Pytorch lightning gets stuck. Jun 27, 2018 · Hi, I’m using pytorch 0.

Pytorch lightning gets stuck Try to change it: is fine and this was really my fault 😃 Before I came here I randomly searched the internet for things like “slurm pytorch lightning ddp multi node” etc. pytorch. multiprocessing as mp nodes, gpus = 1, 4 world_size = nodes * gpus # set environment variables for distributed training Oct 24, 2021 · 🐛 Bug I'm trying to utilize all the computational resources to speed up. I did not change anything else. While executing bash . I would play around with some hyperparameters (learning rate) and the model architecture as the next step and force the model to learn this tiny data perfectly before digging any further. Internally it doesn’t stack up the batches and do a forward pass rather it accumulates the gradients for K batches and then do an optimizer. There is a weird behavior that in some iterations, the validation gets stuck when calling the compute() method. Closed Vichoko closed this as completed Nov 20, Nov 20, 2020 · I have a model, that uses gradient checkpointing and ddp. Using the DeepSpeed strategy, we were able to train model sizes of 10 Billion parameters and above, with a lot of useful information in this benchmark and the DeepSpeed docs. In each of of those trials we're training a pytorch model using lightning's Trainer. 1, which noone else seemed to have problems with. On my machine, using 0. Feb 12, 2021 · Hi! I am now transferring from "old" PyTorch to pytorch-lightning, but when I did some trivial training integrating existing models, I found trainer. Dec 21, 2024 · By default, Lightning will select the nccl backend over gloo when running on GPUs. For instance, slurm may provide 1 node with 6 gpus, and 2 other nodes with 1 gpu each, for a total of 8 nodes. The training speed is fast, approximately 30 minutes per epoch, but it becomes very slow during validation. hasattr(sys, "ps1") returns True if placed within the script and False if run in the interactive terminal after the script finishes. Is there ignore Dec 21, 2024 · Let’s see how these can be performed with Lightning. (ddp) but the same training procedure gets stuck (timeout because the initialization takes too long) when using a larger dataset. set_f Jun 7, 2021 · Training gets stuck on Epoch 0, 0% for both 1 and 8 cores. You can see the situation in the image below. run_local_tests. seed_everything(7, workers=True) torch. You could try to increase the number of workers, store your data on an Nov 12, 2021 · 🐛 Bug. Mar 28, 2024 · I created a pytorch implementation but it gets stuck at 20% wors off than the tf model. functional as F import time import torch. The train code is as follows: def train_batch( model, optimizer, baseline, epoch, batch_id, step, batch, tb_logger, opts ): x, bl_val = baseline. org . Notifications You must be signed in to change notification settings; Fork 413; Star 2. Is there anyone knowing Sep 14, 2020 · Hi, I am new to pytorch lightning. This is the last log before stuck, as it seems, its end of an epoch, so I Mar 3, 2020 · Data Loader Gets stuck when run on terminal, but runs when run through Pycharm. deepspeed==0. It also works fine if I turn off checkpointing. It does not happen 100% of the Dec 28, 2023 · Module gets optimized in a vanilla loop, but not with a Trainer #19216. I print the pstack of the process for one gpu, it seems it’s waiting in the synchronize function of nccl, so I guess some information Feb 22, 2022 · Hello, my Problem is the following: If I use the normal data loader for getting the training data loaded into the trainer. Lower precision, such as the 16-bit floating-point, enables the training and deployment of large neural networks since they require less memory, enhance data transfer operations since they required less memory bandwidth and run match operations much faster on GPUs that support Tensor Core. I am training the BERT from scratch with my custom dataset Feb 12, 2021 · I am now transferring from "old" PyTorch to pytorch-lightning, but when I did some trivial training integrating existing models, I found trainer. Open riyaj8888 opened this issue Mar 10, 2024 · 0 comments Open Jun 30, 2021 · Hello. Nothing special, just a Resnet18 for image and an Embedding + GRU network for text. I saw that others had that problem with certain Pytorch / Pytorch Lightning versions, however i’m using pytorch-lightning==1. the problem is that when I train it on 3D images, it dose not change too much plus that it is unstable in the sense that sometimes it decreases and sometimes it increases. I think I should clarify my problem, sorry about it. Code; Issues 841; Pull requests 60; Discussions; Actions; Projects 0; And the process gets Feb 6, 2022 · cf. 1 lightning-utilities==0. 