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gguf.py : no need to convert tensors twice

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klosax
2023-08-12 21:45:45 +02:00
committed by GitHub
parent 60d540831b
commit 5d81a715d4
1 changed files with 6 additions and 6 deletions
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gguf.py
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@@ -179,20 +179,20 @@ class GGUFWriter:
def ggml_pad(x: int, n: int) -> int: def ggml_pad(x: int, n: int) -> int:
return ((x + n - 1) // n) * n return ((x + n - 1) // n) * n
def add_tensor_info(self, name: str, tensor: np.ndarray): def add_tensor_info(self, name: str, tensor_shape: np.ndarray, tensor_dtype: np.dtype, tensor_nbytes: int):
encoded_name = name.encode("utf8") encoded_name = name.encode("utf8")
self.ti_data += struct.pack("<I", len(encoded_name)) self.ti_data += struct.pack("<I", len(encoded_name))
self.ti_data += encoded_name self.ti_data += encoded_name
n_dims = len(tensor.shape) n_dims = len(tensor_shape)
self.ti_data += struct.pack("<I", n_dims) self.ti_data += struct.pack("<I", n_dims)
for i in range(n_dims): for i in range(n_dims):
self.ti_data += struct.pack("<I", tensor.shape[n_dims - 1 - i]) self.ti_data += struct.pack("<I", tensor_shape[n_dims - 1 - i])
assert tensor.dtype in (np.float32, np.float16), "Only F32 and F16 tensors are supported for now" assert tensor_dtype in (np.float32, np.float16), "Only F32 and F16 tensors are supported for now"
dtype = GGMLQuantizationType.F32 if tensor.dtype == np.float32 else GGMLQuantizationType.F16 dtype = GGMLQuantizationType.F32 if tensor_dtype == np.float32 else GGMLQuantizationType.F16
self.ti_data += struct.pack("<I", dtype) self.ti_data += struct.pack("<I", dtype)
self.ti_data += struct.pack("<Q", self.offset_tensor) self.ti_data += struct.pack("<Q", self.offset_tensor)
self.offset_tensor += GGUFWriter.ggml_pad(tensor.nbytes, self.data_alignment) self.offset_tensor += GGUFWriter.ggml_pad(tensor_nbytes, self.data_alignment)
self.ti_data_count += 1 self.ti_data_count += 1
def write_tensor_to_file(self, tensor: np.ndarray): def write_tensor_to_file(self, tensor: np.ndarray):