https://doi.org/10.6028/NIST.SP.800-185 package sha3 import ( "crypto/internal/fips140" "crypto/internal/fips140/subtle" "errors" ) // spongeDirection indicates the direction bytes are flowing through the sponge. type spongeDirection int const ( // spongeAbsorbing indicates that the sponge is absorbing input. spongeAbsorbing spongeDirection = iota // spongeSqueezing indicates that the sponge is being squeezed. spongeSqueezing ) type Digest struct { a [1600 / 8]byte // main state of the hash // a[n:rate] is the...

https://doi.org/10.6028/NIST.SP.800-185 package sha3 import ( "crypto/internal/fips140" "crypto/internal/fips140/subtle" "errors" ) // spongeDirection indicates the direction bytes are flowing through the sponge. type spongeDirection int const ( // spongeAbsorbing indicates that the sponge is absorbing input. spongeAbsorbing spongeDirection = iota // spongeSqueezing indicates that the sponge is being squeezed. spongeSqueezing ) type Digest struct { a [1600 / 8]byte // main state of the hash // a[n:rate] is the...

    *   `tf.data.Dataset.batch()` now supports `num_parallel_calls` and
        `deterministic` arguments. `num_parallel_calls` is used to indicate that
        multiple input batches should be computed in parallel. With
        `num_parallel_calls` set, `deterministic` is used to indicate that
        outputs can be obtained in the non-deterministic order.
    *   Options returned by `tf.data.Dataset.options()` are no longer mutable.