# alibi\_detect.models.tensorflow\.trainer

## Functions

### `trainer`

```python
trainer(model: keras.src.models.model.Model, loss_fn: .keras._tf_keras.keras.losses, x_train: numpy.ndarray, y_train: numpy.ndarray = None, dataset: keras.src.trainers.data_adapters.py_dataset_adapter.PyDataset = None, optimizer: .tensorflow.keras.optimizers = <class 'keras.src.optimizers.adam.Adam'>, loss_fn_kwargs: dict = None, preprocess_fn: Callable = None, epochs: int = 20, reg_loss_fn: Callable = <function <lambda> at 0x28ee82e50>, batch_size: int = 64, buffer_size: int = 1024, verbose: bool = True, log_metric: Tuple[str, ForwardRef('tf.keras.metrics')] = None, callbacks: .tensorflow.keras.callbacks = None) -> None
```

Train TensorFlow model.

| Name             | Type                                                            | Default                                    | Description                                                                    |
| ---------------- | --------------------------------------------------------------- | ------------------------------------------ | ------------------------------------------------------------------------------ |
| `model`          | `keras.src.models.model.Model`                                  |                                            | Model to train.                                                                |
| `loss_fn`        | `.keras._tf_keras.keras.losses`                                 |                                            | Loss function used for training.                                               |
| `x_train`        | `numpy.ndarray`                                                 |                                            | Training data.                                                                 |
| `y_train`        | `numpy.ndarray`                                                 | `None`                                     | Training labels.                                                               |
| `dataset`        | `keras.src.trainers.data_adapters.py_dataset_adapter.PyDataset` | `None`                                     | Training dataset which returns (x, y).                                         |
| `optimizer`      | `.tensorflow.keras.optimizers`                                  | `<class 'keras.src.optimizers.adam.Adam'>` | Optimizer used for training.                                                   |
| `loss_fn_kwargs` | `dict`                                                          | `None`                                     | Kwargs for loss function.                                                      |
| `preprocess_fn`  | `Callable`                                                      | `None`                                     | Preprocessing function applied to each training batch.                         |
| `epochs`         | `int`                                                           | `20`                                       | Number of training epochs.                                                     |
| `reg_loss_fn`    | `Callable`                                                      | `<function <lambda> at 0x28ee82e50>`       | Allows an additional regularisation term to be defined as reg\_loss\_fn(model) |
| `batch_size`     | `int`                                                           | `64`                                       | Batch size used for training.                                                  |
| `buffer_size`    | `int`                                                           | `1024`                                     | Maximum number of elements that will be buffered when prefetching.             |
| `verbose`        | `bool`                                                          | `True`                                     | Whether to print training progress.                                            |
| `log_metric`     | `Tuple[str, ForwardRef('tf.keras.metrics')]`                    | `None`                                     | Additional metrics whose progress will be displayed if verbose equals True.    |
| `callbacks`      | `.tensorflow.keras.callbacks`                                   | `None`                                     | Callbacks used during training.                                                |

**Returns**

* Type: `None`


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