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.
|