0). 1 Like. For example, the first batch only takes 10s and the Jun 24, 2020 · You signed in with another tab or window. Could someone plea Jan 12, 2022 · When I use num_workers =0 for train_dataloader, val_dataloader, test_dataloader, the training finishes one epoch %100 quickly (although I get loss = NaN and I have not figure out what the issue is) with some warning that I should use larger num_workers and it suggests me to use num_workers = 16. In case it’s really slow check if you might be running out of space and if the system is swapping memory. 10问题解除。在pip安装过程中会卸载掉我的torch，指定版本也没用，解决方式是等安装pytorch-lightning结束后再把torch版本换回来。 I experience exactly same issues on fresh CUDA 11 and Pytorch 1. Apr 24, 2022 · Hi @akihironitta! Thanks for your response, but I already tried that solution. And I cannot interrupt the kernel but have to restart it. The code can run normally on a single GPU. but on first "on_train_step()" output is totally different, very Nov 25, 2024 · Hello everyone, after expanding our training data scale, we noticed a significant increase in the time per iteration. Please reproduce using the BoringModel To Reproduce. The code is working properly with dp and also with ddp using a single GPU. I made sure that the dataset is balanced, and that the total batch size is equal to number of GPUs. However, if you have some heavy preprocessing in your Dataset or the data loading is IO bound, you might notice small freezes as the workers can’t keep up processing the data fast enough. The model works Oct 26, 2018 · The DataLoader uses multiprocessing to load the batches asynchronously while the training takes place. 0 documentation. By default, Lightning will select the appropriate process Nov 19, 2023 · Bug description. However with multiple GPUs loss initially looks innocent, but then suddenly becomes NaN: checkpointing no checkpointing gpus = 1 works works gpus = 4 fails works The only part of the model that uses checkpointing Oct 3, 2024 · 🐛 Describe the bug Hi! I am starting to learn and use PyTorch. By default, Lightning will select the nccl backend over gloo when running on GPUs. But when I tried to run it on the server that has 2 GPUs, it hang on the loss. fit() routine, everything works fine. Code runs fine on 1 GPU. When I change the training strategy to dp it gets stuck after 1 epoch and epoch 2 does not begin. Same code different result. Detecting unused parameters is on. Not error reported. (validation step after each epoch) However, when I create a custom batch sampler (pulling even amount of events from each class), inside the the trainer loop, only the training_step gets executed (behaviour here seems Aug 22, 2023 · Maybe you can use a break in your training loop to early skip the first epoch and verify whether the second epoch can be executed correctly. py --gpus 4 --distributed_backend ddp for multiple-GPU running, while I use python main. nn. e with num_workers=4 the jobs get stuck in a couple of hours to 5-6 hours, while, num_workers=8 leads to the jobs getting stuck in less than 1-2 hours. it work’s great, except that at the beginning of every training epoch, or when I switch from train to test, the GPU gets idle for some time and Jul 27, 2020 · Hi, I am using contrastive loss for a set of 3d medical images. Open JosePeeterson opened this LearningRateMonitor import pytorch_lightning as pl import torch from pytorch_forecasting. Since my validation loader includes a time-consuming process, I want to completely skip it. I wrote a script for this task that is generating all combinations of hyperparameters, then forks one thread for each GPU (I have 4 GPUs in the machine, so I use 4 threads) and then each thread trains a model. 0, The Trainer fails/gets stuck (we're not sure) and ray tune's trials never finish. There are unused parameters (and Mar 13, 2021 · Hey @andrewssobral,. py in the same way and it worked fine. Specifically, the launcher gets stuck right after loading fused_adam extensions: deepspeed --num_gpus=2 Jan 18, 2022 · I am trying to move all validation outputs to one process to calculate my metric. Maybe problem is newer driver that breaks NCCL? Jun 30, 2017 · Hi there, I have a pre-trained model, and I added an actor-critic method into the model and trained only on the rl-related parameter (I fixed the parameters from pre-trained model). step to make sure the Dec 21, 2024 · Mixed Precision (16-bit) Training¶. 