Warning: This API is deprecated and will be removed in a future version of TensorFlow after the replacement is stable.

EuclideanNorm

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public final class EuclideanNorm

Computes the euclidean norm of elements across dimensions of a tensor.

Reduces `input` along the dimensions given in `axis`. Unless `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in `axis`. If `keep_dims` is true, the reduced dimensions are retained with length 1.

Nested Classes

class EuclideanNorm.Options Optional attributes for EuclideanNorm  

Public Methods

Output<T>
asOutput()
Returns the symbolic handle of a tensor.
static <T, U extends Number> EuclideanNorm<T>
create(Scope scope, Operand<T> input, Operand<U> axis, Options... options)
Factory method to create a class wrapping a new EuclideanNorm operation.
static EuclideanNorm.Options
keepDims(Boolean keepDims)
Output<T>
output()
The reduced tensor.

Inherited Methods

Public Methods

public Output<T> asOutput ()

Returns the symbolic handle of a tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static EuclideanNorm<T> create (Scope scope, Operand<T> input, Operand<U> axis, Options... options)

Factory method to create a class wrapping a new EuclideanNorm operation.

Parameters
scope current scope
input The tensor to reduce.
axis The dimensions to reduce. Must be in the range `[-rank(input), rank(input))`.
options carries optional attributes values
Returns
  • a new instance of EuclideanNorm

public static EuclideanNorm.Options keepDims (Boolean keepDims)

Parameters
keepDims If true, retain reduced dimensions with length 1.

public Output<T> output ()

The reduced tensor.