llama.cpp/gguf-py/scripts/gguf_convert_endian.py
Georgi Gerganov e235b267a2
py : switch to snake_case (#8305)
* py : switch to snake_case

ggml-ci

* cont

ggml-ci

* cont

ggml-ci

* cont : fix link

* gguf-py : use snake_case in scripts entrypoint export

* py : rename requirements for convert_legacy_llama.py

Needed for scripts/check-requirements.sh

---------

Co-authored-by: Francis Couture-Harpin <git@compilade.net>
2024-07-05 07:53:33 +03:00

135 lines
5.2 KiB
Python
Executable File

#!/usr/bin/env python3
from __future__ import annotations
import logging
import argparse
import os
import sys
from tqdm import tqdm
from pathlib import Path
import numpy as np
# Necessary to load the local gguf package
if "NO_LOCAL_GGUF" not in os.environ and (Path(__file__).parent.parent.parent / 'gguf-py').exists():
sys.path.insert(0, str(Path(__file__).parent.parent))
import gguf
logger = logging.getLogger("gguf-convert-endian")
def convert_byteorder(reader: gguf.GGUFReader, args: argparse.Namespace) -> None:
if np.uint32(1) == np.uint32(1).newbyteorder("<"):
# Host is little endian
host_endian = "little"
swapped_endian = "big"
else:
# Sorry PDP or other weird systems that don't use BE or LE.
host_endian = "big"
swapped_endian = "little"
if reader.byte_order == "S":
file_endian = swapped_endian
else:
file_endian = host_endian
order = host_endian if args.order == "native" else args.order
logger.info(f"* Host is {host_endian.upper()} endian, GGUF file seems to be {file_endian.upper()} endian")
if file_endian == order:
logger.info(f"* File is already {order.upper()} endian. Nothing to do.")
sys.exit(0)
logger.info("* Checking tensors for conversion compatibility")
for tensor in reader.tensors:
if tensor.tensor_type not in (
gguf.GGMLQuantizationType.F32,
gguf.GGMLQuantizationType.F16,
gguf.GGMLQuantizationType.Q8_0,
):
raise ValueError(f"Cannot handle type {tensor.tensor_type.name} for tensor {repr(tensor.name)}")
logger.info(f"* Preparing to convert from {file_endian.upper()} to {order.upper()}")
if args.dry_run:
return
logger.warning("*** Warning *** Warning *** Warning **")
logger.warning("* This conversion process may damage the file. Ensure you have a backup.")
if order != host_endian:
logger.warning("* Requested endian differs from host, you will not be able to load the model on this machine.")
logger.warning("* The file will be modified immediately, so if conversion fails or is interrupted")
logger.warning("* the file will be corrupted. Enter exactly YES if you are positive you want to proceed:")
response = input("YES, I am sure> ")
if response != "YES":
logger.warning("You didn't enter YES. Okay then, see ya!")
sys.exit(0)
logger.info(f"* Converting fields ({len(reader.fields)})")
for idx, field in enumerate(reader.fields.values()):
logger.info(f"- {idx:4}: Converting field {repr(field.name)}, part count: {len(field.parts)}")
for part in field.parts:
part.byteswap(inplace=True)
logger.info(f"* Converting tensors ({len(reader.tensors)})")
for idx, tensor in enumerate(pbar := tqdm(reader.tensors, desc="Converting tensor")):
log_message = (
f"Converting tensor {repr(tensor.name)}, "
f"type={tensor.tensor_type.name}, "
f"elements={tensor.n_elements} "
)
# Byte-swap each part of the tensor's field
for part in tensor.field.parts:
part.byteswap(inplace=True)
# Byte-swap tensor data if necessary
if tensor.tensor_type == gguf.GGMLQuantizationType.Q8_0:
# Handle Q8_0 tensor blocks (block_q8_0)
# Specific handling of block_q8_0 is required.
# Each block_q8_0 consists of an f16 delta (scaling factor) followed by 32 int8 quantizations.
block_size = 34 # 34 bytes = <f16 delta scaling factor> + 32 * <int8 quant>
n_blocks = len(tensor.data) // block_size
for block_num in (inner_pbar := tqdm(range(n_blocks), desc="Byte-swapping Blocks", leave=False)):
block_offs = block_num * block_size
# Byte-Swap f16 sized delta field
delta = tensor.data[block_offs:block_offs + 2].view(dtype=np.uint16)
delta.byteswap(inplace=True)
# Byte-Swap Q8 weights
if block_num % 100000 == 0:
inner_pbar.set_description(f"Byte-swapping Blocks [{(n_blocks - block_num) // n_blocks}]")
else:
# Handle other tensor types
tensor.data.byteswap(inplace=True)
pbar.set_description(log_message)
logger.info("* Completion")
def main() -> None:
parser = argparse.ArgumentParser(description="Convert GGUF file byte order")
parser.add_argument(
"model", type=str,
help="GGUF format model filename",
)
parser.add_argument(
"order", type=str, choices=['big', 'little', 'native'],
help="Requested byte order",
)
parser.add_argument(
"--dry-run", action="store_true",
help="Don't actually change anything",
)
parser.add_argument("--verbose", action="store_true", help="increase output verbosity")
args = parser.parse_args(None if len(sys.argv) > 1 else ["--help"])
logging.basicConfig(level=logging.DEBUG if args.verbose else logging.INFO)
logger.info(f'* Loading: {args.model}')
reader = gguf.GGUFReader(args.model, 'r' if args.dry_run else 'r+')
convert_byteorder(reader, args)
if __name__ == "__main__":
main()