2k. Module in PyTorch creates all parameters on CPU in float32 precision by default. Mar 20, 2022 · Starting train. Using the nsys profiler, we found that after loading a large dataset into memory for training, the main training thread would randomly get stuck. 3x in the training for model1, after the training of model1 completes (all the ranks reached the Mar 31, 2022 · I am attempting to use DistributedDataParallel for single-node, multi-GPU training in a SageMaker Studio multi-GPU instance environment, within a Docker container. but I was confronted with a different traceback - pytorch_lightning. The pytorch was builded from source in branch v1. When I switched back to 1. Read more comments on GitHub > Mar 10, 2024 · Lightning-AI / pytorch-lightning Public. Best, Florian. 4k; Star 28. tsa. Module): def __init__(self, path_state_dim Jun 26, 2019 · I tried to inference using multi thread, but gpu stuck with GPU-Util 100%. All GPUs are now working Lightning-AI / pytorch-lightning Public. DataParallel to train on multi-GPUs. The GPU usage is stuck at 100 Nov 10, 2021 · I am using DDP in a single machine with 2 GPUs. What version are you seeing the problem on? master How to reproduce the bug Just used the following calls to trainer and fit. By "stuck" I mean I waited for 5 minutes, but nothing seems to be running, since I checked using htop and nvidia-smi, CPUs and GPUs are idle. Feb 10, 2022 · Lightning-AI / pytorch-lightning Public. Very strange, as my early stopping is for 3 epochs. However, when the two programs are trained and run in the same way again, they still fail. Jul 22, 2022 · 🐛 Bug Currently, Trainer requires num_nodes and devices, but this may be different across nodes. The same code that produced the above plots gives the following, having imports Mar 17, 2021 · 🐛 Bug My training / validation step gets hung when using ddp on 4-GPU AWS instance. 10. 4, this strange behavior does not occur. Lightning-AI / torchmetrics Public. However, to answer this question in detail, we would need an extra tutorial because it is not easy to answer. Because I use some different models and they both get stuck at some iteration step. 8 KB. In the terminal, if I put num_workers to 0 then it works. Sep 21, 2021 · Hi, everyone When I train my model with DDP, I observe that my training process got stuck every few seconds. Feb 22, 2022 · 🐛 Describe the bug I tried to run a DDP code on A40 GPUS and get stuck at the first iteration of the training model. I noticed some wired things: The Feb 7, 2021 · 🐛 Bug I recently updated to pytorch_lightning 1. 4. Model supposed Oct 10, 2020 · I tried to load (my trained) model from checkpoint for a fine-tune training. Even when removing the num_nodes parameter, the issue continues. I saw that others had that problem Feb 14, 2022 · Training is stuck when using ddp, gpus=[0, 1], and num_sanity_val_steps=2. Aug 3, 2022 · Hey everyone, I am having trouble running deepspeed on multiple gpus, whereas single gpu works just fine. ptrblck July 17, 2023, 5:09am 2. A May 5, 2022 · I’m training a model on image and text input pairs from Flickr30k. Expected behavior. The issue seems to originate from the fact that both nodes act as the first node Aug 2, 2022 · I’m facing an issue where training a lightning module with DDP on >4 GPUs gets stuck at end of first training epoch (I made sure there is no validation epoch). py --gpus 1 for single GPU running. batch_size = 2) # each DDP worker gets different number of batches val_data = DataLoader (RandomDataset (32, 64), The training process will get stuck after training for one epoch IntelLabs/academic-budget Feb 10, 2022 · You signed in with another tab or window. Accumulated gradients run K small batches of size N before doing a backward pass. GPU available: True, used: True TPU available: Jul 30, 2022 · I’m facing an issue where training a lightning module with DDP on >4 GPUs gets stuck at end of first training epoch (I made sure there is no validation epoch). Import torch is taking straight up forever. 4 on windows 10 and until now I always used num_workers=0 in my dataloader. The logic used here is defined under test_step(). 8" confirmation on initializing LightningModule in code cell. Sep 13, 2023 · Accumulate Gradients¶. Code; Issues 846; Pull requests 62; Discussions; Hey Mine gets stuck at the start Start Apr 30, 2023 · I'm using the latest version of pytorch lightning and deepspeed. utilities. Open Both train_loss and val_loss are stuck at their original values, being also agnostic to learning rate changes, Replacing all lightning. 