Normalizes along dimension axis
using an L2 norm. (deprecated arguments)
tf.compat.v1.linalg.l2_normalize( x, axis=None, epsilon=1e-12, name=None, dim=None )
For a 1-D tensor with axis = 0
, computes
output = x / sqrt(max(sum(x**2), epsilon))
For x
with more dimensions, independently normalizes each 1-D slice along dimension axis
.
Args | |
---|---|
x | A Tensor . |
axis | 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). |
dim | Deprecated alias for axis. |
Returns | |
---|---|
A Tensor with the same shape as x . |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/compat/v1/linalg/l2_normalize