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.