tf.raw_ops.RandomDataset
Creates a Dataset that returns pseudorandom numbers.
tf.raw_ops.RandomDataset(
seed, seed2, output_types, output_shapes, 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 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.
| 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. |
name |
A name for the operation (optional). |
| Returns | |
|---|---|
A Tensor of type variant. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/RandomDataset