tf.raw_ops.SamplingDataset | TensorFlow v2.16.1 (original) (raw)
tf.raw_ops.SamplingDataset
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Creates a dataset that takes a Bernoulli sample of the contents of another dataset.
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tf.compat.v1.raw_ops.SamplingDataset
tf.raw_ops.SamplingDataset(
input_dataset, rate, seed, seed2, output_types, output_shapes, name=None
)
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_fusionstatic optimization. Whether this optimization is performed is determined by theexperimental_optimization.filter_with_random_uniform_fusion option oftf.data.Options.
| Args | |
|---|---|
| input_dataset | A Tensor of type variant. |
| rate | A Tensor of type float32. A scalar representing the sample rate. Each element of input_dataset is retained with this probability, independent of all other elements. |
| seed | A Tensor of type int64. A scalar representing seed of random number generator. |
| seed2 | A Tensor of type int64. A scalar representing seed2 of random number generator. |
| output_types | A list of tf.DTypes that has length >= 1. |
| output_shapes | A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1. |
| name | A name for the operation (optional). |
| Returns |
|---|
| A Tensor of type variant. |
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Last updated 2024-04-26 UTC.