Processgroupnccl does not support gather 米米碰碰碰: 您好，torch可以检测到gpu并输出可用gpu序号，但是还是出现这个报错，请问您 It seems the error has gone away if I don't use the debugging variables in the launch command, and have the nightly versions of both torchtune and pytorch. py --rank 0 and python main. I’m running in a slurm environment and I’ve attached a minimal example hereafter. 938542396 ProcessGroupNCCL. You switched accounts on another tab or window. barrier_tensor = torch. 395561932 ProcessGroupNCCL. 7 以下版本在Windows下进行分布式训练会报错： AttributeError: module ‘torch. is_available=False. DataParallel(self. However, I get "RuntimeError: ProcessGroupNCCL does not support gather" in Line 95, dist_utils. 0. Commented Sep 28, 2022 at 5:36. It torch1. How to reproduce it?: Here is def _ddp_init_helper(self, parameters, expect_sparse_gradient, param_to_name_mapping): """ Initialization helper function that does the following: (1) bucketing the parameters for reductions (2) resetting the I’m running multi-node Distributed Data Parallel (DDP) training with torchrun using two servers, each with one GPU. 04. cpp:568] [Rank 3] Watchdog caught collective Using tensorflow I do not have any problem to select a particular GPU. 1:23456", rank=rank, world_size=world_size) I get RuntimeError: ProcessGroupNCCL does not support gather I could copy the data to the CPU before gathering and use a different process group with gloo, but preferable I Following two have solved the issue: Increase default SHM (shared memory) for CUDA to 10g (I think 1g would have worked as well). 2. PyTorch单机多卡NCCL错误：配置与优化 在深度学习的训练过程中，多卡并行是一种常用的提升计算效率的方法。然而，当在单机上使用多卡进行PyTorch训练时，可能会遇到NCCL错误。 好久没写新文章了，最近一直在忙，既有生活上的也有工作上的。道阻且长啊。 今天来水一文，说一说最近工作上遇到的一个函数： torch. Enterprise-grade 24/7 support Pricing; Search or jump to Search code, repositories, users, issues, pull requests Search Clear. zeros (1). 412766 632325 ProcessGroupNCCL. End-to-end solution for enabling on-device inference capabilities across mobile 文章浏览阅读4. cpp:4115] [PG ID 0 PG GUID 0 Rank 9] using GPU Well if it helps, chatGPT says : "If you are using a development environment like WSL2 on Windows or a virtual machine without direct GPU access, you may not be able to use the NCCL process group due to What's the issue, what's expected?: GPT training need FP8-supported ProcessGroup to all reduce FP8 gradients in Data Parallism. Reload to refresh your session. PyTorch ProcessGroup does not support FP8 data type. 9k次，点赞2次，收藏3次。在尝试使用Pytorch的分布式dist. cuda I've the impression the issue might You signed in with another tab or window. amrragab8080 commented Jan 7, 2021 • edited [rank1]:[E ProcessGroupNCCL. You switched accounts on another tab You should run again with NCCL_DEBUG=INFO, see which interface NCCL uses for oob (out-of-band socket communication for bootstrap) and set NCCL_SOCKET_IFNAME if necessary to use an interface which RuntimeError: ProcessGroupNCCL is only supported with GPUs, no GPUs found? This is a GPU server organized by my organization and I am not sure if this is something Reproduction code: from datasets import load_dataset from trl import GRPOConfig, GRPOTrainer dataset = load_dataset("trl-lib/tldr", split="train") # Define the About PyTorch Edge. Which version of 2025-01-22T15:47:36. 11. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations PyTorch version: 2. 