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`.
Public Methods
Output <Object> |
asOutput
()
Returns the symbolic handle of a tensor.
|
static SamplingDataset | |
Output <?> |
handle
()
|
Inherited Methods
Public Methods
public Output <Object> asOutput ()
Returns the symbolic handle of a 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 <Float> rate, Operand <Long> seed, Operand <Long> seed2, List<Class<?>> 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