> For the complete documentation index, see [llms.txt](https://docs.elbo.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.elbo.ai/reference/api-reference/the-elbo.elboepochiterator.md).

# The elbo.ElboEpochIterator

The iterator class is a decorator on top of a traditional Python iterator. Add this to your training epoch loop.

## Usage

The `elbo.EpochIterator` takes the following arguments:

* The range of epochs usually - `range(0, num_epochs)`
* The PyTorch model it is training
* `save_state_interval` How often should the model state be saved to artifacts directory. A value of `5` means the model state will be saved every 5 epochs.

```python
if __name__ == '__main__':
    print(f"Training MNIST classifier")
    train_data = datasets.MNIST("data", train=True, transform=transforms.ToTensor(), download=True)
    test_data = datasets.MNIST("data", train=False, transform=transforms.ToTensor(), download=True)
    model = MNISTClassifier()
    num_epochs = 10

    for epoch in elbo.elbo.ElboEpochIterator(range(0, num_epochs), model, save_state_interval=1):
        loss = train(model, train_data)
        print(f"Epoch = {epoch} Loss = {loss}")

    test(model, test_data)
```