sampling if it encounters an empty dataset. This preserves the sampling
        ratio throughout training. The prior behavior was to continue sampling,
        skipping over exhausted datasets, until all datasets are exhausted. By
        default, the original behavior (`stop_on_empty_dataset=False`) is
        preserved.
    *   Removed previously deprecated tf.data statistics related APIs:

!g.startReady { // The first invocation sets the starting counter, if not fixed. g.startReady = true g.start = counter } counter -= g.start // Ensure the counter is strictly increasing. if counter == math.MaxUint64 { panic("crypto/cipher: counter exhausted") } if counter < g.next { panic("crypto/cipher: counter decreased or remained the same") } g.next = counter + 1 } fips140.RecordApproved() return g.g.sealAfterIndicator(dst, nonce, plaintext, data) } func (g *GCMWithCounterNonce) Open(dst, nonce,...