Creates a dataset that takes a Bernoulli sample of the contents of another dataset.
There is no transformation in the tf.data Python API for creating this dataset.
Instead, it is created as a result of the `filter_with_random_uniform_fusion`
static optimization. Whether this optimization is performed is determined by the
`experimental_optimization.filter_with_random_uniform_fusion` 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 SamplingDataset | |
| 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 SamplingDataset create (Scope scope, Operand<?> inputDataset, Operand<TFloat32> rate, Operand<TInt64> seed, Operand<TInt64> seed2, List<Class<? extends TType>> outputTypes, List<Shape> outputShapes)
Factory method to create a class wrapping a new SamplingDataset operation.
Parameters
| scope | current scope |
|---|---|
| rate | A scalar representing the sample rate. Each element of `input_dataset` is retained with this probability, independent of all other elements. |
| seed | A scalar representing seed of random number generator. |
| seed2 | A scalar representing seed2 of random number generator. |
Returns
- a new instance of SamplingDataset