'RandomSampler' object has no attribute 'set_epoch'

lili084 commented 1 month ago

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Question

I'm using train.py to train my own data and I'm getting this error, I'm not sure how it's happening if RANK != -1: train_loader.sampler.set_epoch(epoch)

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glenn-jocher commented 1 month ago

@lili084 hi there,

Thank you for reaching out and providing details about the issue you're encountering.

The error you're seeing, 'RandomSampler' object has no attribute 'set_epoch', typically occurs when the train_loader is using a RandomSampler instead of a DistributedSampler. The set_epoch method is specific to DistributedSampler and is used in distributed training to shuffle the data differently at each epoch.

To resolve this, please ensure that your code is correctly setting up the DistributedSampler when running in a distributed environment. Here is a snippet that demonstrates how to set up the DistributedSampler:

from torch.utils.data import DistributedSampler

# Assuming dataset is already defined
if RANK != -1:
    sampler = DistributedSampler(dataset)
else:
    sampler = torch.utils.data.RandomSampler(dataset)

train_loader = torch.utils.data.DataLoader(dataset, sampler=sampler, ...)

If you are not running in a distributed environment, you can bypass the set_epoch call by adding a condition:

if RANK != -1:
    train_loader.sampler.set_epoch(epoch)

Please make sure you are using the latest version of YOLOv5 and all related dependencies. You can update YOLOv5 by pulling the latest changes from the repository:

git pull

If the issue persists after these changes, please let us know, and we can further investigate. Thank you for your patience and for being a part of the YOLO community! 😊

ultralytics / yolov5