numpy.from_dlpack#

numpy.from_dlpack(x, /, *, device=None, copy=None)#

Create a NumPy array from an object implementing the __dlpack__ protocol. Generally, the returned NumPy array is a view of the input object. See [1] and [2] for more details.

Parameters:

xobject: A Python object that implements the __dlpack__ and __dlpack_device__ methods.
devicedevice, optional: Device on which to place the created array. Default: None. Must be "cpu" if passed which may allow importing an array that is not already CPU available.
copybool, optional: Boolean indicating whether or not to copy the input. If True, the copy will be made. If False, the function will never copy, and will raise BufferError in case a copy is deemed necessary. Passing it requests a copy from the exporter who may or may not implement the capability. If None, the function will reuse the existing memory buffer if possible and copy otherwise. Default: None.

Returns:

outndarray

References

[1]

Array API documentation, https://data-apis.org/array-api/latest/design_topics/data_interchange.html#syntax-for-data-interchange-with-dlpack

[2]

Python specification for DLPack, https://dmlc.github.io/dlpack/latest/python_spec.html

Examples

>>> import torch  
>>> x = torch.arange(10)  
>>> # create a view of the torch tensor "x" in NumPy
>>> y = np.from_dlpack(x)  