Pytorch infinite dataloader Trying to test some new stuff in master branch (built from source), but training always got stuck after a few hundreds iterations withou Dec 4, 2020 · To create such a dataloader you will first need a class which inherits from the Dataset Pytorch class. Infinite iterator for training Let’s use an infinite data iterator as training dataflow DataLoader – First entry is x, a dictionary of tensors with the entries, and shapes in brackets. One of its key components is the `DataLoader`, which simplifies the process of loading and batching data during model training and inference. This is a subclass of torch. Dataset that allow you to use pre-loaded datasets as well as your own data. Dec 29, 2018 · Hey there I am new to PyTorch. How could I reset it before it accomplish one epoch so that it will not raise a stopIteration May 27, 2025 · During training, it's usually beneficial to shuffle the data to prevent the model from memorizing the order of the samples and to ensure that each batch is a representative sample of the overall dataset. There is a standard implementation of this class in pytorch which should be TensorDataset. But I primarily work with images and text. I think its that the stopping condition of looping through the dataset has to be using the len function. I have an infinite DataLoader that wraps an IterableDataset that basical Nov 11, 2017 · In the examples on how to use a Dataset object, it is suggested to access it with: for i in range (len (dataset)): print (dataset [i]) but it would be reasonable to expect that you can access a dataset as an iterator, like: for item in datas Jul 7, 2020 · Hello, Hello, i was wondering how the dataloder with num_workers > 0 queu works. DataLoader that does not stop producing minibatches after the dataset is consumed but is a (potentially unbounded) generator of minibatches. encoder_cat long (batch_size x n_encoder_time_steps x n_features) Jun 11, 2020 · I just started playing with pytorch-lightning API to decide whether to make the switch for my own speech processing project. In this article, we'll explore how PyTorch's DataLoader works and how you can use it to streamline your data pipeline. W Feb 13, 2020 · The same training script works well with Pytorch 1. In my use case it is about 25s every time and can be completely eliminated by having an infinite sampler, saving hours of training time. I imagine N wokers are created. IterableDataset. class MyDataLoader(torch. py. Dataset): def __init__(self, data_size=50000): self. Direct… Aug 6, 2019 · Is there a canonical way of creating an infinite iterator in pytorch? It is unfortunate that itertools. 0) dataloader on a custom dataset freezes occasionally. Can someone advise what’s the best way to have what I want implemented? (Use DataLoader’s parallel loading, while simultaneously guaranteeing every batch loaded is entirely new. This even happens when my call-back uses data not even seen in training. Though for some reason it DOES work on the strange example I cooked up without looping forever…so it might be a weird edge case. I expect once I wrap it with the dataloader class everything should work fine (I hope). DataLoad can only provide data batch of one epoch. g. We know you can define your own. I cannot reproduce the freezing, it seems random: it usually "runs" without issues, but sometimes it gets stuck. In situations where the training data is too large to fit into machine memory, one approach is to write a data loader that . cycle is implemented in this way, although I suppose it makes sense in the average case where the amount of data is very low. get (timeout=timeout) on line 779 of the Pytorch python code dataloader. The authors train the networks on the given number of images, instead of for a given number of epoch Feb 20, 2022 · Dataset and DataLoader's parts are ok, I recycled from another code that I built, but got an infinite loop at that part in my code: def train (train_loader, MLP, epoch, criterion, optimizer): MLP. DataLoader can shuffle the data at the beginning of each epoch (a complete pass through the dataset). This article provides examples of how it can be used to implement a parallel streaming DataLoader Feb 1, 2021 · I want to load video frames to train my network, and to speed things up, I’d like to use multiple threads. The DataLoader supports both map-style and iterable-style datasets with single- or multi-process loading, customizing loading order and optional automatic batching (collation) and memory pinning. Oct 22, 2025 · Learn how PyTorch’s DataLoader speeds up deep learning with efficient batching, shuffling, and lazy loading across diverse data types. Aug 15, 2022 · I have created a dataloader whose length is 50000. Apr 1, 2021 · When using the PyTorch neural network library to create a machine learning prediction model, you must prepare the training data and write code to serve up the data in batches. Aug 11, 2018 · The torch. This evidence strongly Jul 16, 2019 · I think I figured it out. Jul 23, 2025 · It provides functionalities for batching, shuffling, and processing data, making it easier to work with large datasets. Dataset stores the samples and their corresponding labels, and DataLoader wraps an iterable around the Dataset to enable easy access to the samples. DataLoader and torch. ) Mar 7, 2025 · Depending on the dataset, the overhead of recreating the dataloader iter can be significant. The problem is that the length of the sampler cannot be infinite as python does not have infinite integer. data. 11. Here’s what I tried: class Infinite(Dataset): def __len__(self): return HPARAMS. 