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/r2.4/api_docs/python/tf/raw_ops/RandomDataset