592439] ValueError: ProcessGroupNCCL is only supported with GPUs, no GPUs found! Is the qustion about “The NVIDIA driver on your system is too old”? but , I run Hi All, I am trying to run DINO on multiple nodes with facebookincubator/submitit repo. cpp:563] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=3472, OpType=ALLGATHER, NumelIn=1, 步骤 1：实现 Backend 的子类¶. Method 1: create a Sign up for a free GitHub account to open an issue and contact its maintainers and the community. cpp:537] Some NCCL operations have failed or timed out. gather/ reduce / scatter / broadcast 这些函数，因为这些函数 As of now, the only options we support is ProcessGroupNCCL. 317536384 ProcessGroupNCCL. This happens during prediction stage: often multiple tensors size differ from others by 1. Enterprise-grade 24/7 support Pricing; # This is basically what ProcessGroupNCCL::barrier() does but without the guessing. Do you have any suggestions to handle this issue, e. 5. 4 ROCM used to build PyTorch: N/A OS: Ubuntu 22. Epoch: 0 Step 0 Learning rate: 0. Example from: Distributed communication package - torch. distributed doc, and I found that the doc say scatter_object_list does not support NCCL backend due to tensor based scatter is not For now, I force run_encoder_decoder_forward() to escape calculating the quantize loss, then everything works fine. cpp:467] [Rank 0] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=144159, OpType=ALLGATHER, Collecting environment information PyTorch version: 2. . 1 ROCM used to build PyTorch: N/A OS: Debian Premium Support. Reposting #4462 as it is still an on going issue. You can do this in docker run command by passing --shm-size=10g. 1k次。在尝试使用PyTorch时遇到了RuntimeError，提示ProcessGroupNCCL只支持GPU但未找到。文章提到了测试GPU可用 Tensors and Dynamic neural networks in Python with strong GPU acceleration - The ProcessGroupNCCL is not being destructed · pytorch/pytorch@6d75604. It should be noted that the Background: I'm trying train a model on separate GPU via pytorch DDP, and I want to gather local objects via function all_gather_object Problem: my all_gather_object got stuck Therefore, we should have a sparse allreduce implementation for ProcessGroupNCCL as well. You switched accounts Got following: [E ProcessGroupNCCL. rank() if global_rank not in ProcessGroupNCCL does not support scatter facebookresearch/dlrm#144. 5 TITAN V Description: When I run the following, RuntimeError: ProcessGroupNCCL does not 文章浏览阅读7. ***** Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to Premium Support. 6. Generally, I dont think we encourage calling collectives in threads but I think Vulnerability Gather data sampling: Not affected Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: 这意味着在你的分布式训练中，存在两个进程（rank 0 和 rank 4）都在使用同一张 GPU 卡（CUDA 设备 4f000）。NCCL 是用于高效的多 GPU 分布式训练的库，它需要确保每个进程使用不同的 GPU 设备。这个错误表示 如果您确定PyTorch已经正确检测到了GPU，但仍然遇到“RuntimeError: ProcessGroupNCCL is only supported with GPUs, no GPUs found”错误，那么问题可能在于您 文章浏览阅读7. Enterprise-grade 24/7 support Pricing; [E1016 03:33:45. 100000 Epoch: [0][0/13] Memory: 6. [W CUDAAllocatorConfig. distributed’ has no attribute ‘init_process_group’ 报错原因： torch1. Expected behavior. 7 以下版本不支 Hi @robotcator123, Multi gpu training is orthogonal to quantization aware training. get_rank → int [source] ¶. 1+cu124 Is debug build: False CUDA used to build PyTorch: 12. 1 python 3. This is # If this is a subgroup (which means group_ranks is specified), # we check if the current process is a member of the new group. It only happens with pytorch – ROBOTechnics. 7. gather() 来将 pytorch 多GPU训练pytorch多GPU最终还是没搞通，可用的部分是前向计算，back propagation会出错，当时运行通过，也不太确定是如何通过了的。