`RandomTranslation`, `RandomRotation`, `RandomHeight`, `RandomWidth`,
    `RandomZoom`, `RandomContrast`
*   Improved **`TextVectorization`** layer, which handles string tokenization,
    n-gram generation, and token encoding
    *   The `TextVectorization` layer now accounts for the mask_token as part of
        the vocabulary size when output_mode='int'. This means that, if you have

			a.Total = atomic.LoadInt64(&old.Total)
			a.N = atomic.LoadInt64(&old.N)
			e.mu.Lock()
			e.lastMinuteLatency.addAll(t-1, a)
			e.mu.Unlock()
			acc = newAcc
		} else {
			// We may be able to grab the new accumulator by yielding.
			runtime.Gosched()
			acc = e.cached.Load()
		}
	}
	atomic.AddInt64(&acc.N, 1)
	atomic.AddInt64(&acc.Total, int64(value))
	atomic.AddInt64(&acc.Size, sz)
}