# tf.contrib.layers.unit_norm

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


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

Note that the rank of input must be known.

#### Args:

• 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.

#### Returns:

The normalized Tensor.

#### Raises:

• ValueError: If dim is smaller than the number of dimensions in 'inputs'.