>>> ms.set_auto_parallel_context(pipeline_config={"pipeline_interleave": True, "pipeline_scheduler": "gpipe"}) >>> ms.get_auto_parallel_context("pipeline_config") Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/jenkins7/.local/lib/python3.7/site...
in__init__ self.broadcast_bucket_size) File"/mnt/lustre/lirundong/Program/conda_env/torch-1.2-cuda-9.0/lib/python3.6/site-packages/torch/nn/parallel/distributed.py", line 480,in_distributed_broadcast_coalesced dist._broadcast_coalesced(self.process_group, tensors, buffer_size) RuntimeError: ...
Tensor Overview DataType StructValEntry Tensorboard Overview LabelsEntry TensorboardBlob TensorboardBlobSequence TensorboardExperiment Overview LabelsEntry TensorboardRun Overview LabelsEntry TensorboardTensor TensorboardTimeSeries Overview Metadata ValueType ThresholdConfig TimeSeriesData TimeS...
TensorboardTensor TensorboardTimeSeries Overview Metadata ValueType ThresholdConfig TimeSeriesData TimeSeriesDataPoint TimestampSplit TokensInfo Tool TrainingConfig TrainingPipeline Overview LabelsEntry Trial Overview Parameter State WebAccessUrisEntry TrialContext TunedModel TuningDataStats Tuni...
(modellink) [root@localhostModelLink]# python convert_ckpt.py \ --model-type GPT \ --load-model-type hf \ --save-model-type mg \ --target-tensor-parallel-size 1 \ --target-pipeline-parallel-size 1 \ --load-dir ./model_from_hf/Qwen2-72B-Instruct \ ...
#ray.shutdown() #ray.init(num_gpus=torch.cuda.device_count()) self.llm = LLM(model="/s/hpc-datasets/models/llama-3/Meta-Llama-3.1-405B-Instruct-FP8", tensor_parallel_size=tensor_parallel_size,gpu_memory_utilization=0.95,max_model_len=32768, max_num_batched_tokens=32768) def __call...
join(cfg.respth, 'model_final.pth') net.load_state_dict(torch.load(save_pth), strict=False) net.cuda() net.eval() if not args.local_rank == -1: net = nn.parallel.DistributedDataParallel(net, device_ids = [args.local_rank, ], output_device = args.local_rank ) ## evaluator ...
Source File: data_parallel_dist.py From ps_pytorch with MIT License 5 votes def _reduction_thread_fn(queue, group_id, device_ids, reduction_streams, nccl_streams): def _process_batch(): dev_grad_batch, dev_events, job_event = queue.get() dev_coalesced = [] # Coalesce the tensors...
示例1: buildModel ▲点赞 7▼ voidbuildModel(){ TimeManager::getCurrent ()->setTimeStepSize (0.005); createMesh();// create static rigid bodystringfileName = dataPath +"/models/cube.obj"; IndexedFaceMesh mesh; VertexData vd; OBJLoader::loadObj(fileName, vd, mesh);stringfileNameTorus ...
SimulationModel::ConstraintGroupVector &groups = model.getConstraintGroups();while(iter < maxIter) {for(unsignedintgroup =0; group < groups.size(); group++) {#pragmaomp parallel default(shared){#pragmaomp for schedule(static)for(inti =0; i < (int)groups[group].size(); i++) ...