# tf.nn.l2_normalize(x, dim, epsilon=1e-12, name=None)

### tf.nn.l2_normalize(x, dim, epsilon=1e-12, name=None)

See the guide: Neural Network > Normalization

Normalizes along dimension dim using an L2 norm.

For a 1-D tensor with dim = 0, computes

output = x / sqrt(max(sum(x**2), epsilon))


For x with more dimensions, independently normalizes each 1-D slice along dimension dim.

#### Args:

• x: A Tensor.
• dim: Dimension along which to normalize. A scalar or a vector of integers.
• epsilon: A lower bound value for the norm. Will use sqrt(epsilon) as the divisor if norm < sqrt(epsilon).
• name: A name for this operation (optional).

#### Returns:

A Tensor with the same shape as x.

Defined in tensorflow/python/ops/nn_impl.py.