torch backend: keras.utils.split_dataset requires tensorflow

[oluwandabira]

The keras.utils.split_dataset function requires tensorflow to be installed even tho the docstring states that the dataset argument can be a torch.utils.data.Dataset (and I assumed that means it would just work on the torch dataset with no issues).

[TaiXeflar]

Same pytorch user just here.
Keras 3 will use tf as backend as default if KERAS_BACKEND is not set.
You can export ENV variable or just add this at the top of your python script:

import os
os.environ["KERAS_BACKEND"] = "torch"

I think this will helps?

[oluwandabira]

Thanks but that isn't the issue. I've set the KERAS_BACKEND environment variable to torch I can fit and evaluate and evaluate my pytorch model with pytorch dataloaders just fine, but spliting my pytorch dataset with keras.utils.split_dataset fails because I don't have tensorflow installed.

[sonali-kumari1]

Hi @oluwandabira -

Could you please provide a standalone code and Pytorch dataset you are trying to split with keras.utils.split_dataset to replicate this issue. Thanks!

[oluwandabira]

import os
os.environ["KERAS_BACKEND"] = "torch"
import torch
import keras

class Dataset(torch.utils.data.Dataset):
    def __init__(self, len : int):
        super().__init__()
        self._len = len

    def __len__(self):
        return self._len

    def __getitem__(self, index):
        return torch.rand((224, 224, 3)), torch.rand(())
    

dataset = Dataset(10)

train, test = keras.utils.split_dataset(dataset, left_size=0.7)

pip freeze

absl-py==2.1.0 contourpy==1.3.1 cycler==0.12.1 filelock==3.17.0 fire==0.7.0 fonttools==4.56.0 fsspec==2025.2.0 h5py==3.13.0 Jinja2==3.1.5 joblib==1.4.2 keras==3.8.0 kiwisolver==1.4.8 markdown-it-py==3.0.0 MarkupSafe==3.0.2 matplotlib==3.10.0 mdurl==0.1.2 ml_dtypes==0.5.1 mpmath==1.3.0 namex==0.0.8 networkx==3.4.2 numpy==2.2.3 nvidia-cublas-cu12==12.4.5.8 nvidia-cuda-cupti-cu12==12.4.127 nvidia-cuda-nvrtc-cu12==12.4.127 nvidia-cuda-runtime-cu12==12.4.127 nvidia-cudnn-cu12==9.1.0.70 nvidia-cufft-cu12==11.2.1.3 nvidia-curand-cu12==10.3.5.147 nvidia-cusolver-cu12==11.6.1.9 nvidia-cusparse-cu12==12.3.1.170 nvidia-cusparselt-cu12==0.6.2 nvidia-nccl-cu12==2.21.5 nvidia-nvjitlink-cu12==12.4.127 nvidia-nvtx-cu12==12.4.127 optree==0.14.0 packaging==24.2 pillow==11.1.0 Pygments==2.19.1 pyparsing==3.2.1 python-dateutil==2.9.0.post0 rich==13.9.4 scikit-learn==1.6.1 scipy==1.15.2 six==1.17.0 sympy==1.13.1 termcolor==2.5.0 threadpoolctl==3.5.0 torch==2.6.0 torchvision==0.21.0 triton==3.2.0 typing_extensions==4.12.2

Running the above code in the above environment results in a ImportError: This requires the tensorflow module. You can install it via 'pip install tensorflow'

[sonali-kumari1]

Hi @oluwandabira -

Thanks for sharing the reproducible code. We will look into it and update you soon.