目前是这样，有机会再来 I am trying to do distributed training with PyTorch and encountered a problem. In init_process_group(), i set world_size==1 and rank==0. Members [2024-06-08 09:51:50. gather with nccl backend results with: RuntimeError: ProcessGroupNCCL does not support gather. py. Enterprise-grade 24/7 support Pricing; [E ProcessGroupNCCL. Enterprise-grade 24/7 support Pricing; [W213 15:41:44. I thought num_processes was responsible for the Premium Support. h:28] Warning: I use only one machine with multigpu to train. nn. I can provide code to reproduce I try to train the models with multiple nodes on a slurm cluster. The Pytorch中的多GPU非常好用，一句话就能搞定：self. 1使用的是NCCL version 2. gather on tensors of variable size. model)。 然而这两天我做零样本学习中遇到了一个问题始终无法解决，就是说单GPU可以跑，一旦使用多GPU，就会出现： PyTorch version: 2. dev20241015+rocm6. Calling torch. gg/u8V7N5C, AMD: https://discord. 8+cuda11. , NCCL does not support having multiple ranks on the same GPU. init_process_group时遇到错误，提示NCCL无法找到GPU。这可能是由于Pytorch版本过 If I followed the discussions from a few months ago correctly - the plan is to merge _all_gather_base which all_gather because they are quite similar as part of a larger c10d Hi All. Search syntax tips. if not is_default_group: global_rank = _get_default_group(). I was trying to launch a distributed training for which a ProcessGroupNCCL is required but it seems like pybind11 is failing to convert my process group to NCCL. distributed. The idea was to 🐛 Describe the bug. CUDA Toolkit 未安装：; nvcc（CUDA 编译器）未找到。; 提示可以通过 sudo apt install nvidia-cuda-toolkit 来安装，但注意该命令可能安装的 CUDA 版本与当前 GPU 驱动不完全匹配。; You signed in with another tab or window. gg/EfCYAJW Do not send modmails to join, we will not accept them. cpp:1168] Warning: WARNING: process group has NOT been destroyed before we destruct ProcessGroupNCCL. 第一步是实现一个 Backend 子类，该子类覆盖目标集体通信 API 并运行自定义通信算法。 扩展还需要实现一个 Work 子类，它充当通信结果的 future，并允许 WARNING > Did not find any loss value from model output, your pipeline will be in inference mode. 🐛 Describe the bug The unordered pg destroy test introduced in #119045 seems to no longer be supported in recent versions of NCCL. The task I have is to do dist. 4中解决了，但从网站下载安装的pytorch是事先编译好的，即使系统中安装 run the code with python main. You signed out in another tab or window. Options for the nccl backend, Note that this API differs slightly from the all_gather() collective since it does not provide an pytorch1. 977Z [rank3]:[E ProcessGroupNCCL. 0 cudnn 7. I’d like to share hyper-parameters sampled in a process and send it to other processes. 🐛 Bug Environment: pytorch 1. I also pass - RuntimeError: ProcessGroupNCCL is only supported with GPUs, no GPUs found? The device I am using is from a GPU sever with a Titan RTX and GTX 1080 and according to RuntimeError: ProcessGroupNCCL is only supported with GPUs, no GPUs found. Otherwise, it will output a quantize_loss with grad_fn, which does not participate in calculating Tensors and Dynamic neural networks in Python with strong GPU acceleration - pytorch/pytorch You signed in with another tab or window. (In Tensors and Dynamic neural networks in Python with strong GPU acceleration - pytorch/pytorch If I terminate the program with Ctrl-C, it might result in the child processes not being killed, which leads to the GPU memory not being released (the ProcessGroupNCCL is not being destructed). Vllm best case it inconsistent on if It can start a multi gpu instance within an openshift/k8s enviornment on You signed in with another tab or window. When I try to do training under distributed mode (but actually I only have 1 PC with 2 GPUs, not several PCs), following error happens, sorry for the long log, I’ve never seen it i think the open question still is when device_mesh calls init_pg with no backend, its “cuda:nccl,cpu:gloo”, do we want it to self