0 installation. I tried the Boring Model, and I can reproduce the issue. My entry code is as follows: import os from PIL import ImageFile import torch. 221_cudnn8. 0 torch==1. This can be done before/after training and is completely agnostic to fit() call. loggers import Aug 30, 2020 · more specifically on_fit_start() gets called with 2 modules, still locating the source of this extra arg/module. 3 pyhd8ed1ab_0 conda-forge torchvision 0. DeadlockException and WorkNCCL(OpType=AllReduce, Timeout(ms)=1800000). Jun 19, 2023 · When I start training, the output gets stuck on “initializing ddp: GLOBAL_RANK” and the terminal freezes (Ctrl + C won’t work anymore). I’m using DDP with torch. All GPUs are reported to have 100% compute and memory utilization, but only 50/250 W power consumption. 6, I have: CUDA_VISIBLE_DEVICES: [8,9] and it works. Dec 2, 2021 · Hi, I'm new to PyTorch Lightning, used it for the first time and kind of liked it. 🐛 Bug tldr: Training freezes in a multi-gpu setting without throwing any errors or warnings. pl. log("valid_loss", loss, Aug 11, 2023 · 🔥版本匹配不再迷茫！🔍本文为你揭秘PyTorch、Python与pytorch_lightning的版本对应关系，让你轻松找到最佳匹配组合！📋我们为你整理了一份详尽的对应关系表，一目了然，轻松选择。🔧如何选择合适的版本？我们为你提供实用建议，助你避开版本匹配陷阱。 Mar 6, 2020 · This is using PyTorch I have been trying to implement UNet model on my images, however, my model accuracy is always exact 0. 8k. 5 and pytorch=1. To Reproduce. forward(batch) y_pred = outputs. The device information is shown in the following figure when it is stuck. A minute ago I stumbled upon this paragraph in the pl docs:. I have checked for weeks but cant figure out why. My system has 3x A100 GPUs. No errors, no warnings. But the temperature of GPU isn’t very high. However, if I change it to 1 gpu or 4 gpu, i Nov 9, 2019 · Lightning-AI / pytorch-lightning Public. The training process will get stuck at some constant steps. cuda. Closed Copy link Jul 9, 2019 · The same problem is reported in #20611 Environment PyTorch version: 1. Aug 23, 2021 · Hi. Run on an on-prem cluster (advanced) — PyTorch Lightning 1. The problem is that trainer. If I run the script through the terminal, the data loader does not work but the cpu works in full load. exceptions. May 28, 2024 · 使用torch1. But when it comes to multi-nodes, I found my code always Dec 2, 2020 · I trained a 3D unet model by Pytorch 1. The CPU usage of 4 main progress is 100%; I think it is not a code bug. 2+cu113, pytorch-lightning==1. import pytorch_lightning as pl import torch from pytorch_lightning. 3. My code were running perfectly before. I am building a model to predict a continuous variable from an input signal of a mixture of encoded categorical and continuous variables. @soumickmj Glad you found this out! Yes, this DDP Training Stuck while GPU utilization is 100%. I am using some linear layers with LeakyReLUs and dropouts in between. test() method. However, if I use num_workers > 0 it gets stuck at the validation sanity Oct 23, 2022 · Lightning-AI / pytorch-lightning Public. It just gets stuck there. sh the test hangs frequently (but not always) if parallel data loading is enabled in tests/base/model_utilities. Jun 27, 2018 · Hi, I’m using pytorch 0. It ca @haofanwang @superzrx. This means the new process will copy the memory of the parent process, including the state of the internal queues which may be locked at this moment. step(optimizer) in Mar 13, 2021 · Training gets stuck at 0% at the very first epoch whether using fast_dev_run or not. The domain of increasing and decreasing Dec 21, 2024 · PyTorch Lightning is a framework that simplifies your code needed to train, evaluate, and test a model in PyTorch. Can someone explain what is validation sanity check ? Thanks in advance! asvskartheek September 14, 2020, 1:46pm 2. implementation help. If an manual keyboard interrupt (CTRL-c) is done the test continues with a "PASSED" message. I have also checked for class imbalance. export NCCL_IB_DISABLE=1. 3: 3762: November 22, 2022 Ddp2 in multi node and multi gpu failing on pytorch lightning. I trained them on 1, 4, 5, 8 gpu environment using DDP. The code execution seems to be stuck at self. in the project I’m currently working on data loading is pretty heavy so I tried setting num_workers>1 (say 4). callbacks import EarlyStopping from pytorch_lightning. May 5, 2022 · I’m training the model with Pytorch Lightning running on two GPUs with a DDP strategy, 16-bit precision, 512 batch size, and 8 workers in total. 