o Mea=@sddlZddlZddlmZddlmZddlmZddlmZddlm Z ddlm Z dd l m Z gd Z dad d Zd dZddZddZddZddZddZddZddZddZdd Zd!d"Zd#d$Zd%d&Zd'd(ZdS))N)core) framework) ParallelEnv)is_compiled_with_cinn)is_compiled_with_cuda)is_compiled_with_rocm)cuda)get_cudnn_version set_device get_deviceXPUPlaceIPUPlaceMLUPlaceis_compiled_with_xpuis_compiled_with_ipurrris_compiled_with_npuis_compiled_with_mluget_all_device_typeget_all_custom_device_typeget_available_deviceget_available_custom_devicecCtS)a Whether paddle was built with WITH_ASCEND_CL=ON to support Ascend NPU. Returns (bool): `True` if NPU is supported, otherwise `False`. Examples: .. code-block:: python import paddle support_npu = paddle.device.is_compiled_with_npu() )rrrrFD:\Projects\ConvertPro\env\Lib\site-packages\paddle/device/__init__.pyr3 rcCr)a Whether paddle was built with WITH_IPU=ON to support Graphcore IPU. Returns (bool): `True` if IPU is supported, otherwise `False`. Examples: .. code-block:: python import paddle support_ipu = paddle.is_compiled_with_ipu() )rrrrrrrBrrcCr)z Return a Graphcore IPU Place Examples: .. code-block:: python # required: ipu import paddle place = paddle.device.IPUPlace() )rrrrrrrQrrcCr)a Whether paddle was built with WITH_XPU=ON to support Baidu Kunlun Returns (bool): whether paddle was built with WITH_XPU=ON Examples: .. code-block:: python import paddle support_xpu = paddle.device.is_compiled_with_xpu() )rrrrrrr`rrcC t|S)a Return a Baidu Kunlun Place Parameters: dev_id(int): Baidu Kunlun device id Examples: .. code-block:: python # required: xpu import paddle place = paddle.device.XPUPlace(0) )rr dev_idrrrr o r cCr)a0 Whether paddle was built with WITH_MLU=ON to support Cambricon MLU Returns (bool): whether paddle was built with WITH_MLU=ON Examples: .. code-block:: python # required: mlu import paddle support_mlu = paddle.device.is_compiled_with_mlu() )rrrrrrrsrcCr)z Return a Cambricon MLU Place Parameters: dev_id(int): MLU device id Examples: .. code-block:: python # required: mlu import paddle place = paddle.device.MLUPlace(0) )rrrrrrrrrcCs8tsdStdurtt}|atdkrdS|StS)a This funciton return the version of cudnn. the retuen value is int which represents the cudnn version. For example, if it return 7600, it represents the version of cudnn is 7.6. Returns: int: A int value which represents the cudnn version. If cudnn version is not installed, it return None. Examples: .. code-block:: python import paddle cudnn_version = paddle.device.get_cudnn_version() Nr)rr_cudnn_versionint cudnn_version)r"rrrr s r c Cs:|}|dkrt}|S|dkr#tstdttj}|S|dkrEts/tdt dd d}t |d }t |}|S|d krgtsQtd t d d d}t |d }t|}|S|d krytsstdt}|S|dkrtstdt dd d}t |d }t|}|S|tvrt d|d d}t |d }t||}|Std|}td|} td|} td|} |s| s| s| s| dd} | d } | tvr| d}t |}t| |}ntddddgdtD|r5ts"td|| dd} | d}t |}t|}| rWtsDtd| | dd} | d}t |}t |}| rytsftd | | dd} | d}t |}t|}| rtstd!| | dd} | d}t |}t|}|S)"NcpugpuzLThe device should not be 'gpu', since PaddlePaddle is not compiled with CUDAxpuzKThe device should not be 'xpu', since PaddlePaddle is not compiled with XPUZFLAGS_selected_xpus0,rnpuzKThe device should not be 'npu', since PaddlePaddle is not compiled with NPUZFLAGS_selected_npusZipuzKThe device should not be 'ipu', since PaddlePaddle is not compiled with IPUmluzKThe device should not be 'mlu', since PaddlePaddle is not compiled with MLUZFLAGS_selected_mluszFLAGS_selected_{}szgpu:\d+zxpu:\d+znpu:\d+zmlu:\d+:rz3The device must be a string which is like 'cpu', {}z, css|] }d||VqdS)z '{}', '{}:x'N)format).0xrrr sz$_convert_to_place..)r$r%r(r)zIThe device should not be {}, since PaddlePaddle is not compiled with CUDAzHThe device should not be {}, since PaddlePaddle is not compiled with XPUzHThe device should not be {}, since PaddlePaddle is not compiled with NPUzHThe device should not be {}, since PaddlePaddle is not compiled with mlu)lowerrCPUPlacer ValueError CUDAPlacerrrosgetenvsplitr!r rNPUPlacerrrrrr+ CustomPlacerematchjoin)deviceZ lower_deviceplaceZ selected_xpus device_idZ selected_npusZ selected_mlusZselected_devicesZavaliable_gpu_deviceZavaliable_xpu_deviceZavaliable_npu_deviceZavaliable_mlu_deviceZdevice_info_list device_typerrr_convert_to_places\W  P  IC  <   7                  r?cCst|}t||S)a3 Paddle supports running calculations on various types of devices, including CPU, GPU, XPU, NPU, MLU and IPU. They are represented by string identifiers. This function can specify the global device which the OP will run. Parameters: device(str): This parameter determines the specific running device. It can be ``cpu``, ``gpu``, ``xpu``, ``npu``, ``mlu``, ``gpu:x``, ``xpu:x``, ``npu:x``, ``mlu:x`` and ``ipu``, where ``x`` is the index of the GPUs, XPUs, NPUs or MLUs. Examples: .. code-block:: python import paddle paddle.device.set_device("cpu") x1 = paddle.ones(name='x1', shape=[1, 2], dtype='int32') x2 = paddle.zeros(name='x2', shape=[1, 2], dtype='int32') data = paddle.stack([x1,x2], axis=1) )r?rZ_set_expected_place)r;r<rrrr &s r cCsd}t}t|tjrd}|St|tjr"|}dt|}|St|tjr4|}dt|}|St|tj rF|}dt|}|St|tj rYt }d |d}|St|tj rk|}dt|}|St|tjr|}|}|d t|}|Std |) a This funciton can get the current global device of the program is running. It's a string which is like 'cpu', 'gpu:x', 'xpu:x', 'mlu:x' and 'npu:x'. if the global device is not set, it will return a string which is 'gpu:x' when cuda is avaliable or it will return a string which is 'cpu' when cuda is not avaliable. Examples: .. code-block:: python import paddle device = paddle.device.get_device() r#zgpu:zxpu:znpu:z ipus:{{0-{}}}rzmlu:r*z&The device specification {} is invalid)rZ_current_expected_place isinstancerr0r2Z get_device_idstrr r6rZget_ipu_device_countr+rr7Zget_device_typer1)r;r<r=Z num_devicesr>rrrr As>           r cCr)a Get all available device types. Returns: A list of all available device types. Examples: .. code-block:: python import paddle paddle.device.get_all_device_type() # Case 1: paddlepaddle-cpu package installed, and no custom device registerd. # Output: ['cpu'] # Case 2: paddlepaddle-gpu package installed, and no custom device registerd. # Output: ['cpu', 'gpu'] # Case 3: paddlepaddle-cpu package installed, and custom deivce 'CustomCPU' is registerd. # Output: ['cpu', 'CustomCPU'] # Case 4: paddlepaddle-gpu package installed, and custom deivce 'CustomCPU' and 'CustomGPU' is registerd. # Output: ['cpu', 'gpu', 'CustomCPU', 'CustomGPU'] )rrrrrrrmrcCr)a Get all available custom device types. Returns: A list of all available custom device types. Examples: .. code-block:: python import paddle paddle.device.get_all_custom_device_type() # Case 1: paddlepaddle-gpu package installed, and no custom device registerd. # Output: None # Case 2: paddlepaddle-gpu package installed, and custom deivce 'CustomCPU' and 'CustomGPU' is registerd. # Output: ['CustomCPU', 'CustomGPU'] )rrrrrrrrcCr)a= Get all available devices. Returns: A list of all available devices. Examples: .. code-block:: python import paddle paddle.device.get_available_device() # Case 1: paddlepaddle-cpu package installed, and no custom device registerd. # Output: ['cpu'] # Case 2: paddlepaddle-gpu package installed, and no custom device registerd. # Output: ['cpu', 'gpu:0', 'gpu:1'] # Case 3: paddlepaddle-cpu package installed, and custom deivce 'CustomCPU' is registerd. # Output: ['cpu', 'CustomCPU'] # Case 4: paddlepaddle-gpu package installed, and custom deivce 'CustomCPU' and 'CustomGPU' is registerd. # Output: ['cpu', 'gpu:0', 'gpu:1', 'CustomCPU', 'CustomGPU:0', 'CustomGPU:1'] )rrrrrrrrCrcCr)a Get all available custom devices. Returns: A list of all available custom devices. Examples: .. code-block:: python import paddle paddle.device.get_available_custom_device() # Case 1: paddlepaddle-gpu package installed, and no custom device registerd. # Output: None # Case 2: paddlepaddle-gpu package installed, and custom deivce 'CustomCPU' and 'CustomGPU' is registerd. # Output: ['CustomCPU', 'CustomGPU:0', 'CustomGPU:1'] )rrrrrrrrDr)r8r3Z paddle.fluidrrZpaddle.fluid.dygraph.parallelrZpaddle.fluid.frameworkrrrr@r __all__r rrrrr rrr r?r r rrrrrrrrs4        b,