]
counts: npt.NDArray[np.float32]
class IMatrixDatWriter:
"""Writes the old binary imatrix .dat format."""
def __init__(self, outfile: Path):
self.outfile = outfile
self.chunk_size: int = 512
self.chunk_count: int = 0
self.dataset: str = ""
self.entries: dict[str, IMatrixEntry] = {}
def write(self) -> None:
if self.chunk_size == 0:
raise ValueError("chunk_size is 0, cannot write imatrix")
with open(self.outfile, "wb") as f:
np.array([len(self.entries)], dtype=np.int32).tofile(f)
for name, entry in self.entries.items():
name_bytes = name.encode("utf-8")
np.array([len(name_bytes)], dtype=np.int32).tofile(f)
f.write(name_bytes)
ncall = int(entry.counts[0] / self.chunk_size)
np.array([ncall], dtype=np.int32).tofile(f)
np.array([len(entry.values)], dtype=np.int32).tofile(f)
(entry.values / np.float32(self.chunk_size)).astype(np.float32).tofile(f)
logger.debug(" %s: ncall=%d, nval=%d", name, ncall, len(entry.values))
np.array([self.chunk_count], dtype=np.int32).tofile(f)
dataset_bytes = self.dataset.encode("utf-8")
np.array([len(dataset_bytes)], dtype=np.int32).tofile(f)
if dataset_bytes:
f.write(dataset_bytes)
class GGUFIMatrixReader:
"""Reads imatrix data from a GGUF file."""
SUMS_SUFFIXES = (".sums", ".in_sum2")
COUNTS_SUFFIX = ".counts"
def __init__(self, gguf_path: Path):
reader = gguf.GGUFReader(gguf_path)
self.chunk_count: int = 0
self.chunk_size: int = 512
self.dataset: str = ""
self.entries: dict[str, IMatrixEntry] = {}
# --- Read KV metadata ---
for field in reader.fields.values():
key = field.name
if key in CHUNK_COUNT_KEYS:
val = int(field.parts[field.data[0]][0])
self.chunk_count = val
elif key in CHUNK_SIZE_KEYS:
val = int(field.parts[field.data[0]][0])
self.chunk_size = val
elif key in DATASET_KEYS:
val = bytes(field.parts[field.data[0]]).decode("utf-8")
self.dataset = val
# --- Read all tensors (copy + ensure float32) ---
tensor_map: dict[str, npt.NDArray[np.float32]] = {}
for tensor in reader.tensors:
tensor_map[tensor.name] = np.array(tensor.data, dtype=np.float32)
logger.debug(" Tensor: %s shape=%s", tensor.name, tensor_map[tensor.name].shape)
# --- Match sums/counts pairs ---
sums_tensors: dict[str, npt.NDArray[np.float32]] = {}
counts_tensors: dict[str, npt.NDArray[np.float32]] = {}
for tname, tdata in tensor_map.items():
matched_sum = False
for suffix in self.SUMS_SUFFIXES:
if tname.endswith(suffix):
sums_tensors[tname[:-len(suffix)]] = tdata
matched_sum = True
break
if not matched_sum and tname.endswith(self.COUNTS_SUFFIX):
counts_tensors[tname[:-len(self.COUNTS_SUFFIX)]] = tdata
for name, sums in sums_tensors.items():
counts = counts_tensors.get(name)
if counts is None:
logger.warning("No counts tensor for %r, assuming 0", name)
counts = np.array([0.0], dtype=np.float32)
self.entries[name] = IMatrixEntry(values=sums, counts=counts)
logger.info("Loaded %d imatrix entries from GGUF", len(self.entries))
# --- Diagnostic output if nothing matched ---
if not self.entries:
logger.error("No imatrix tensor pairs found!")
logger.error(
"Expected pairs like '<name>%s' + '<name>%s'",
self.SUMS_SUFFIXES[0], self.COUNTS_SUFFIX
)
if tensor_map:
logger.error("Tensors actually present in the file (%d):", len(tensor_map))
for n in sorted(tensor_map):
logger.error(" %s", n)
else:
logger.error("The file contains no tensors at all.")
logger.error(
"This file may not be a GGUF imatrix, or it may use a "
"naming convention this script doesn't recognize yet."
)
def to_writer(self, outfile: Path) -> IMatrixDatWriter:
writer = IMatrixDatWriter(outfile)
writer.chunk_count = self.chunk_count
writer.chunk_size = self.chunk_size
writer.dataset = self.dataset
writer.entries = self.entries
return writer
def parse_args():
parser = argparse.ArgumentParser(
description="Convert a GGUF imatrix file to the old imatrix.dat format")
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 a GGUF 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(".dat")
else:
args.outfile = Path(str(input_file) + ".dat")
if args.outfile.exists():
logger.error(
"Default output already exists, use --outfile to overwrite: %s",
args.outfile
)
sys.exit(1)
reader = GGUFIMatrixReader(args.imatrix)
if not reader.entries:
logger.error("Nothing to write (no entries). Re-run with --verbose for details.")
sys.exit(1)
writer = reader.to_writer(args.outfile)
writer.write()
logger.info("Wrote %d entries to %s", len(writer.entries), args.outfile)

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@@ -186,6 +186,11 @@ class Keys:
TYPE = "adapter.type"
LORA_ALPHA = "adapter.lora.alpha"
class IMatrix:
CHUNK_COUNT = "imatrix.chunk_count"
CHUNK_SIZE = "imatrix.chunk_size"
DATASETS = "imatrix.datasets"
#
# recommended mapping of model tensor names for storage in gguf
#
@@ -194,6 +199,7 @@ class Keys:
class GGUFType:
MODEL = "model"
ADAPTER = "adapter"
IMATRIX = "imatrix"
class MODEL_ARCH(IntEnum):

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@@ -11,3 +11,4 @@
-r ./requirements/requirements-convert_llama_ggml_to_gguf.txt
-r ./requirements/requirements-convert_lora_to_gguf.txt
-r ./requirements/requirements-tool_bench.txt
-r ./requirements/requirements-convert_imatrix_gguf_to_dat.txt

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@@ -0,0 +1 @@
numpy~=1.26.4