tf.raw_ops.RngReadAndSkip

Advance the counter of a counter-based RNG.

tf.raw_ops.RngReadAndSkip(
    resource, alg, delta, name=None
)

The state of the RNG after rng_read_and_skip(n) will be the same as that after uniform([n]) (or any other distribution). The actual increment added to the counter is an unspecified implementation choice.

In the case that the input algorithm is RNG_ALG_AUTO_SELECT, the counter in the state needs to be of size int64[2], the current maximal counter size among algorithms. In this case, this op will manage the counter as if it is an 128-bit integer with layout [lower_64bits, higher_64bits]. If an algorithm needs less than 128 bits for the counter, it should use the left portion of the int64[2]. In this way, the int64[2] is compatible with all current RNG algorithms (Philox, ThreeFry and xla::RandomAlgorithm::RNG_DEFAULT). Downstream RNG ops can thus use this counter with any RNG algorithm.

resource A Tensor of type resource. The handle of the resource variable that stores the state of the RNG. The state consists of the counter followed by the key.
alg A Tensor of type int32. The RNG algorithm.
delta A Tensor of type uint64. The amount of advancement.
name A name for the operation (optional).

A Tensor of type int64.