StatelessParameterizedTruncatedNormal

public final class StatelessParameterizedTruncatedNormal

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

Output<V>
asOutput()
Returns the symbolic handle of the tensor.
static <V extends TNumber> StatelessParameterizedTruncatedNormal<V>
create(Scope scope, Operand<? extends TNumber> shape, Operand<? extends TNumber> seed, Operand<V> means, Operand<V> stddevs, Operand<V> minvals, Operand<V> maxvals)
Factory method to create a class wrapping a new StatelessParameterizedTruncatedNormal operation.
Output<V>
output()
The outputs are truncated normal samples and are a deterministic function of `shape`, `seed`, `minvals`, `maxvals`, `means` and `stddevs`.

Inherited Methods

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "StatelessParameterizedTruncatedNormal"

Public Methods

public Output<V> asOutput ()

Returns the symbolic handle of the 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 StatelessParameterizedTruncatedNormal<V> create (Scope scope, Operand<? extends TNumber> shape, Operand<? extends TNumber> seed, Operand<V> means, Operand<V> stddevs, Operand<V> minvals, Operand<V> maxvals)

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

Parameters
scope current scope
shape The shape of the output tensor.
seed 2 seeds (shape [2]).
means The mean parameter of each batch.
stddevs The standard deviation parameter of each batch. Must be greater than 0.
minvals The minimum cutoff. May be -infinity.
maxvals The maximum cutoff. May be +infinity, and must be more than the minval for each batch.
Returns
  • a new instance of StatelessParameterizedTruncatedNormal

public Output<V> output ()

The outputs are truncated normal samples and are a deterministic function of `shape`, `seed`, `minvals`, `maxvals`, `means` and `stddevs`.