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`.