# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os from paddle.device import get_available_custom_device # (TODO: GhostScreaming) It will be removed later. from paddle.fluid import core class DeviceType: CPU = 'cpu' GPU = 'gpu' XPU = 'xpu' NPU = 'npu' MLU = 'mlu' IPU = 'ipu' CUSTOM_DEVICE = 'custom_device' class Device: def __init__(self, dtype=None, memory="", labels=""): self._dtype = dtype self._memory = memory self._labels = labels def __str__(self): return ",".join(self._labels) @property def dtype(self): return self._dtype @property def count(self): return len(self._labels) or 1 @property def memory(self): return self._memory @property def labels(self): return self._labels @labels.setter def labels(self, lbs): if isinstance(lbs, str): self._labels = lbs.split(',') elif isinstance(lbs, list): self._labels = lbs else: self._labels = [] def get_selected_device_key(self): if self._dtype == DeviceType.CPU: return 'FLAGS_selected_cpus' if self._dtype == DeviceType.GPU: return 'FLAGS_selected_gpus' if self._dtype == DeviceType.NPU: return 'FLAGS_selected_npus' if self._dtype == DeviceType.XPU: return 'FLAGS_selected_xpus' if self._dtype == DeviceType.MLU: return 'FLAGS_selected_mlus' if self._dtype == DeviceType.IPU: return 'FLAGS_selected_ipus' if self._dtype == DeviceType.CUSTOM_DEVICE: return 'FLAGS_selected_{}s'.format(os.getenv('PADDLE_XCCL_BACKEND')) return 'FLAGS_selected_devices' def get_selected_devices(self, devices=''): ''' return the device label/id relative to the visible devices ''' if not devices: return [str(x) for x in range(0, len(self._labels))] else: devs = [x.strip() for x in devices.split(',')] return [str(self._labels.index(d)) for d in devs] def get_custom_device_envs(self): return { 'PADDLE_DISTRI_BACKEND': 'xccl', 'PADDLE_XCCL_BACKEND': os.getenv('PADDLE_XCCL_BACKEND'), } @classmethod def parse_device(self): dev = Device() visible_devices = None if 'PADDLE_XCCL_BACKEND' in os.environ: dev._dtype = DeviceType.CUSTOM_DEVICE visible_devices_str = '{}_VISIBLE_DEVICES'.format( os.getenv('PADDLE_XCCL_BACKEND').upper() ) if visible_devices_str in os.environ: visible_devices = os.getenv(visible_devices_str) elif 'CUDA_VISIBLE_DEVICES' in os.environ: dev._dtype = DeviceType.GPU visible_devices = os.getenv("CUDA_VISIBLE_DEVICES") elif 'XPU_VISIBLE_DEVICES' in os.environ: dev._dtype = DeviceType.XPU visible_devices = os.getenv("XPU_VISIBLE_DEVICES") elif 'ASCEND_VISIBLE_DEVICES' in os.environ: dev._dtype = DeviceType.NPU visible_devices = os.getenv("ASCEND_VISIBLE_DEVICES") elif 'MLU_VISIBLE_DEVICES' in os.environ: dev._dtype = DeviceType.MLU visible_devices = os.getenv("MLU_VISIBLE_DEVICES") if visible_devices is not None and visible_devices != 'all': dev._labels = visible_devices.split(',') else: return self.detect_device() return dev @classmethod def detect_device(self): def get_custom_devices_count(device_type): all_custom_devices = get_available_custom_device() all_custom_devices = [ device.split(':')[0] for device in all_custom_devices ] custom_devices_count = all_custom_devices.count(device_type) return custom_devices_count dev = Device() num = 0 visible_devices = None if 'PADDLE_XCCL_BACKEND' in os.environ: custom_device_type = os.getenv('PADDLE_XCCL_BACKEND') dev._dtype = DeviceType.CUSTOM_DEVICE num = get_custom_devices_count(custom_device_type) visible_devices_str = '{}_VISIBLE_DEVICES'.format( custom_device_type.upper() ) if visible_devices_str in os.environ: visible_devices = os.getenv(visible_devices_str) elif core.is_compiled_with_cuda(): dev._dtype = DeviceType.GPU num = core.get_cuda_device_count() visible_devices = os.getenv("CUDA_VISIBLE_DEVICES") elif core.is_compiled_with_xpu(): dev._dtype = DeviceType.XPU num = core.get_xpu_device_count() visible_devices = os.getenv("XPU_VISIBLE_DEVICES") elif core.is_compiled_with_npu(): dev._dtype = DeviceType.NPU num = core.get_npu_device_count() visible_devices = os.getenv("ASCEND_VISIBLE_DEVICES") elif core.is_compiled_with_mlu(): dev._dtype = DeviceType.MLU num = core.get_mlu_device_count() visible_devices = os.getenv("MLU_VISIBLE_DEVICES") elif core.is_compiled_with_ipu(): dev._dtype = DeviceType.IPU num = core.get_ipu_device_count() # For IPUs, 'labels' is a list which contains the available numbers of IPU devices. dev._labels = [str(x) for x in range(0, num + 1)] return dev if num == 0: dev._dtype = DeviceType.CPU elif visible_devices is None or visible_devices == "all": dev._labels = [str(x) for x in range(0, num)] else: dev._labels = visible_devices.split(',') return dev if __name__ == '__main__': d = Device.parse_device() print(d.get_selected_devices())