# tf.contrib.layers.unit_norm

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/contrib/layers/python/layers/layers.py#L3065-L3100) |

Normalizes the given input across the specified dimension to unit length.

    tf.contrib.layers.unit_norm(
        inputs, dim, epsilon=1e-07, scope=None
    )

Note that the rank of `input` must be known.

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| ## Args ||
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| `inputs` | A `Tensor` of arbitrary size. |
| `dim` | The dimension along which the input is normalized. |
| `epsilon` | A small value to add to the inputs to avoid dividing by zero. |
| `scope` | Optional scope for variable_scope. |

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| ## Returns ||
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| The normalized `Tensor`. ||

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| ## Raises ||
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| `ValueError` | If dim is smaller than the number of dimensions in 'inputs'. |

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