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import os
from typing import Dict, Optional, Union
import numpy as np
import paddle
from safetensors import numpy
def save(tensors: Dict[str, paddle.Tensor], metadata: Optional[Dict[str, str]] = None) -> bytes:
"""
Saves a dictionary of tensors into raw bytes in safetensors format.
Args:
tensors (`Dict[str, paddle.Tensor]`):
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.paddle import save
import paddle
tensors = {"embedding": paddle.zeros((512, 1024)), "attention": paddle.zeros((256, 256))}
byte_data = save(tensors)
```
"""
np_tensors = _paddle2np(tensors)
return numpy.save(np_tensors, metadata=metadata)
def save_file(
tensors: Dict[str, paddle.Tensor],
filename: Union[str, os.PathLike],
metadata: Optional[Dict[str, str]] = None,
) -> None:
"""
Saves a dictionary of tensors into raw bytes in safetensors format.
Args:
tensors (`Dict[str, paddle.Tensor]`):
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.paddle import save_file
import paddle
tensors = {"embedding": paddle.zeros((512, 1024)), "attention": paddle.zeros((256, 256))}
save_file(tensors, "model.safetensors")
```
"""
np_tensors = _paddle2np(tensors)
return numpy.save_file(np_tensors, filename, metadata=metadata)
def load(data: bytes, device: str = "cpu") -> Dict[str, paddle.Tensor]:
"""
Loads a safetensors file into paddle format from pure bytes.
Args:
data (`bytes`):
The content of a safetensors file
Returns:
`Dict[str, paddle.Tensor]`: dictionary that contains name as key, value as `paddle.Tensor` on cpu
Example:
```python
from safetensors.paddle import load
file_path = "./my_folder/bert.safetensors"
with open(file_path, "rb") as f:
data = f.read()
loaded = load(data)
```
"""
flat = numpy.load(data)
return _np2paddle(flat, device)
def load_file(filename: Union[str, os.PathLike], device="cpu") -> Dict[str, paddle.Tensor]:
"""
Loads a safetensors file into paddle format.
Args:
filename (`str`, or `os.PathLike`)):
The name of the file which contains the tensors
device (`Dict[str, any]`, *optional*, defaults to `cpu`):
The device where the tensors need to be located after load.
available options are all regular paddle device locations
Returns:
`Dict[str, paddle.Tensor]`: dictionary that contains name as key, value as `paddle.Tensor`
Example:
```python
from safetensors.paddle import load_file
file_path = "./my_folder/bert.safetensors"
loaded = load_file(file_path)
```
"""
flat = numpy.load_file(filename)
output = _np2paddle(flat, device)
return output
def _np2paddle(numpy_dict: Dict[str, np.ndarray], device: str = "cpu") -> Dict[str, paddle.Tensor]:
for k, v in numpy_dict.items():
numpy_dict[k] = paddle.to_tensor(v, place=device)
return numpy_dict
def _paddle2np(paddle_dict: Dict[str, paddle.Tensor]) -> Dict[str, np.array]:
for k, v in paddle_dict.items():
paddle_dict[k] = v.detach().cpu().numpy()
return paddle_dict
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