Pytorch resnet memory leak. 2GB on average.


  1. Pytorch resnet memory leak. One obvious fix would be to break your video into multiple chunks so that your seq_length effectively comes down. empty_cache () to release CPU memory explicitly? I meet memory leak on CPU. This is currently causing my model to crash every ~9 hours because it eats up ~64gb of ram and crashes due to OOM. Feb 2, 2024 · I tested it in the latest official release. 0. Here is the piece of code to reproduce this fault. no_grad(): #Create a simple resnet model = model_zoo. Most of the memory leak threads I found were unhelpful so I wanted to throw together a few tips her… Jul 9, 2025 · In this blog post, we will explore the fundamental concepts of PyTorch Lightning memory leaks, their usage in the context of deep learning, common practices to identify them, and best practices to prevent and fix them. 2. I started to profile my app to find a place with huge memory allocation and found it in model inference (if I comment my network inference then there’s no problems with a memory). getpid()). Other backends such as aot_eager and cudagraphs show completely flat memory usage. My code is like: Jun 11, 2020 · I’m trying to run my model with Flask but I bumped into high memory consumption and eventually shutting down of server. cuda. memory_info()[0]/(2. I’m using the following test code: #Utilities import os import psutil #JIT trace test import torch import torchvision. Feb 14, 2022 · I’m currently processing a video data where I’m wanting to convert each video into 3 feature types: mfcc features for the audio, a directory of 160x160 torch tensors with the cropped faces from each frame (the videos are of zoom conversations), and finally a [n_frames x 512] tensor of facial features from each frame that are computed using a pretrained resnet. 6. backward (). I guess that somehow a copy of the graph remain in the memory but can’t see where it happens and what t… Mar 26, 2020 · Hi Maybe I’m doing something wrong, but I’ve noticed a continuous increase in the memory usage when calling torch. 0, maskrcnn for inference. The leak seems to be happening at the first call of loss. The code for 2 nodes is like this, First, I define two classes for transformer shard import os import sys import threading import time import torch import torch. jit. rpc as rpc from torch. My conclusion is that the leak has been fixed. nn as nn import torch. Aug 24, 2024 · This I think is the root cause of your memory issues. rpc to implement pipeline parallelism for transformer-based inference, the memory consumption increases with each forward pass. I’m using the “nvidia-smi -lms 100” and windows Task Manager to monitor the usage of GPU, so There is any wrong in monitor the usage of GPU or just pytorch leak GPU memory in conv2d? Aug 8, 2021 · The isue is exactly describe here: CPU memory gradually leaks when num_workers > 0 in the DataLoader · Issue #13246 · pytorch/pytorch · GitHub I do use num_workers=16 but the solution posted there, using pyarrow, does not solve my issue - I still have this memory leak. resnet50() for i in range(1000): jit_resnet50 = torch. no_grad() and calling torch. Apr 3, 2020 · To start with, I’m using the following: My model input is RGB images of size 128x128. trace(model, inputs) multiple times in the same process. 0,mmdetection 2. PyTorch will not be able to free the computation graph in the backward() call due to this. empty_cache() after each iteration. In Resnet the first conv2d seem to consume about 300M and not release after that. Aug 26, 2017 · Something to consider with variable sized batches is that pytorch allocates memory for the batches as needed and doesn’t free them inline because the cost of calling garbage collection during the training loop is too high. **30) ) increases by about 0. distributed. Mar 25, 2021 · Hi All, I was wondering if there are any tips or tricks when trying to find CPU memory leaks? I’m currently running a model, and every epoch the RAM usage (as calculated via psutil. models as vision_models from torchvision. models import resnet resnet50 = vision_models. 2GB on average. The size of the training set is something around 122k and my validation’s 22k. resnet18 Jan 5, 2022 · I have found there is obvious memory leak when I try to export torchscript multiple times. Jan 22, 2025 · To further illustrate the memory leak issue, here's another example using a simple ResNet + LSTM model. The code uses two pretrained Feb 2, 2023 · You are not running into a memory leak but an expected increase in memory usage since you are storing tensors without detaching them. mps. Are there any tips or tricks for finding memory leaks? The only thing Jul 20, 2021 · Hi, when I use torch. Jan 22, 2020 · Just wanted to make a thread with some information I wish I found before spending 4 hours trying to debug a memory leak. rpc Nov 7, 2022 · Is there a way like torch. I will give different solutions Apr 3, 2020 · Memory Leakage with PyTorch If you’re reading this post, then most probably you’re facing this problem. 80k different shapes were used. First inference: Line # Mem usage Increment Line Contents Mar 16, 2023 · The inductor backend for torch. Similar to the previous example, memory usage steadily increases during repeated inference, even when using torch. 7, poytorch1. And I’m really not sure where this leak is coming from. This Dec 12, 2023 · I run out of GPU memory when training my model. The memory rises at around 5k initial shapes, and then remains almost constant as more different shapes are inputted. I am on python3. models as model_zoo with torch. jit . The process may occupy over 20 GB RAM after exporting resnet50 40 times. Process(os. import torch import torchvision. RAM is full, in the very beginning of the training, your data is not huge, and maybe Sep 16, 2020 · I’m using pytorch 1. Learn diagnostics, root causes, and memory optimization strategies for large-scale ML training. compile leaks memory on every call to a compiled mmseg model. 9. Jul 20, 2025 · Troubleshoot PyTorch GPU memory leaks and CUDA OOM errors. 66f5agm ojmdz vylxj fgb2 yiywa fxy 0jia w8j p49 fxk