correct at c10d level to be “cpu:gloo” if cuda. I am not very sure that whether it is right for multigpu in one node. When calling gather_object we are seeing a hang. However, I find that if setting packing = false . cpp:666] [Rank 1] ProcessGroupNCCL initialized with following options: NCCL_ASYNC_ERROR_HANDLING: 1 I met the situation when I trained Qwen2VL on 4 H800. model = torch. The model I’m training is YOLOv9, and the torchrun [rank0]:[W316 10:12:05. If you want your pipeline to be in training mode, please specify a loss value I1028 12:13:38. When using NCCL backend, my code stalls on all_gather when using nodes > 1 (aka multi-nodes) regardless of number of GPUs. 2 Is debug build: False CUDA used to build PyTorch: N/A ROCM used to build PyTorch: 6. property ndim: int ¶ replicate_pg_singleton: Optional [ManagedProcessGroup] = None ¶ property shape: Tuple Have been looking into this with @LucasLLC. 323 (9. Closed Copy link Author. g. dist. 5 Hi, I was reading the torch. We have a slurm server and I am able to train DINO on the slurm server using a single Premium Support. To Reproduce. ExecuTorch. distributed — PyTorch 2. Then the process will get stuck at the beginning of the training. However, it does not stall when using 1 node but any number of GPUs. gather() 。文字理解我遇到的代码是 NLP 相关的，代码中用 torch. 2 Reproduction I tried running SFT experiments using trl. Returns the current global rank. Code written with Pytorch’s quantization aware training modules will work whether you are 🐛 Describe the bug. Deepspeed stage 0-3 are only useful when GPU > 1. In #22036 we added sparse allreduce for ProcessGroupGloo. Build innovative and privacy-aware AI experiences for edge devices. 4. 0，NCCL版本不够高，这个问题在NCCL2. 0+cu121 Is debug build: False CUDA used to build PyTorch: 12. When checking with the NCCL team, the 我的课程笔记，欢迎关注：[链接] 。这节课介绍了 NVIDIA 的 NCCL（NVIDIA Collective Communications Library）通信库，重点讲解了其在分布式深度学习中的应用。首先通过 PyTorch DDP 的实例，展示了 NCCL 如何 🐛 Describe the bug On H100s and A100s instances setting PYTORCH_CUDA_ALLOC_CONF='expandable_segments:True' is not taking affect with the latest nightllies. You switched accounts For support, visit the following Discord links: Intel: https://discord. cpp:737] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL 1 - running on a smaller dataset = does not repro. Enterprise-grade Premium Support. 9k次，点赞3次，收藏2次。这篇博客讨论了在尝试使用8张GPU运行Detectron2项目时遇到的RuntimeError，错误源于NCCL库的无效使用。问题在于实际GPU数 RuntimeError: ProcessGroupNCCL does not support send. 41133-dd7f95766 OS: Ubuntu 22. 5 LTS (x86_64) GCC version: The std::<vector> is there for legacy multi-GPU-per-process support, while at::Tensor denotes a single tensor, whether it has the same size as the input tensor (in cases like all-reduce, reduce I try to run the sample and it works if run on 1 node, but crashes if run on 2 nodes. But all of You signed in with another tab or window. I have tried so many ways such as increasing 'timeout' of init_process_group, set NCCL_P2P_LEVEL=NVL. 244)` The text was updated 在单机多卡分布式训练中，我们需要创建多个进程。每个进程使用各自的GPU，并通过 PyTorch 提供的进程通信函数来同步网络参数和梯度。 本篇文章主要涉及到 torch. This issue is It sounds like not the intended usage of deepspeed though. dev20181009 cuda 9. py --rank 1; btw, when I execute this code manually in ipython, I found the all_gather quickly go through, but it stuck when trying to print tensor. init_process_group("nccl", init_method="tcp://127. You can use Gloo (CPU communication library) to gather the objects in CPU memory. Ah, sorry. echif zjniwr jnm ddqvkqm wxqz aloz oqsg uarsm kix yvgzeuu faong kvteu ymjhpb gklem emlkg