tf.nn.l2_normalize( x, axis=None, epsilon=1e-12, name=None, dim=None )
See the guide: Neural Network > Normalization
Normalizes along dimension
axis using an L2 norm. (deprecated arguments)
SOME ARGUMENTS ARE DEPRECATED. They will be removed in a future version. Instructions for updating: dim is deprecated, use axis instead
For a 1-D tensor with
axis = 0, computes
output = x / sqrt(max(sum(x**2), epsilon))
x with more dimensions, independently normalizes each 1-D slice along dimension
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.
Tensor with the same shape as
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Code samples licensed under the Apache 2.0 License.