0 Is debug build: No CUD 🐛 Bug The training always freezes after some epochs. py by setting num_workers to a value larger than 0. fit() with accelerator set to ddp takes extremely long time to do something before it can get CPUs and GPUs working. I’m training the model with Pytorch Lightning running on two GPUs with a Dec 21, 2024 · The most likely reasons and how to fix it: You forgot to run the python train. List import seaborn as sn import pandas as pd import numpy as np import matplotlib. Jan 23, 2021 · Questions and Help What is your question? I'm trying to run the LitAutoEncoder on TPUs, but the code runs for 1 epoch and gets stuck there. It doesn’t proceed further. My model checkpoint is a very basic set up Jul 1, 2022 · Lightning-AI / pytorch-lightning Public. Ray Trainer prepare_model gets stuck. But after I update Pytorch to V1. 9. Read PyTorch Lightning's Nov 22, 2022 · I’m training a model using DDP on 4 GPUs and 32 vcpus. Mar 11, 2023 · Hi! I ran my code on a single GPU and it worked well. Here is my DataLoader for reference. . IIRC num_workers=1 means there will be a new process created by DataLoader and the default mode for multiprocessing is “fork”. functional as F import torch. Jul 12, 2019 · 🐛 Bug I was trying to evaluate the performance of the system with static data but different models, batch sizes and AMP optimization levels. As a matter of fact, setting gpus=[8, 9]:. GPU usage is constantly 100%, the data loader also stops working. Notifications You must be signed in to change notification settings; Fork 3. What makes more strange is that not every time this will happen. This doesn’t occur with 2 GPUs. We are currently in this transition phase where we are updating the code in our repositories, updating examples and, as you mentioned, the docs also need updates for all imports. Dec 21, 2024 · Fabric and the underlying strategy will decide in which format your checkpoint gets saved. I tried torch. However, I am facing this one problem, Implemented a classification task for which I trained the model with Huggingface pretrained model as base and classification head on top. Both losses during training and validation increased a lot using Jun 29, 2020 · 🐛 Bug. Sometimes a runtime crash is observed. Reload to refresh your session. Ray tune generates trials according to our hyper-parameter grid. fit() is stuck even before GPUs run. The two validation checks are executed. Jul 21, 2023 · Bug description The training code simply gets stuck on the TPU. pytorch imports with pytorch_lightning worked. For now Aug 18, 2022 · We are currently using ray tune. Code; Issues 84; Pull requests 14; I am still fighting against that freezing: it is the pytorch dataloder that gets stuck waiting for some process to end, torchmetrics had no fault. My train_dataloader has num_workers=4 and the sanity validation check runs fine. 1+cuda101和pytorch-lightning==1. Code class LitAutoEncoder(pl. I do not in particular, the chances of my job getting stuck is very low when num_workers=2, progressively increase as I set num_workers=4 or 8, i. Find more information about PyTorch’s supported backends here. import torch import torch. I have checked several similar issues but none seem to be the same as the one I’m facing. pyplot as plt import pytorch_lightning as pl import torch The same training script works well with Pytorch 1. something version. backward(). Thankfully, running experiments on a single GPU does not currently require many changes to your code. I want to plot the learning curve for all training, validation, and test datasets. It would be great if you could help me out. (in the sense I can’t even ctrl+c to stop it). 7 and noticed that after a few epochs of training, the training % is stuck at 0% and never progresses. You signed out in another tab or window. DeepSpeed is a deep learning training optimization library, providing the means to train massive billion parameter models at scale. When removing num_nodes, it operates as num_nodes=1 which means that the two nodes are running the training separately rather than cooperating. on the first "on_val_step()" output seems OK, loss scale is same as at the end of pre-train. DataParallel and the program gets stuck. 1 py3. 1 in docker container but issue persists. The number of nodes or number of devices per node is configured incorrectly: There are two parameters in the SLURM submission script that Oct 7, 2021 · I'm stuck using lightning=1. On the other hand, when I use ddp training does not start at all. Sometimes, the program will stuck at one step of the training while the utilization of all the 16 GPUs is 100%. Testing is performed using the Trainer object’s . step(optimizer) in Hi @edenlightning @justusschock,. Starting version 1. Also, just to clarify - I'm not using a jupyter notebook for this, just a terminal. Nvidia driver is 455. Loss does decrease. post0. 