RandomDataset

public final class RandomDataset

Creates a Dataset that returns pseudorandom numbers.

Creates a Dataset that returns a stream of uniformly distributed pseudorandom 64-bit signed integers.

In the TensorFlow Python API, you can instantiate this dataset via the class `tf.data.experimental.RandomDataset`.

Instances of this dataset are also created as a result of the `hoist_random_uniform` static optimization. Whether this optimization is performed is determined by the `experimental_optimization.hoist_random_uniform` option of `tf.data.Options`.

Constants

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

Public Methods

Output < TType >
asOutput ()
Returns the symbolic handle of the tensor.
static RandomDataset
create ( Scope scope, Operand < TInt64 > seed, Operand < TInt64 > seed2, List<Class<? extends TType >> outputTypes, List< Shape > outputShapes)
Factory method to create a class wrapping a new RandomDataset operation.
Output <?>

Inherited Methods

Constants

public static final String OP_NAME

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

Constant Value: "RandomDataset"

Public Methods

public Output < TType > 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 RandomDataset create ( Scope scope, Operand < TInt64 > seed, Operand < TInt64 > seed2, List<Class<? extends TType >> outputTypes, List< Shape > outputShapes)

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

Parameters
scope current scope
seed A scalar seed for the random number generator. If either seed or seed2 is set to be non-zero, the random number generator is seeded by the given seed. Otherwise, a random seed is used.
seed2 A second scalar seed to avoid seed collision.
Returns
  • a new instance of RandomDataset

public Output <?> handle ()