tf.compat.v1.linalg.l2_normalize
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/r2.3/api_docs/python/tf/compat/v1/linalg/l2_normalize