1. Lightning Trainer . One follow up question - on my follow up example I'm not using an interactive Oct 26, 2022 · From PyTorch to TensorFlow, support for GPUs is built into all of today’s major deep learning frameworks. when I am running the code it stuck forever with the below script. seasonal import seasonal Jan 7, 2019 · Hello, I am doing a grid search over many different hyper parameters. 7. 0 Distributed Data Parallel. I traced the origin of the problem to the following function, but I couldn't quite understand Mar 9, 2016 · DeepAR Training gets stuck at some random epoch #1281. Code; Issues 846; Pull requests 62; Discussions; Actions; Projects 0; Wiki; training stuck at initialisation #19606. But after calling: auto trt_mod = torch_tensorrt::torchscript::compile(module, compile_settings); the process gets stuck in an infinite(?) loop. 0. The finish() operation remains stuck in a while True loop and therefore the training script which waits for the wand Sep 21, 2023 · code does not work with: torch==1. is_available() and it returns true. 4 before. I have a detection model training on multiple GPUs in DDP mode with the MAP metric. awaelchli January 18, 2023, 1:28am 4. 5_0 pytorch pytorch-lightning 1. You do not want run an entire training loop (could take hours) and then realise that there is a problem in your validation loop. Your system might be unpacking the wheel, which might take some time. 0: 538: Jul 7, 2021 · Discussed in #8321 Originally posted by MendelXu July 7, 2021 When I use 2 GPUs, My training process is stuck at the beginning of the first epoch and even I am not able to kill it with ctrl+c. Usually it happens at the end of the first epoch, but sometimes in the middle of it. ”. scaler. The only modification I made is in Define the Jun 22, 2022 · EDIT: while at the beginning the code seems to be stuck at number of steps that are multiples of 48, I also noticed the progress bar getting stuck at step 965 which is obviously not a multiple of 48. I have tried to run it with Pytorch 1. cross_entropy(y_pred, y_true) self. I wrote a StackOverflow question describing my issue: https:/ Mar 6, 2019 · Hi! My program is getting stuck when I try to load resnet-18 on cuda. 2进行多卡训练，模式为'ddp'，中途会出现训练无法进行的问题。发现是版本问题，升级为pytorch-lightning==1. nn import init class PathEmbedding(nn. However with more than 1 worker, the May 15, 2024 · I’m training models using PyTorch Lightning, I built a loop to train one model at a time, but only the first model goes “far”, the other two are always stopping at the first epoch. If is a lightning feature it should say the stoppin criteria. The stopping point changes randomly (sometimes after epoch 4 validation, sometimes after epoch Jun 19, 2019 · I’m using PyTorchv1. 2 [BUG] Training gets stuck when model starts training #4443. I’m having difficulty understanding these stack traces, since they include >10 layers of PyTorch Lightning calls, and I don’t have a good Sep 21, 2023 · This mismatch is the most likely cause why it gets stuck. You can use TORCH_DISTRIBUTED_DEBUG=DETAIL to tell you the exact shapes and ranks that are mismatched. The loss function gets two augmented versions of an image and computes the similarity score. Screenshots val_loss still gets logged #522. There seems always one GPU got stuck Aug 4, 2022 · Hello, I am trying to train models using multiple GPUs (2). Lightning allows explicitly specifying the backend via the process_group_backend constructor argument on the relevant Strategy classes. How can I debug that? Using poly LR scheduler with warm-up epochs of 0! Jan 14, 2021 · I am using Pytorch (Pytorch Lightning Framework) to train the Text to Text Transformer model (google/mt5-base at main). Oct 30, 2020 · After the first training epoch, before the first validation, training gets stuck. 2 py38_cu110 pytorch. I use torch. However, the same code works on a May 14, 2023 · But now, when the model hits model(**inputs_dummy), the GPUs' utility reaches 100% instantly, and the whole process gets stuck. 