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import os
import sys
from typing import Dict, Optional, Union
import numpy as np
from safetensors import deserialize, safe_open, serialize, serialize_file
def _tobytes(tensor: np.ndarray) -> bytes:
if not _is_little_endian(tensor):
tensor = tensor.byteswap(inplace=False)
return tensor.tobytes()
def save(tensor_dict: Dict[str, np.ndarray], metadata: Optional[Dict[str, str]] = None) -> bytes:
"""
Saves a dictionary of tensors into raw bytes in safetensors format.
Args:
tensor_dict (`Dict[str, np.ndarray]`):
The incoming tensors. Tensors need to be contiguous and dense.
metadata (`Dict[str, str]`, *optional*, defaults to `None`):
Optional text only metadata you might want to save in your header.
For instance it can be useful to specify more about the underlying
tensors. This is purely informative and does not affect tensor loading.
Returns:
`bytes`: The raw bytes representing the format
Example:
```python
from safetensors.numpy import save
import numpy as np
tensors = {"embedding": np.zeros((512, 1024)), "attention": np.zeros((256, 256))}
byte_data = save(tensors)
```
"""
flattened = {k: {"dtype": v.dtype.name, "shape": v.shape, "data": _tobytes(v)} for k, v in tensor_dict.items()}
serialized = serialize(flattened, metadata=metadata)
result = bytes(serialized)
return result
def save_file(
tensor_dict: Dict[str, np.ndarray], filename: Union[str, os.PathLike], metadata: Optional[Dict[str, str]] = None
) -> None:
"""
Saves a dictionary of tensors into raw bytes in safetensors format.
Args:
tensor_dict (`Dict[str, np.ndarray]`):
The incoming tensors. Tensors need to be contiguous and dense.
filename (`str`, or `os.PathLike`)):
The filename we're saving into.
metadata (`Dict[str, str]`, *optional*, defaults to `None`):
Optional text only metadata you might want to save in your header.
For instance it can be useful to specify more about the underlying
tensors. This is purely informative and does not affect tensor loading.
Returns:
`None`
Example:
```python
from safetensors.numpy import save_file
import numpy as np
tensors = {"embedding": np.zeros((512, 1024)), "attention": np.zeros((256, 256))}
save_file(tensors, "model.safetensors")
```
"""
flattened = {k: {"dtype": v.dtype.name, "shape": v.shape, "data": _tobytes(v)} for k, v in tensor_dict.items()}
serialize_file(flattened, filename, metadata=metadata)
def load(data: bytes) -> Dict[str, np.ndarray]:
"""
Loads a safetensors file into numpy format from pure bytes.
Args:
data (`bytes`):
The content of a safetensors file
Returns:
`Dict[str, np.ndarray]`: dictionary that contains name as key, value as `np.ndarray` on cpu
Example:
```python
from safetensors.numpy import load
file_path = "./my_folder/bert.safetensors"
with open(file_path, "rb") as f:
data = f.read()
loaded = load(data)
```
"""
flat = deserialize(data)
return _view2np(flat)
def load_file(filename: Union[str, os.PathLike]) -> Dict[str, np.ndarray]:
"""
Loads a safetensors file into numpy format.
Args:
filename (`str`, or `os.PathLike`)):
The name of the file which contains the tensors
Returns:
`Dict[str, np.ndarray]`: dictionary that contains name as key, value as `np.ndarray`
Example:
```python
from safetensors.numpy import load_file
file_path = "./my_folder/bert.safetensors"
loaded = load_file(file_path)
```
"""
result = {}
with safe_open(filename, framework="np") as f:
for k in f.keys():
result[k] = f.get_tensor(k)
return result
_TYPES = {
"F64": np.float64,
"F32": np.float32,
"F16": np.float16,
"I64": np.int64,
"U64": np.uint64,
"I32": np.int32,
"U32": np.uint32,
"I16": np.int16,
"U16": np.uint16,
"I8": np.int8,
"U8": np.uint8,
"BOOL": bool,
}
def _getdtype(dtype_str: str) -> np.dtype:
return _TYPES[dtype_str]
def _view2np(safeview) -> Dict[str, np.ndarray]:
result = {}
for k, v in safeview:
dtype = _getdtype(v["dtype"])
arr = np.frombuffer(v["data"], dtype=dtype).reshape(v["shape"])
result[k] = arr
return result
def _is_little_endian(tensor: np.ndarray) -> bool:
byteorder = tensor.dtype.byteorder
if byteorder == "=":
if sys.byteorder == "little":
return True
else:
return False
elif byteorder == "|":
return True
elif byteorder == "<":
return True
elif byteorder == ">":
return False
raise ValueError(f"Unexpected byte order {byteorder}")
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