panic("crypto/cipher: incorrect nonce length given to GCM") } counter := byteorder.BEUint64(nonce[len(nonce)-8:]) if !g.ready { // In the first call, the counter is zero, so we learn the XOR mask. g.ready = true g.mask = counter } counter ^= g.mask // Ensure the counter is monotonically increasing. if counter == math.MaxUint64 { panic("crypto/cipher: counter wrapped") } if counter < g.next { panic("crypto/cipher: counter decreased") } g.next = counter + 1 fips140.RecordApproved() return g.g.sealAfterIndicator(dst,...

because ul and ol\n  margin-bottom: 0;\n  @include border-radius(var(--#{$prefix}list-group-border-radius));\n}\n\n.list-group-numbered {\n  list-style-type: none;\n  counter-reset: section;\n\n  > .list-group-item::before {\n    // Increments only this instance of the section counter\n    content: counters(section, \".\") \". \";\n    counter-increment: section;\n  }\n}\n\n// Interactive list items\n//\n// Use anchor or button elements instead of `li`s or `div`s to create interactive\n// list items. Includes...

        a new API for creating `Dataset`s from lists of elements.
    *   Graduated experimental APIs:
        *   [`tf.data.Dataset.counter`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#counter),
            which creates `Dataset`s of indefinite sequences of numbers.
        *   [`tf.data.Dataset.ignore_errors`](https://www.tensorflow.org/api_docs/python/tf/data/Dataset/#ignore_errors),