i! ddlmZddlZddlZddlmZddlmZ ddgZ GddejZ ejjedddd d ed e dzd edzd dfdZy))AnyN) _to_dlpack)Device DLDeviceType from_dlpackcHeZdZdZdZdZdZdZdZdZ dZ d Z d Z d Z d Zd ZdZdZy)r))))))) ) ) ) ) ))))N)__name__ __module__ __qualname__kDLCPUkDLCUDA kDLCUDAHost kDLOpenCL kDLVulkankDLMetalkDLVPIkDLROCM kDLROCMHost kDLExtDevkDLCUDAManaged kDLOneAPI kDLWebGPU kDLHexagonkDLMAIAL/var/www/html/engine/venv/lib/python3.12/site-packages/torch/utils/dlpack.pyrrsM FGKIIH FGKINIIJGr+ato_dlpack(tensor) -> PyCapsule Returns an opaque object (a "DLPack capsule") representing the tensor. .. note:: ``to_dlpack`` is a legacy DLPack interface. The capsule it returns cannot be used for anything in Python other than use it as input to ``from_dlpack``. The more idiomatic use of DLPack is to call ``from_dlpack`` directly on the tensor object - this works when that object has a ``__dlpack__`` method, which PyTorch and most other libraries indeed have now. .. warning:: Only call ``from_dlpack`` once per capsule produced with ``to_dlpack``. Behavior when a capsule is consumed multiple times is undefined. Args: tensor: a tensor to be exported The DLPack capsule shares the tensor's memory. )devicecopy ext_tensorr-r.returnz torch.Tensorc t|dri}d|d<|}d}d}|||d<|j}|t|trt j |}t|tj st dt|tjj|}||k7}|s||d <|r|durtd |d |d |d tjtjfvr_tjjd|d} |d tjk(} | r| j d k(rdn | j } | |d<d} |j"di|} | %|j'dd |j"di|} | '|j'ddd} |j"di|} | $|j'd d|j"di|} tjj)| } |dur|s|s| j+} |r| j-|} | S|| t d|} tjj)| S#t$$rYwxYw#t$$rYwxYw#t$$rYwxYw)afrom_dlpack(ext_tensor) -> Tensor Converts a tensor from an external library into a ``torch.Tensor``. The returned PyTorch tensor will share the memory with the input tensor (which may have come from another library). Note that in-place operations will therefore also affect the data of the input tensor. This may lead to unexpected issues (e.g., other libraries may have read-only flags or immutable data structures), so the user should only do this if they know for sure that this is fine. Args: ext_tensor (object with ``__dlpack__`` attribute, or a DLPack capsule): The tensor or DLPack capsule to convert. If ``ext_tensor`` is a tensor (or ndarray) object, it must support the ``__dlpack__`` protocol (i.e., have a ``ext_tensor.__dlpack__`` method). Otherwise ``ext_tensor`` may be a DLPack capsule, which is an opaque ``PyCapsule`` instance, typically produced by a ``to_dlpack`` function or method. device (torch.device or str or None): An optional PyTorch device specifying where to place the new tensor. If None (default), the new tensor will be on the same device as ``ext_tensor``. copy (bool or None): An optional boolean indicating whether or not to copy ``self``. If None, PyTorch will copy only if necessary. Examples:: >>> import torch.utils.dlpack >>> t = torch.arange(4) # Convert a tensor directly (supported in PyTorch >= 1.10) >>> t2 = torch.from_dlpack(t) >>> t2[:2] = -1 # show that memory is shared >>> t2 tensor([-1, -1, 2, 3]) >>> t tensor([-1, -1, 2, 3]) # The old-style DLPack usage, with an intermediate capsule object >>> capsule = torch.utils.dlpack.to_dlpack(t) >>> capsule >>> t3 = torch.from_dlpack(capsule) >>> t3 tensor([-1, -1, 2, 3]) >>> t3[0] = -9 # now we're sharing memory between 3 tensors >>> t3 tensor([-9, -1, 2, 3]) >>> t2 tensor([-9, -1, 2, 3]) >>> t tensor([-9, -1, 2, 3]) __dlpack__)r r max_versionTFNr.z&from_dlpack: unsupported device type: dl_devicez&cannot move DLPack tensor from device z to z- without copying. Set copy=None or copy=True.rzcuda:r streamzQdevice and copy kwargs not supported when ext_tensor is already a DLPack capsule.r*)hasattr__dlpack_device__ isinstancestrtorchr-AssertionErrortype_C_torchDeviceToDLDevice ValueErrorrrr"cudacurrent_stream cuda_streamr2 TypeErrorpop _from_dlpackcloneto)r/r-r.kwargsrequested_copyproducer_handled_copycross_device_transfer ext_devicetarget_dl_devicer5is_cuda stream_ptrdlpacktensors r,rr:s@z<("$ &} $ %  !F6N  113  &#&f-fell3$'MdSYl^%\]] %xx>>vF &03C%C !)&6{#%  JJ}d + ...88 > JJvt $$) ! ...88 > JJ{D )*Z**4V4F&&v. T !*?H]\\^F !YYv&F   !1 c xx$$V,,Y       s6I;I'$I6 I$#I$' I32I36 JJ)typingrr:enumtorch._Cr to_dlpack torch.typesr_Device__all__IntEnumrr= _add_docstrboolrr*r+r,r\s ,)  4<<&Y!8" m-m- dNm- + m-  m-r+