tf.nn.l2_normalize
tf.nn.l2_normalize
tf.nn.l2_normalize
l2_normalize( x, dim, epsilon=1e-12, name=None )
Defined in tensorflow/python/ops/nn_impl.py
.
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
: ATensor
. -
dim
: Dimension along which to normalize. A scalar or a vector of integers. -
epsilon
: A lower bound value for the norm. Will usesqrt(epsilon)
as the divisor ifnorm < sqrt(epsilon)
. -
name
: A name for this operation (optional).
Returns:
A Tensor
with the same shape as x
.
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/nn/l2_normalize