tf.contrib.layers.unit_norm

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

Defined in tensorflow/contrib/layers/python/layers/layers.py.

See the guide: Layers (contrib) > Higher level ops for building neural network layers

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'.