o p i@sddlmZddlZddlZddlmZmZmZmZddl Z ddl m Z ddl m Z ddlmZer>ddlmZdd l mZd d gZed d dZGdddeeZGdddejZddd Zddd ZdS)) annotationsN) TYPE_CHECKINGLiteralProtocolTypeVar) DenseTensor) check_type)in_dygraph_mode) CapsuleType)Tensor to_dlpack from_dlpack _T_contraT) contravariantc@s*eZdZdZddddd Zdd d Zd S) SupportDLPackz ref: https://github.com/numpy/numpy/blob/7e6e48ca7aacae9994d18a3dadbabd2b91c32151/numpy/__init__.pyi#L3068-L3077 https://github.com/numpy/numpy/blob/7e6e48ca7aacae9994d18a3dadbabd2b91c32151/numpy/__init__.pyi#L4730-L4731 .streamrNone | _T_contrareturnr cCdSN)selfrrrZ/home/app/PaddleOCR-VL/.venv_paddleocr/lib/python3.10/site-packages/paddle/utils/dlpack.py __dlpack__0zSupportDLPack.__dlpack__tuple[int, Literal[0]]cCrrr)rrrr__dlpack_device__2rzSupportDLPack.__dlpack_device__N)rrrr )rr)__name__ __module__ __qualname____doc__rrrrrrr)src@s4eZdZdZdZdZdZdZdZdZ dZ d Z d Z d S) DLDeviceType))r))))) ) ) )N) rr r!ZkDLCPUkDLCUDAZ kDLCUDAHostZ kDLOpenCLZ kDLVulkanZkDLMetalZkDLVPIZkDLROCMZ kDLExtDevZ kDLOneAPIrrrrr#5sr#xr rr cCsLtrt|tjstdt|d|St |dt d|S)a Encodes a tensor to DLPack. Args: x (Tensor): The input tensor, and the data type can be ``bool``, ``float16``, ``float32``, ``float64``, ``int8``, ``int16``, ``int32``, ``int64``, ``uint8``, ``complex64``, ``complex128``. Returns: dltensor, and the data type is PyCapsule. Examples: .. code-block:: python :name: code-paddle-to-paddle >>> import paddle >>> # x is a tensor with shape [2, 4] >>> x = paddle.to_tensor([[0.2, 0.3, 0.5, 0.9], ... [0.1, 0.2, 0.6, 0.7]]) >>> dlpack = paddle.utils.dlpack.to_dlpack(x) >>> print(dlpack) >>> # doctest: +SKIP('the address will change in every run') >>> #doctest: -SKIP >>> # dlpack capsule will be renamed to 'used_dltensor' after decoded >>> y = paddle.utils.dlpack.from_dlpack(dlpack) >>> print(dlpack) >>> # doctest: +SKIP('the address will change in every run') .. code-block:: python :name: code-paddle-to-torch >>> # doctest: +SKIP('torch will not be installed') >>> # type: ignore >>> # convert tensor from paddle to other framework using to_dlpack >>> import torch >>> x = paddle.randn([2, 4]).to(device="cpu") >>> y = torch.from_dlpack(paddle.utils.dlpack.to_dlpack(x)) >>> print(y.shape) torch.Size([2, 4]) >>> # doctest: -SKIP zAThe type of 'x' in to_dlpack must be paddle.Tensor, but received .r.r ) r isinstancepaddler TypeErrortypevalueZ get_tensorZ _to_dlpackr r)r.rrrr Bs/ dlpackSupportDLPack | CapsuleTypecCst|drT|}|dtjfvrOttjdtdtj j |d}Wdn1s0wY|dtjk}|rE|j dkrEdn|j }|j |d}n| }n|}tjj|}tritj||d}|S) a Decodes a DLPack to a tensor. The returned Paddle tensor will share the memory with the tensor from given dlpack. Args: dlpack (SupportDLPack | CapsuleType): A PyCapsule object with the dltensor, or that implements '__dlpack__' and '__dlpack_device__' methods. If `dlpack` is a tensor (or ndarray) object, it must support the `__dlpack__` protocol (i.e., have a `dlpack.__dlpack__` method). Otherwise `dlpack` may be a DLPack capsule, which is an opaque `PyCapsule` instance, typically produced by a `to_dlpack` function or method. Returns: out (Tensor): A tensor decoded from DLPack. The data type of returned tensor can be one of: ``int32``, ``int64``, ``float16``, ``float32`` and ``float64``. The device of returned tensor can be one of: ``CPU``, ``CUDAPlace``, ``CUDAPinnedPlace``. Examples: .. code-block:: python :name: code-paddle-from-paddle >>> import paddle >>> # From DLPack capsule >>> x = paddle.to_tensor([[0.2, 0.3, 0.5, 0.9], ... [0.1, 0.2, 0.6, 0.7]], place="cpu") >>> dlpack = paddle.utils.dlpack.to_dlpack(x) >>> y = paddle.utils.dlpack.from_dlpack(dlpack) >>> # dlpack capsule will be renamed to 'used_dltensor' after decoded >>> print(dlpack) >>> # doctest: +SKIP('the address will change in every run') >>> print(y) Tensor(shape=[2, 4], dtype=float32, place=Place(cpu), stop_gradient=True, [[0.20000000, 0.30000001, 0.50000000, 0.89999998], [0.10000000, 0.20000000, 0.60000002, 0.69999999]]) >>> # data of tensor x is shared with tensor y >>> y[0, 0] = 10.0 >>> print(x) Tensor(shape=[2, 4], dtype=float32, place=Place(gpu:0), stop_gradient=True, [[10. , 0.30000001, 0.50000000, 0.89999998], [0.10000000, 0.20000000, 0.60000002, 0.69999999]]) .. code-block:: python :name: code-paddle-from-numpy >>> # Directly from external tensor that implements '__dlpack__' and '__dlpack_device__' methods >>> import paddle >>> import numpy as np >>> x = np.array([[0.2, 0.3, 0.5, 0.9], ... [0.1, 0.2, 0.6, 0.7]]) >>> y = paddle.utils.dlpack.from_dlpack(x) >>> y[0, 0] = 10.0 >>> # data of tensor x is shared with tensor y >>> print(x) [[10. 0.3 0.5 0.9] [ 0.1 0.2 0.6 0.7]] rrignore)categoryr$Nr)Zplace)hasattrrr#r-warningscatch_warningsfilterwarnings UserWarningr1devicecudaZcurrent_streamZ cuda_streamrbasecorerr r Z_place)r5r>rZis_gpuZ stream_ptrZdlpack_outrrrr~s& A   )r.r rr )r5r6rr ) __future__renumr:typingrrrrr1Z base.corerZbase.data_feederr Zbase.frameworkr Ztyping_extensionsr r __all__rrIntEnumr#r rrrrrs&        <