vbatts/llama.cpp
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gguf : enforce that tensor names are unique (#6905)

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* not allow adding duplicated tensor name

* no duplicated tensor while reading gguf

* typo

* throw exception inside llama_model_loader

Co-authored-by: slaren <slarengh@gmail.com>

---------

Co-authored-by: slaren <slarengh@gmail.com>
This commit is contained in:
Xuan Son Nguyen 2024-04-28 17:36:18 +02:00 • committed by GitHub
parent ce023f6f2f
commit 7bb36ccf91
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GPG key ID: B5690EEEBB952194
4 changed files with 32 additions and 1 deletions
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8
gguf-py/gguf/gguf_reader.py
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@ -234,8 +234,14 @@ class GGUFReader:
def _build_tensors(self, start_offs: int, fields: list[ReaderField]) -> None:
tensors = []
tensor_names = set() # keep track of name to prevent duplicated tensors
for field in fields:
_name_len, name_data, _n_dims, dims, raw_dtype, offset_tensor = field.parts
# check if there's any tensor having same name already in the list
tensor_name = str(bytes(name_data), encoding = 'utf-8')
if tensor_name in tensor_names:
raise ValueError(f'Found duplicated tensor with name {tensor_name}')
tensor_names.add(tensor_name)
ggml_type = GGMLQuantizationType(raw_dtype[0])
n_elems = np.prod(dims)
block_size, type_size = GGML_QUANT_SIZES[ggml_type]
@ -267,7 +273,7 @@ class GGUFReader:
item_count = n_bytes
item_type = np.uint8
tensors.append(ReaderTensor(
name = str(bytes(name_data), encoding = 'utf-8'),
name = tensor_name,
tensor_type = ggml_type,
shape = dims,
n_elements = n_elems,

5
gguf-py/gguf/gguf_writer.py
View file

@ -63,6 +63,7 @@ class GGUFWriter:
self.kv_data_count = 0
self.ti_data = bytearray()
self.ti_data_count = 0
self.ti_names = set()
self.use_temp_file = use_temp_file
self.temp_file = None
self.tensors = []
@ -197,6 +198,10 @@ class GGUFWriter:
if self.state is not WriterState.EMPTY:
raise ValueError(f'Expected output file to be empty, got {self.state}')
if name in self.ti_names:
raise ValueError(f'Duplicated tensor name {name}')
self.ti_names.add(name)
encoded_name = name.encode("utf8")
self.ti_data += self._pack("Q", len(encoded_name))
self.ti_data += encoded_name