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https://github.com/ggerganov/llama.cpp.git
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gguf : track writer state, free unneeded tensors, cleanup (#3871)
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413503d4b9
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@ -646,18 +646,17 @@ class GGUFValueType(IntEnum):
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sys.exit()
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class WriterState(Enum):
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EMPTY = auto()
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HEADER = auto()
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KV_DATA = auto()
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TI_DATA = auto()
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class GGUFWriter:
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fout: BufferedWriter
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arch: str
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offset_tensor = 0
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data_alignment = GGUF_DEFAULT_ALIGNMENT
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kv_data = b""
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kv_data_count = 0
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ti_data = b""
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ti_data_count = 0
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use_temp_file: bool
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temp_file: tempfile.SpooledTemporaryFile[bytes] | None = None
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tensors: list[tuple[np.ndarray[Any, Any], int]]
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temp_file: tempfile.SpooledTemporaryFile[bytes] | None
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tensors: list[np.ndarray[Any, Any]]
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@property
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def pack_prefix(self):
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@ -683,27 +682,47 @@ class GGUFWriter:
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GGUFValueType.FLOAT64: f"{self.pack_prefix}d",
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GGUFValueType.BOOL: "?" ,
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}
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self.add_architecture()
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self.offset_tensor = 0
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self.data_alignment = GGUF_DEFAULT_ALIGNMENT
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self.kv_data = b""
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self.kv_data_count = 0
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self.ti_data = b""
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self.ti_data_count = 0
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self.use_temp_file = use_temp_file
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self.temp_file = None
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self.tensors = []
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endianess_str = "Big Endian" if self.endianess == GGUFEndian.BIG else "Little Endian"
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print(f"This gguf file is for {endianess_str} only")
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self.state = WriterState.EMPTY
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self.add_architecture()
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def write_header_to_file(self):
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if self.state is not WriterState.EMPTY:
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raise ValueError(f'Expected output file to be empty, got {self.state}')
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self.fout.write(struct.pack("<I", GGUF_MAGIC))
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self.fout.write(struct.pack(f"{self.pack_prefix}I", GGUF_VERSION))
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self.fout.write(struct.pack(f"{self.pack_prefix}Q", self.ti_data_count))
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self.fout.write(struct.pack(f"{self.pack_prefix}Q", self.kv_data_count))
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self.flush()
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# print("tensors " + str(self.ti_data_count) + " kv " + str(self.kv_data_count))
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self.state = WriterState.HEADER
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def write_kv_data_to_file(self):
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if self.state is not WriterState.HEADER:
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raise ValueError(f'Expected output file to contain the header, got {self.state}')
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self.fout.write(self.kv_data)
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self.flush()
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self.state = WriterState.KV_DATA
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def write_ti_data_to_file(self):
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if self.state is not WriterState.KV_DATA:
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raise ValueError(f'Expected output file to contain KV data, got {self.state}')
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self.fout.write(self.ti_data)
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self.flush()
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self.state = WriterState.TI_DATA
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def add_key(self, key: str):
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self.add_val(key, GGUFValueType.STRING, add_vtype=False)
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@ -796,6 +815,9 @@ class GGUFWriter:
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return ((x + n - 1) // n) * n
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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):
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if self.state is not WriterState.EMPTY:
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raise ValueError(f'Expected output file to be empty, got {self.state}')
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assert raw_dtype is not None or tensor_dtype in (np.float32, np.float16), "Only F32 and F16 tensors are supported for now"
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encoded_name = name.encode("utf8")
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@ -825,23 +847,22 @@ class GGUFWriter:
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shape: Sequence[int] = raw_shape if raw_shape is not None else tensor.shape
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self.add_tensor_info(name, shape, tensor.dtype, tensor.nbytes, raw_dtype = raw_dtype)
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pad = GGUFWriter.ggml_pad(tensor.nbytes, self.data_alignment) - tensor.nbytes
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if self.temp_file is None:
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self.tensors.append((tensor, pad))
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if self.temp_file is None:
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self.tensors.append(tensor)
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return
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tensor.tofile(self.temp_file)
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self.write_padding(self.temp_file, tensor.nbytes)
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if pad != 0:
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self.temp_file.write(bytes([0] * pad))
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def write_padding(self, fp: BinaryIO, n: int, align: int | None = None):
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def write_padding(self, fp: IO[bytes], n: int, align: int | None = None):
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pad = GGUFWriter.ggml_pad(n, align if align is not None else self.data_alignment) - n
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if pad != 0:
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fp.write(bytes([0] * pad))
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def write_tensor_data(self, tensor: np.ndarray[Any, Any]):
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if self.state is not WriterState.TI_DATA:
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raise ValueError(f'Expected output file to contain tensor info, got {self.state}')
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if self.endianess==GGUFEndian.BIG:
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tensor.byteswap(inplace=True)
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self.write_padding(self.fout, self.fout.tell())
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@ -854,10 +875,13 @@ class GGUFWriter:
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self.write_padding(self.fout, self.fout.tell())
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if self.temp_file is None:
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for (currtensor, currpad) in self.tensors:
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currtensor.tofile(self.fout)
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if currpad != 0:
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self.fout.write(bytes([0] * currpad))
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while True:
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try:
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tensor = self.tensors.pop(0)
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except IndexError:
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break
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tensor.tofile(self.fout)
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self.write_padding(self.fout, tensor.nbytes)
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return
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self.temp_file.seek(0)
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@ -1002,11 +1026,8 @@ class GGUFWriter:
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class SpecialVocab:
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load_merges: bool = False
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merges: list[str] = []
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special_token_types: tuple[str, ...] = ('bos', 'eos', 'unk', 'sep', 'pad')
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special_token_ids: dict[str, int] = {}
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n_vocab: int | None = None
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merges: list[str]
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special_token_ids: dict[str, int]
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def __init__(
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self, path: str | os.PathLike[str], load_merges: bool = False,
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@ -1016,8 +1037,11 @@ class SpecialVocab:
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self.special_token_ids = {}
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self.n_vocab = n_vocab
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self.load_merges = load_merges
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self.merges = []
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if special_token_types is not None:
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self.special_token_types = special_token_types
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else:
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self.special_token_types = ('bos', 'eos', 'unk', 'sep', 'pad')
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self._load(Path(path))
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def _load(self, path: Path) -> None:
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@ -1,6 +1,6 @@
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[tool.poetry]
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name = "gguf"
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version = "0.4.5"
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version = "0.4.6"
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description = "Write ML models in GGUF for GGML"
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authors = ["GGML <ggml@ggml.ai>"]
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packages = [
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