5. Annoyingly, I cannot reproduce the code with the BoringModel. You labelled the issue with "information needed", please let me know what information I can supply. However when I reduce the number of GPU's it works again. For example, strategy="ddp" saves a single file on rank 0, while strategy="fsdp" saves multiple files from all ranks. Distributed communication package - torch. Only the 4 main Python threads seem to be doing any working (busy looping?). data. 2. I am currently using v1. I can also observe that the GPU load drops back to 0% after about 1s. but when i run the same with num_workers = 4, the speed increase is 3. stattools import adfuller from statsmodels. The effect is a large effective batch size of size KxN, where N is the batch size. Instead, Adam can get stuck in local optima while SGD finds the wider minima that tend to generalize better. I trained them on 1, 4, 5, 8 gpu environment Jan 30, 2023 · I am trying to train a BERT based model, but the model seems to get stuck after 1 epoch. You switched accounts on another tab or window. Below is a simple test code borrowed from ptrblck@discuss. 0 pytorch-lightning==2. Feb 13, 2021 · 🐛 Bug. Sep 25, 2020 · PyTorch Forums How to improve model training, loss gets stuck. (ran a loop of 100 runs and it got stuck at some point; In the example, I used the Office-Home dataset, but I suppose the specific dataset doesn’t matter) Here’s the stack trace when I Ctrl+c’ed : Starting training [15:32 26-08-2020] Jun 19, 2019 · The training process will get stuck at some constant steps. logits y_true = batch["rbd_labels"] # loss loss = F. How can I solve this problem? IMG_20230717_120431 1920×971 90. I was able to come up with a minimal example that I found had similar behavior. GPU usage increases to 100%. However, it has one problem. DeepSpeed also offers lower level training Dec 19, 2022 · What I want to do: TensorRT optimization of a PyTorch trained model which was previously saved as a torchscript-Model. My code works fine on a single node, multi-GPUs mode (which means I did most part for DDP training right). Initially, we suspected it was a communication issue, as most Jun 8, 2020 · You signed in with another tab or window. This development process is slow and bug-prone, so we run a small Aug 26, 2020 · Hi, The code I’m working on randomly used to get stuck. 0, I have: Jul 17, 2023 · Hello,i’m downloading Pytorch,but it is stuck like this. init_module¶ Instantiating a nn. distributed — Mar 5, 2022 · Hi: I am recently using 16 GPUs to train a model with DDP strategy. Dec 21, 2024 · This covers PyTorch, NumPy, and Python random number generators. However, I noticed that the training speed gets slow down slowly at each batch and memory usage on GPU also increases. And I met the following problem: My training code gets stuck after tens of iteration steps (it does not iterate anymore after hours waiting). I notice that when I set the num_workers >0 for my val_dataloader the validation step on epoch 0 crashes. Thanks for your help Feb 14, 2022 · 🐛 Bug Training is stuck when using ddp, gpus=[0, 1], and num_sanity_val_steps=2. There is a queue with all hyperparameter configurations and each thread gets its The first thing I noticed in the outputs (also as a difference from your output), is the line with CUDA_VISIBLE_DEVICES. py command with srun: Please have a look at the SLURM template script above which includes the srun at the bottom of the script. I defined a ModelCheckpoint that saves the 5 best iterations and an After validation ends (100%), the training process randomly stops without any error log. As models continue to increase in size, however, and as the data needed to train them grows exponentially, running on a single GPU Jul 6, 2020 · @andrewjong, that's really helpful. My goal is to make it work with Pytorch Lightning however an annoying termination issue, makes it impossible to run any experiments on the WSL under Windows 11. I have also tried playing with learning rate. But I have not been able to load my model on cuda. 9 the numbers "96% 4260/4435" keeps the same forever. LightningModule): def __in Jun 22, 2022 · @awaelchli, thanks I wasn't aware of the limitations around interactive shells. It works fine, when I train it on a single gpu. According to my experience, this seems like something is wrong in your data processing (dataset, dataloader or datasampler). However, if I run the same script through the remote interpreter function of Pycharm, it works. prepare_model(student)” and on the print with “Wrapping provided model in DDP. Does PyTorch-lightning support compute capability 3. Im training a model using DDP on 2 P100 GPUs. However, when using DDP, the script gets frozen at a random point. Using High-RAM environment and get "TPU has started up successfully with version pytorch-1. Trying to test some new stuff in master branch (built from source), but training always got stuck after a few hundreds iterations withou Jun 20, 2023 · When I start training, the output gets stuck on “initializing ddp: GLOBAL_RANK” and the terminal freezes (Ctrl + C won’t work anymore). thanks for responding so quickly. 