# add\_prediction

The purpose of the `leap_binder.add_prediction` function is to describe the prediction(s) tensors for visualization and analysis purposes. This function adds a prediction type, which later can be assigned to the model graph prediction node(s).

```python
code_loader.leap_binder.add_prediction(
    name=str,
    labels=List[str]
    channel_dim: int = -1
)
```

<table><thead><tr><th width="158.46928201888204">Args</th><th></th></tr></thead><tbody><tr><td><code>name</code></td><td><em>(str)</em> with the given name of the <strong>input,</strong> e.g. image</td></tr><tr><td><code>labels</code></td><td><em>(List[str])</em> an array containing the labels associated with this <strong>prediction</strong></td></tr><tr><td><code>channel_dim</code></td><td>(defaults to -1). The dimension in which the channels exists in the prediction. channel_dim should be set to 1 for channel first predictions (i.e. - C,H,W).</td></tr></tbody></table>

### Examples

#### Basic Usage

```python
...

LABELS = ['0','1','2','3','4','5','6','7','8','9']
leap_binder.add_prediction(
    name='predicted_digit',
    labels=LABELS
)
```

Full script usage can be found at [**Integration Script**](/tensorleap-integration/writing-integration-code.md#dataset-script).

#### Guides

Full examples can be found at the **Dataset Integration** section of the following guides:

* [**MNIST Guide**](/guides/full-guides/mnist-guide.md)
* [**IMDB Guide**](/guides/full-guides/imdb-guide.md)


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