# Callback for RNN training


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<a
href="https://github.com/fastai/fastai/blob/main/fastai/callback/rnn.py#L14"
target="_blank" style="float:right; font-size:smaller">source</a>

### ModelResetter

``` python

def ModelResetter(
    after_create:NoneType=None, before_fit:NoneType=None, before_epoch:NoneType=None, before_train:NoneType=None,
    before_batch:NoneType=None, after_pred:NoneType=None, after_loss:NoneType=None, before_backward:NoneType=None,
    after_cancel_backward:NoneType=None, after_backward:NoneType=None, before_step:NoneType=None,
    after_cancel_step:NoneType=None, after_step:NoneType=None, after_cancel_batch:NoneType=None,
    after_batch:NoneType=None, after_cancel_train:NoneType=None, after_train:NoneType=None,
    before_validate:NoneType=None, after_cancel_validate:NoneType=None, after_validate:NoneType=None,
    after_cancel_epoch:NoneType=None, after_epoch:NoneType=None, after_cancel_fit:NoneType=None,
    after_fit:NoneType=None
):

```

*[`Callback`](https://docs.fast.ai/callback.core.html#callback) that
resets the model at each validation/training step*

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<a
href="https://github.com/fastai/fastai/blob/main/fastai/callback/rnn.py#L24"
target="_blank" style="float:right; font-size:smaller">source</a>

### RNNCallback

``` python

def RNNCallback(
    after_create:NoneType=None, before_fit:NoneType=None, before_epoch:NoneType=None, before_train:NoneType=None,
    before_batch:NoneType=None, after_pred:NoneType=None, after_loss:NoneType=None, before_backward:NoneType=None,
    after_cancel_backward:NoneType=None, after_backward:NoneType=None, before_step:NoneType=None,
    after_cancel_step:NoneType=None, after_step:NoneType=None, after_cancel_batch:NoneType=None,
    after_batch:NoneType=None, after_cancel_train:NoneType=None, after_train:NoneType=None,
    before_validate:NoneType=None, after_cancel_validate:NoneType=None, after_validate:NoneType=None,
    after_cancel_epoch:NoneType=None, after_epoch:NoneType=None, after_cancel_fit:NoneType=None,
    after_fit:NoneType=None
):

```

*Save the raw and dropped-out outputs and only keep the true output for
loss computation*

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<a
href="https://github.com/fastai/fastai/blob/main/fastai/callback/rnn.py#L29"
target="_blank" style="float:right; font-size:smaller">source</a>

### RNNRegularizer

``` python

def RNNRegularizer(
    alpha:float=0.0, beta:float=0.0
):

```

*Add AR and TAR regularization*

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<a
href="https://github.com/fastai/fastai/blob/main/fastai/callback/rnn.py#L41"
target="_blank" style="float:right; font-size:smaller">source</a>

### rnn_cbs

``` python

def rnn_cbs(
    alpha:float=0.0, beta:float=0.0
):

```

*All callbacks needed for (optionally regularized) RNN training*