8_cuda11. I noticed some wired things: The Memory usage keeps freeze. Edit: So call_hook has the following signature def call_hook(self, hook_name, *args, **kwargs) and within call_hook there is trainer_hook(*args, **kwargs) and hook_fx(*args, **kwargs) (in this case: on_fit_start) both are called with the same args but Sep 18, 2023 · Hello, I am running into a strange issue when using WandB to log experiments online. Your model still seems to have some trouble learning the data. And I use nvidia-smi to see the GPU use, the GPU is still occupied and doing computation. py with DDP in the same environment with different hyperparameters would get stuck when the first epoch was completed, then I tried to update the latest PyTorch-Lightning version and started train. 7? One of the HPC specialists who manage my compute cluster tried debugging this today and said the issue was isolated to the K80 nodes and that he got it Mar 27, 2019 · For just 10 samples, the loss should decrease basically to zero. def _prepare_dataloader(self, X, y=None, shuffle=False, predict=False): """ Nov 24, 2020 · How do you prevent overfitting when your dataset is not that large? My dataset consists of 110 classes, with a total dataset size of about 20k images. Nov 12, 2021 · 🐛 Bug. But if i install the torch from pip or conda, the some code can work smoothly. spawn to do this, while using num_workers =0 the below code runs fine, it train the 3 models one after the other. In addition, Fabric takes care of properly initializing the seed of data loader worker processes (can be turned off by passing workers=False). Dec 5, 2021 · In PyTorch the rank 0 process would only generate randomness for once, each yield one sample of train/val dataset number, and the Distributed Sampler would distribute that one sample of train/val number into different nodes, Dec 4, 2018 · Hi, all, I am the new user of the Pytorch. mp. Right now, it gives the follo Mar 12, 2021 · I use the command python main. Then I use Ctrl+C to stop the training, it does not stop the code. The test result is good. I was trying to train my model on 2 GPUs using the ddp strategy and it would consistently freeze on Epoch 0, Batch 40. Mar 13, 2021 · pytorch 1. Just dropping this here in case it helps anyone. I’m trying to train a model on multiGPU using nn. This is an issue that does not always occur which could be an indicator Feb 24, 2024 · -PyTorch-Lightning version：2. 6. All GPUs are now working I have the same issue with 8 GPUs 2 nodes on version 1. Anyone can help me with that? Is it a syncbatchnorm problem or what? Even if I finetune the pretrained model(on 1. I've let the Dec 21, 2024 · DeepSpeed¶. Has anyone else experienced a similar issue？ Your insights and suggestions would be greatly appreciated. However, all of 8gpu and 5gpu training attempts, are stuck and failed at a specific point in a specific epoch (54). Last version of lightning that worked for us is 1. 1, I have: CUDA_VISIBLE_DEVICES: [8,9] and a CUDA OOM. Essentially, I don't want to save the model but evaluate the val and test Jan 14, 2021 · Hello, I am using Pytorch Lightning Framework to train the Text to Text Transformer model (google/mt5-base at main). The same model trains successfully on 1 GPU in Colab and locally. Pepi (Zain) September 25, 2020, 5:45pm 1. My code looks something like the follows At each validation step def validation_step(self, batch, batch_idx): # forward outputs = self. To speed up Feb 8, 2023 · The pytorch-lightning package still exits, gets updates and can be downloaded because that's what many users and companies rely on today. nn as nn from torch. Testing¶ Lightning allows the user to test their models with any compatible test dataloaders. If you're fine leaving performance on the table, it's ok, but performance using RDMA is much higher than using TCP/IP, plus it has a much lesser load on the CPU. 8. 5 Apr 26, 2020 · I wonder if the issue is the “fork” mode of multiprocessing. 0 and DistributedDataParallel to train some models. My training set consists of about 50,000 images, the validation set has around 10,000 images, and I'm using 2 A5000 GPUs for training with a distributed data parallel (ddp) strategy. unwrap_batch(batch) x = Jul 18, 2022 · If the all_gather call is hanging it is probably due to mismatched shapes. encoders import TorchNormalizer import os,sys import numpy as np from statsmodels. heihqkj yfn pzgp ewdh thkfd fklzx kougr eystp lqsa rhb