tf.raw_ops.RandomDataset | TensorFlow v2.16.1 (original) (raw)
tf.raw_ops.RandomDataset
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Creates a Dataset that returns pseudorandom numbers.
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tf.compat.v1.raw_ops.RandomDataset
tf.raw_ops.RandomDataset(
seed, seed2, output_types, output_shapes, metadata='', name=None
)
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 thehoist_random_uniform static optimization. Whether this optimization is performed is determined by the experimental_optimization.hoist_random_uniformoption of tf.data.Options.
| Args | |
|---|---|
| seed | A Tensor of type int64. 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 Tensor of type int64. A second scalar seed to avoid seed collision. |
| 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. |
| metadata | An optional string. Defaults to "". |
| name | A name for the operation (optional). |
| Returns |
|---|
| A Tensor of type variant. |