tf.math.l2_normalize
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Normalizes along dimension axis
using an L2 norm.
tf.math.l2_normalize(
x, axis=None, epsilon=1e-12, name=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).
|
Returns |
A Tensor with the same shape as x .
|
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.math.l2_normalize\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 1 version](/versions/r1.15/api_docs/python/tf/math/l2_normalize) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.0.0/tensorflow/python/ops/nn_impl.py#L627-L653) |\n\nNormalizes along dimension `axis` using an L2 norm.\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tf.linalg.l2_normalize`](/api_docs/python/tf/math/l2_normalize), [`tf.nn.l2_normalize`](/api_docs/python/tf/math/l2_normalize)\n\n\u003cbr /\u003e\n\n tf.math.l2_normalize(\n x, axis=None, epsilon=1e-12, name=None\n )\n\nFor a 1-D tensor with `axis = 0`, computes \n\n output = x / sqrt(max(sum(x**2), epsilon))\n\nFor `x` with more dimensions, independently normalizes each 1-D slice along\ndimension `axis`.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-----------|------------------------------------------------------------------------------------------------------|\n| `x` | A `Tensor`. |\n| `axis` | Dimension along which to normalize. A scalar or a vector of integers. |\n| `epsilon` | A lower bound value for the norm. Will use `sqrt(epsilon)` as the divisor if `norm \u003c sqrt(epsilon)`. |\n| `name` | A name for this operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor` with the same shape as `x`. ||\n\n\u003cbr /\u003e"]]