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refactor: Further refine functionality, improve user interaction, and streamline vocabulary handling
- Renamed command-line arguments for clarity and consistency. - Improved path resolution and import adjustments for robustness. - Thoughtfully handled 'awq-path' and conditional logic for the weighted model. - Enhanced model and vocabulary loading with the 'VocabFactory' class for structured and adaptable loading. - Strengthened error handling and user feedback for a more user-friendly experience. - Structured output file handling with clear conditions and defaults. - Streamlined and organized the 'main' function for better logic flow. - Passed 'sys.argv[1:]' to 'main' for adaptability and testability. These changes solidify the script's functionality, making it more robust, user-friendly, and adaptable. The use of the 'VocabFactory' class is a notable enhancement in efficient vocabulary handling, reflecting a thoughtful and iterative approach to script development.
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convert.py

Lines changed: 54 additions & 44 deletions
Original file line numberDiff line numberDiff line change
@@ -1555,8 +1555,9 @@ def main(argv: Optional[list[str]] = None) -> None:
15551555
args = parser.parse_args(argv)
15561556

15571557
if args.awq_path:
1558-
sys.path.insert(1, str(Path(__file__).parent / 'awq-py'))
1558+
sys.path.insert(1, str(Path(__file__).resolve().parent / "awq-py"))
15591559
from awq.apply_awq import add_scale_weights
1560+
15601561
tmp_model_path = args.model / "weighted_model"
15611562
if tmp_model_path.is_dir():
15621563
print(f"{tmp_model_path} exists as a weighted model.")
@@ -1575,74 +1576,83 @@ def main(argv: Optional[list[str]] = None) -> None:
15751576
if not args.vocab_only:
15761577
model_plus = load_some_model(args.model)
15771578
else:
1578-
model_plus = ModelPlus(model = {}, paths = [args.model / 'dummy'], format = 'none', vocab = None)
1579+
model_plus = ModelPlus(
1580+
model={}, paths=[args.model / "dummy"], format="none", vocab=None
1581+
)
15791582

15801583
if args.dump:
15811584
do_dump_model(model_plus)
15821585
return
1586+
15831587
endianess = gguf.GGUFEndian.LITTLE
1584-
if args.bigendian:
1588+
if args.big_endian:
15851589
endianess = gguf.GGUFEndian.BIG
15861590

15871591
params = Params.load(model_plus)
15881592
if params.n_ctx == -1:
15891593
if args.ctx is None:
1590-
raise Exception("The model doesn't have a context size, and you didn't specify one with --ctx\n"
1591-
"Please specify one with --ctx:\n"
1592-
" - LLaMA v1: --ctx 2048\n"
1593-
" - LLaMA v2: --ctx 4096\n")
1594+
raise Exception(
1595+
"The model doesn't have a context size, and you didn't specify one with --ctx\n"
1596+
"Please specify one with --ctx:\n"
1597+
" - LLaMA v1: --ctx 2048\n"
1598+
" - LLaMA v2: --ctx 4096\n"
1599+
)
15941600
params.n_ctx = args.ctx
15951601

1596-
if args.outtype:
1602+
if args.out_type:
15971603
params.ftype = {
15981604
"f32": GGMLFileType.AllF32,
15991605
"f16": GGMLFileType.MostlyF16,
16001606
"q8_0": GGMLFileType.MostlyQ8_0,
1601-
}[args.outtype]
1607+
}[args.out_type]
16021608

16031609
print(f"params = {params}")
16041610

1605-
vocab: Vocab
1611+
model_parent_path = model_plus.paths[0].parent
1612+
vocab_path = Path(args.vocab_dir or args.model or model_parent_path)
1613+
vocab_factory = VocabFactory(vocab_path)
1614+
vocab, special_vocab = vocab_factory.load_vocab(args.vocab_type, model_parent_path)
1615+
16061616
if args.vocab_only:
1607-
if not args.outfile:
1608-
raise ValueError("need --outfile if using --vocab-only")
1609-
# FIXME: Try to respect vocab_dir somehow?
1610-
vocab = VocabLoader(params, args.vocab_dir or args.model)
1611-
special_vocab = gguf.SpecialVocab(model_plus.paths[0].parent,
1612-
load_merges = True,
1613-
n_vocab = vocab.vocab_size)
1614-
outfile = args.outfile
1615-
OutputFile.write_vocab_only(outfile, params, vocab, special_vocab,
1616-
endianess = endianess, pad_vocab = args.padvocab)
1617-
print(f"Wrote {outfile}")
1617+
if not args.out_file:
1618+
raise ValueError("need --out-file if using --vocab-only")
1619+
out_file = args.out_file
1620+
OutputFile.write_vocab_only(
1621+
out_file,
1622+
params,
1623+
vocab,
1624+
special_vocab,
1625+
endianess=endianess,
1626+
pad_vocab=args.pad_vocab,
1627+
)
1628+
print(f"Wrote {out_file}")
16181629
return
16191630

16201631
if model_plus.vocab is not None and args.vocab_dir is None:
16211632
vocab = model_plus.vocab
1622-
else:
1623-
vocab_dir = args.vocab_dir if args.vocab_dir else model_plus.paths[0].parent
1624-
vocab = VocabLoader(params, vocab_dir)
1625-
1626-
# FIXME: Try to respect vocab_dir somehow?
1627-
print(f"Vocab info: {vocab}")
1628-
special_vocab = gguf.SpecialVocab(model_plus.paths[0].parent,
1629-
load_merges = True,
1630-
n_vocab = vocab.vocab_size)
1631-
1632-
print(f"Special vocab info: {special_vocab}")
1633-
model = model_plus.model
1634-
model = convert_model_names(model, params)
1635-
ftype = pick_output_type(model, args.outtype)
1636-
model = convert_to_output_type(model, ftype)
1637-
outfile = args.outfile or default_outfile(model_plus.paths, ftype)
16381633

1639-
params.ftype = ftype
1640-
print(f"Writing {outfile}, format {ftype}")
1634+
model = model_plus.model
1635+
model = convert_model_names(model, params)
1636+
ftype = pick_output_type(model, args.out_type)
1637+
model = convert_to_output_type(model, ftype)
1638+
out_file = args.out_file or default_output_file(model_plus.paths, ftype)
16411639

1642-
OutputFile.write_all(outfile, ftype, params, model, vocab, special_vocab,
1643-
concurrency = args.concurrency, endianess = endianess, pad_vocab = args.padvocab)
1644-
print(f"Wrote {outfile}")
1640+
params.ftype = ftype
1641+
print(f"Writing {out_file}, format {ftype}")
1642+
1643+
OutputFile.write_all(
1644+
out_file,
1645+
ftype,
1646+
params,
1647+
model,
1648+
vocab,
1649+
special_vocab,
1650+
concurrency=args.concurrency,
1651+
endianess=endianess,
1652+
pad_vocab=args.pad_vocab,
1653+
)
1654+
print(f"Wrote {out_file}")
16451655

16461656

1647-
if __name__ == '__main__':
1648-
main()
1657+
if __name__ == "__main__":
1658+
main(sys.argv[1:]) # Exclude the first element (script name) from sys.argv

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