gguf : track writer state, free unneeded tensors, cleanup (#3871)

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Jared Van Bortel 2023-11-07 12:43:04 -05:00 committed by GitHub
parent 413503d4b9
commit 0a7c980b6f
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2 changed files with 54 additions and 30 deletions

View file

@ -646,18 +646,17 @@ class GGUFValueType(IntEnum):
sys.exit()
class WriterState(Enum):
EMPTY = auto()
HEADER = auto()
KV_DATA = auto()
TI_DATA = auto()
class GGUFWriter:
fout: BufferedWriter
arch: str
offset_tensor = 0
data_alignment = GGUF_DEFAULT_ALIGNMENT
kv_data = b""
kv_data_count = 0
ti_data = b""
ti_data_count = 0
use_temp_file: bool
temp_file: tempfile.SpooledTemporaryFile[bytes] | None = None
tensors: list[tuple[np.ndarray[Any, Any], int]]
temp_file: tempfile.SpooledTemporaryFile[bytes] | None
tensors: list[np.ndarray[Any, Any]]
@property
def pack_prefix(self):
@ -683,27 +682,47 @@ class GGUFWriter:
GGUFValueType.FLOAT64: f"{self.pack_prefix}d",
GGUFValueType.BOOL: "?" ,
}
self.add_architecture()
self.offset_tensor = 0
self.data_alignment = GGUF_DEFAULT_ALIGNMENT
self.kv_data = b""
self.kv_data_count = 0
self.ti_data = b""
self.ti_data_count = 0
self.use_temp_file = use_temp_file
self.temp_file = None
self.tensors = []
endianess_str = "Big Endian" if self.endianess == GGUFEndian.BIG else "Little Endian"
print(f"This gguf file is for {endianess_str} only")
self.state = WriterState.EMPTY
self.add_architecture()
def write_header_to_file(self):
if self.state is not WriterState.EMPTY:
raise ValueError(f'Expected output file to be empty, got {self.state}')
self.fout.write(struct.pack("<I", GGUF_MAGIC))
self.fout.write(struct.pack(f"{self.pack_prefix}I", GGUF_VERSION))
self.fout.write(struct.pack(f"{self.pack_prefix}Q", self.ti_data_count))
self.fout.write(struct.pack(f"{self.pack_prefix}Q", self.kv_data_count))
self.flush()
# print("tensors " + str(self.ti_data_count) + " kv " + str(self.kv_data_count))
self.state = WriterState.HEADER
def write_kv_data_to_file(self):
if self.state is not WriterState.HEADER:
raise ValueError(f'Expected output file to contain the header, got {self.state}')
self.fout.write(self.kv_data)
self.flush()
self.state = WriterState.KV_DATA
def write_ti_data_to_file(self):
if self.state is not WriterState.KV_DATA:
raise ValueError(f'Expected output file to contain KV data, got {self.state}')
self.fout.write(self.ti_data)
self.flush()
self.state = WriterState.TI_DATA
def add_key(self, key: str):
self.add_val(key, GGUFValueType.STRING, add_vtype=False)
@ -796,6 +815,9 @@ class GGUFWriter:
return ((x + n - 1) // n) * n
def add_tensor_info(self, name: str, tensor_shape: Sequence[int], tensor_dtype: np.dtype[np.float16] | np.dtype[np.float32], tensor_nbytes: int, raw_dtype: GGMLQuantizationType | None = None):
if self.state is not WriterState.EMPTY:
raise ValueError(f'Expected output file to be empty, got {self.state}')
assert raw_dtype is not None or tensor_dtype in (np.float32, np.float16), "Only F32 and F16 tensors are supported for now"
encoded_name = name.encode("utf8")
@ -825,23 +847,22 @@ class GGUFWriter:
shape: Sequence[int] = raw_shape if raw_shape is not None else tensor.shape
self.add_tensor_info(name, shape, tensor.dtype, tensor.nbytes, raw_dtype = raw_dtype)
pad = GGUFWriter.ggml_pad(tensor.nbytes, self.data_alignment) - tensor.nbytes
if self.temp_file is None:
self.tensors.append((tensor, pad))
if self.temp_file is None:
self.tensors.append(tensor)
return
tensor.tofile(self.temp_file)
self.write_padding(self.temp_file, tensor.nbytes)
if pad != 0:
self.temp_file.write(bytes([0] * pad))
def write_padding(self, fp: BinaryIO, n: int, align: int | None = None):
def write_padding(self, fp: IO[bytes], n: int, align: int | None = None):
pad = GGUFWriter.ggml_pad(n, align if align is not None else self.data_alignment) - n
if pad != 0:
fp.write(bytes([0] * pad))
def write_tensor_data(self, tensor: np.ndarray[Any, Any]):
if self.state is not WriterState.TI_DATA:
raise ValueError(f'Expected output file to contain tensor info, got {self.state}')
if self.endianess==GGUFEndian.BIG:
tensor.byteswap(inplace=True)
self.write_padding(self.fout, self.fout.tell())
@ -854,10 +875,13 @@ class GGUFWriter:
self.write_padding(self.fout, self.fout.tell())
if self.temp_file is None:
for (currtensor, currpad) in self.tensors:
currtensor.tofile(self.fout)
if currpad != 0:
self.fout.write(bytes([0] * currpad))
while True:
try:
tensor = self.tensors.pop(0)
except IndexError:
break
tensor.tofile(self.fout)
self.write_padding(self.fout, tensor.nbytes)
return
self.temp_file.seek(0)
@ -1002,11 +1026,8 @@ class GGUFWriter:
class SpecialVocab:
load_merges: bool = False
merges: list[str] = []
special_token_types: tuple[str, ...] = ('bos', 'eos', 'unk', 'sep', 'pad')
special_token_ids: dict[str, int] = {}
n_vocab: int | None = None
merges: list[str]
special_token_ids: dict[str, int]
def __init__(
self, path: str | os.PathLike[str], load_merges: bool = False,
@ -1016,8 +1037,11 @@ class SpecialVocab:
self.special_token_ids = {}
self.n_vocab = n_vocab
self.load_merges = load_merges
self.merges = []
if special_token_types is not None:
self.special_token_types = special_token_types
else:
self.special_token_types = ('bos', 'eos', 'unk', 'sep', 'pad')
self._load(Path(path))
def _load(self, path: Path) -> None:

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@ -1,6 +1,6 @@
[tool.poetry]
name = "gguf"
version = "0.4.5"
version = "0.4.6"
description = "Write ML models in GGUF for GGML"
authors = ["GGML <ggml@ggml.ai>"]
packages = [