imbalanced-dataset-sampler
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A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
Hi, I am using BERT for multi label classification. The dataset is imbalance and I use ImbalancedDatasetSampler as the sampler. The train data has been tokenized, has id, mask and...
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If I can make one small quick suggestion, perhaps the two following plots in your README should have the same y axis limits. 
https://github.com/zzw-zwzhang/Yoneed/blob/main/sampler.py#L15
Hi everyone, I have a question concering using subsets with this sampler. According to the code it chooses samples from all entries in the parent dataset: https://github.com/ufoym/imbalanced-dataset-sampler/blob/e9dd2deca6e058771533678b29b38a60843b0a85/torchsampler/imbalanced.py#L49-L50 Shouldn't it only...
I have added a few lines that allow to work with pytorch-geometric dataset. Since Pytorch-geometric data is saved as a list before being loaded by a Pytorch-geometric Dataloader, the modification...
`callback_get_label: a callback-like function which takes two arguments - dataset and index` This [no longer seems to be the case](https://github.com/ufoym/imbalanced-dataset-sampler/commit/ad50e22240c5316f8855db972542e1e2c388f839#diff-2df1f4597623f25e583732eb253eba0b08914c4a36d219d19dda17b9c7b3932dR42)? Please update how the new use-case looks like, because above...
I don't know if the val_dataset needle a balance. Thanks.
Thanks for the great work! I try to combine two datasets by using "dataset = dataset1+dataset2", and it gives me such error: AttributeError: 'ConcatDataset' object has no attribute 'get_labels' Is...
Hi ! I noticed that they are some bugs introduce with the last commit [ad50e22](https://github.com/ufoym/imbalanced-dataset-sampler/commit/ad50e22240c5316f8855db972542e1e2c388f839) Step to reproduce ` import torch from torchsampler import ImbalancedDatasetSampler mnist = torchvision.datasets.MNIST('.', train=True, download=True,...