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 | |
Output<?> |
handle()
|
Inherited Methods
Constants
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
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