1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
|
#!/usr/bin/env python3
# Original by https://github.com/eiz
# https://github.com/ggerganov/llama.cpp/issues/324#issuecomment-1476227818
import argparse
import glob
import os
import struct
import sys
from sentencepiece import SentencePieceProcessor
HPARAMS = keys = ["vocab_size", "dim", "multiple_of", "n_heads", "n_layers"]
def parse_args():
parser = argparse.ArgumentParser(description='Upgrade old ggml model files to the current format')
parser.add_argument('dir_model', help='directory containing ggml .bin files')
parser.add_argument('tokenizer_model', help='path to LLaMA tokenizer.model file')
return parser.parse_args()
def read_header(f_in):
struct_fmt = "i" * (3 + len(HPARAMS))
struct_size = struct.calcsize(struct_fmt)
buf = f_in.read(struct_size)
return struct.unpack(struct_fmt, buf)
def write_header(f_out, header):
(magic, vocab_size, dim, multiple_of, n_heads, n_layers, rot, ftype) = header
if magic != 0x67676d6c:
raise Exception('Invalid file magic. Must be an old style ggml file.')
values = [
0x67676d66, # magic: ggml in hex
1, # file version
vocab_size,
dim,
multiple_of,
n_heads,
n_layers,
rot,
ftype
]
f_out.write(struct.pack("i" * len(values), *values))
def write_tokens(fout, tokenizer):
for i in range(tokenizer.vocab_size()):
if tokenizer.is_unknown(i):
text = " \u2047 ".encode("utf-8")
elif tokenizer.is_control(i):
text = b""
elif tokenizer.is_byte(i):
piece = tokenizer.id_to_piece(i)
if len(piece) != 6:
print(f"Invalid token: {piece}")
sys.exit(1)
byte_value = int(piece[3:-1], 16)
text = struct.pack("B", byte_value)
else:
text = tokenizer.id_to_piece(i).replace("\u2581", " ").encode("utf-8")
fout.write(struct.pack("i", len(text)))
fout.write(text)
fout.write(struct.pack("f", tokenizer.get_score(i)))
def read_tokens(f_in, tokenizer):
for i in range(tokenizer.vocab_size()):
len_b = f_in.read(4)
(length,) = struct.unpack("i", len_b)
f_in.read(length)
def copy_all_data(f_out, f_in):
while True:
buf = f_in.read(1024 * 1024)
if not buf:
break
f_out.write(buf)
def convert_one_file(path_in, tokenizer):
path_tmp = f"{path_in}.tmp"
path_orig= f"{path_in}.orig"
print(f"converting {path_in}")
with open(path_in, "rb") as f_in, open(path_tmp, "wb") as f_out:
write_header(f_out, read_header(f_in))
read_tokens(f_in, tokenizer)
write_tokens(f_out, tokenizer)
copy_all_data(f_out, f_in)
os.rename(path_in, path_orig)
os.rename(path_tmp, path_in)
def main():
args = parse_args()
files = []
files.extend(glob.glob(f"{args.dir_model}/*.bin"))
files.extend(glob.glob(f"{args.dir_model}/*.bin.*"))
tokenizer = SentencePieceProcessor(args.tokenizer_model)
for file in files:
convert_one_file(file, tokenizer)
if __name__ == "__main__":
main()
|
