tf.math.is_non_decreasing

Normalizes along dimension axis using an L2 norm.

View aliases

Main aliases

tf.linalg.l2_normalize, tf.nn.l2_normalize

tf.math.l2_normalize(
    x, axis=None, epsilon=1e-12, name=None
)

Used in the notebooks

Used in the tutorials
Universal Sentence Encoder TFP Release Notes notebook (0.11.0) TensorFlow Addons Losses: TripletSemiHardLoss TFP Release Notes notebook (0.12.1)

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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tf.math / is_non_decreasing

View aliases

Used in the notebooks

Args

Returns