4 before. You would need to subclass Sampler and give an instance of your custom sampler to the dataloader you’re creating. I see 2 options: the program goes through all workers in sequence? This would mean that if one worker is delayed for some reason, the other workers have to wait until this specific worker can deliver the goods. I tried two approaches and would like to know which one should be preferred or if there is a better solution for an infinite stream of data in Pytorch. So you may have to use a very large number there like int(1e100). Dec 8, 2017 · the dataset itself has only 150 data points, and pytorch dataloader iterates jus t once over the whole dataset, because of the batch size of 150. It provides functionalities for batching, shuffling, and processing data, making it easier to work with large datasets. This blog aims to delve into the fundamental concepts What are some optimizations that one could use for the data loader in PyTorch? The data type could be anything. Oct 3, 2021 · I'm learning pytorch, and I'm trying to implement a paper about the progressive growing of GANs. Jan 25, 2019 · Upon a casual look at the Python side of things I can’t pinpoint where. Jan 24, 2019 · 我不认为PyTorch API支持无限集合，但是您可以尝试在 DataLoader 中分叉代码并自己执行。 您可以使用 batch_sampler 参数，并传入一个基于 RandomSampler 实现的自定义变体。 Feb 24, 2019 · I’d like to implement an infinite loop Dataset & DataLoader. _data_queue. When I calculate its length it prints out 50000. Infinite iterator for training Let’s use an infinite data iterator as training dataflow Oct 29, 2025 · There appears to be a significant and consistent memory leak in the PyTorch DataLoader on the Windows platform. However, a common and frustrating issue that many practitioners encounter is the `DataLoader` hanging. The leak occurs specifically when the DataLoader's iterator is kept alive for a large number of steps (e. With the python debugger (pdb) I’ve seen that internally, torch goes into a while True loop and never exits. utils. How to work with data iterators When the data provider for training or validation is an iterator (infinite or finite with known or unknown size), here are some basic examples of how to setup trainer or evaluator. 2 brought with it a new dataset class: torch. Nov 21, 2018 · Hi, I am not sure this would work. , in an "infinite" sampling loop for step-based training). But does anyone have any clever tricks to share? Thank you in advance! Aug 14, 2022 · My Pytorch (1. May 11, 2018 · Is there a good way to have an infinite dataloader? That said, is there a class that will provide automatically looping for method like data_loader. I can Oct 29, 2025 · There appears to be a significant and consistent memory leak in the PyTorch DataLoader on the Windows platform. get_next()? And how to maintain full iterations? May 5, 2023 · I would like to use IterableDataset to create an infinite dataset that I can pass to DataLoader. Then the iterator is simply an iterator that return a random valid index Nov 13, 2023 · Test_dataloader = DataLoader(test_dataset,batch_size = batch_size, shuffle = False,num_workers=1) When I try to iterate and sample the very first datapoint in the Train_dataloader using the following python iter and next functions, it seems get into an infinite loop type of scenario PyTorch provides two data primitives: torch. Here’s a Pytorch 实现“无限循环”数据集和数据加载器 在本文中，我们将介绍如何使用PyTorch实现一个“无限循环”的数据集和数据加载器。 在机器学习任务中，通常需要循环使用数据，以便有效地训练模型。 我们将使用PyTorch的Dataset和DataLoader类来完成这个任务。 Feb 1, 2021 · This call back executes normally but when I revert to training the pytorch dataloader code gets stuck in an infinite loop calling self. This would also mean that if a worker gets stuck into an infinite loop Jul 23, 2025 · PyTorch's DataLoader is a powerful tool for efficiently loading and processing data for training deep learning models. Trying to test some new stuff in master branch (built from source), but training always got stuck after a few hundreds iterations withou What are some optimizations that one could use for the data loader in PyTorch? The data type could be anything. I created a custom Dataset class for this, but when the Dataloader tries to iterate over it, it gets stuck. batch_size # return 1<<30 # This causes huge memory usag Jul 8, 2025 · In the realm of deep learning, PyTorch has emerged as a powerful and widely - used framework. My question is now, is there generally any way to tell dataloader of pytorch to repeat over the dataset if it's once done with iteration? 代码解析 这段代码基于 infinite_data_loader 参数创建不同类型的数据加载器： 当 infinite_data_loader 为True时： 创建 InfiniteDataLoader 实例 自定义的无限循环数据加载器，会持续提供数据而不会在一个epoch结束时停止 当 infinite_data_loader 为False时： 创建标准的PyTorch DataLoader 实例 这是普通的数据加载器，一个 Oct 31, 2019 · The release of PyTorch 1. Nov 8, 2024 · Setting Up the Environment To get started with IterableDataset in PyTorch, you’ll need a recent version of the library, along with any dependencies specific to your project. I can predict and classify images one by one, can anyone please help me to classify all the images of a folder in a batch. However, I can successfully iterate over the dataset manually. Jun 13, 2025 · Data loader combines a dataset and a sampler, and provides an iterable over the given dataset. I have a inference code that predicts and classify images. nuj1z k6ijc wrgt jiw koaei pwy 4vhu zradf qm33u lou